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This web portal is built using the github repository at https://github.com/usnistgov/SEA-DATA.\nThe purpose of the National Advanced Spectrum and Communications Test Network (NASCTN) Citizens Broadband Radio Service (CBRS) Sharing Ecosystem Assessment (SEA) project is to provide data-driven insight into the CBRS sharing ecosystem\u2019s effectiveness between commercial and Department of Defense (DoD) incumbent systems, and to track changes in the spectrum environment over time. CBRS is the \u201cfirst of a kind\u201d nationwide shared spectrum ecosystem in the 3550-3700 MHz band. The implementation of this project included the installation of sensor systems at selected sites on the east and the west coast of the United States, along with a control and prototyping system in Boulder, Colorado. This data provides time and frequency selective power measurements from 3530 MHz -3710 MHz from summer 2024 to summer of 2026. This data is targeted at the commercial, military and civilian stakeholders of Citizen's Broadband Radio Service (CBRS) that would benefit from in-depth real time and longitudinal analysis of a shared spectrum environment. These data were collected with sensors running the IEEE 802.15.22.3 Spectrum Characterization and Occupancy Sensing (SCOS) sensor system. In addition, the data is formatted and saved using  SigMF (signal metadata format). This project was a collaboration between NIST, NTIA / ITS, NASA and MITRE.","distribution":[{"accessURL":"https://github.com/usnistgov/SEA-DATA","description":"The github repository that is used to build the nist.pages site.","format":"github repository","title":"SEA-Data Web Portal Github Repository"},{"accessURL":"https://pages.nist.gov/SEA-DATA/","description":"A static website describing how to access data from the NASCTN CBRS SEA program.","format":"html","title":"NASCTN CBRS SEA DATA INSTRUCTIONS"}],"identifier":"ark:/88434/mds2-4219","issued":"2026-06-24","keyword":["CBRS","ESC","NASCTN","Naval Radar","RF","SAS","Wireless"],"landingPage":"https://data.nist.gov/od/id/mds2-4219","language":["en"],"license":"https://www.nist.gov/open/license","modified":"2026-06-01 00:00:00","programCode":["006:045"],"publisher":{"@type":"org:Organization","name":"National Institute of Standards and Technology"},"references":["https://nvlpubs.nist.gov/nistpubs/TechnicalNotes/NIST.TN.2359.pdf","https://www.mitre.org/sites/default/files/2026-01/PR-25-3159-spectrum-monitoring-sensor-radio-service-assessment.pdf"],"theme":["Advanced Communications:Wireless (RF)"],"title":"SEA-DATA Web Portal"},"description":"Data Access Instructions for The NASCTN CBRS SEA program. This web portal is built using the github repository at https://github.com/usnistgov/SEA-DATA.\nThe purpose of the National Advanced Spectrum and Communications Test Network (NASCTN) Citizens Broadband Radio Service (CBRS) Sharing Ecosystem Assessment (SEA) project is to provide data-driven insight into the CBRS sharing ecosystem\u2019s effectiveness between commercial and Department of Defense (DoD) incumbent systems, and to track changes in the spectrum environment over time. CBRS is the \u201cfirst of a kind\u201d nationwide shared spectrum ecosystem in the 3550-3700 MHz band. The implementation of this project included the installation of sensor systems at selected sites on the east and the west coast of the United States, along with a control and prototyping system in Boulder, Colorado. This data provides time and frequency selective power measurements from 3530 MHz -3710 MHz from summer 2024 to summer of 2026. 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While conventional treatments predict two symmetric sidebands from independent $m_J$ transitions, experiments have reported additional unexplained spectral features. We show that these arise from elliptical RF polarization, which coherently couples multiple magnetic sublevels and requires a full multi-level treatment.\nWe develop and diagonalize a Hamiltonian including all coupled m_J sublevels, predicting polarization-dependent degeneracies that produce two, three, or four resolved peaks. Using long-wavelength transitions and an anechoic environment we realize homogeneous RF fields that for the first time enable complete resolution of the m_J-dependent dressed states. We observe excellent agreement with theory as the RF ellipticity is varied.\nThese results demonstrate that RF polarization fundamentally modifies Autler\u2013Townes spectra and provide a consistent framework for interpreting magnetic-sublevel structure, with implications for Rydberg-based RF electrometry and polarimetry.","distribution":[{"downloadURL":"https://data.nist.gov/od/ds/mds2-4157/4157_README.txt","mediaType":"text/plain","title":"readme"},{"downloadURL":"https://data.nist.gov/od/ds/mds2-4157/Fig2.csv","mediaType":"text/csv","title":"Figure 2"},{"downloadURL":"https://data.nist.gov/od/ds/mds2-4157/Fig3.csv","mediaType":"text/csv","title":"Figure 3"},{"downloadURL":"https://data.nist.gov/od/ds/mds2-4157/Fig4.csv","mediaType":"text/csv","title":"Figure 4"},{"downloadURL":"https://data.nist.gov/od/ds/mds2-4157/Fig5.csv","mediaType":"text/csv","title":"Figure 5"}],"identifier":"ark:/88434/mds2-4157","issued":"2026-07-23","keyword":["Rydberg atoms","atomic physics","electric field","fields strength","receivers","volts/meter"],"landingPage":"https://data.nist.gov/od/id/mds2-4157","language":["en"],"license":"https://www.nist.gov/open/license","modified":"2026-04-13 00:00:00","programCode":["006:045"],"publisher":{"@type":"org:Organization","name":"National Institute of Standards and Technology"},"theme":["Physics:Atomic, molecular, and quantum","Physics:Spectroscopy"],"title":"Data associated with \"Resolving magnetic-sublevel structure in Rydberg Autler-Townes spectra with arbitrary RF polarization\""},"description":"We investigate the role of magnetic sublevels in Autler\u2013Townes spectra of Rydberg atoms driven by radio-frequency (RF) fields with arbitrary polarization. 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We observe excellent agreement with theory as the RF ellipticity is varied.\nThese results demonstrate that RF polarization fundamentally modifies Autler\u2013Townes spectra and provide a consistent framework for interpreting magnetic-sublevel structure, with implications for Rydberg-based RF electrometry and polarimetry.","distribution_titles":["readme","Figure 2","Figure 3","Figure 4","Figure 5"],"harvest_record":"https://catalog.data.gov/harvest_record/8e91ef57-be55-4f5d-bfb7-cb1137aeb050","harvest_record_raw":"https://catalog.data.gov/harvest_record/8e91ef57-be55-4f5d-bfb7-cb1137aeb050/raw","has_download":true,"has_spatial":false,"identifier":"ark:/88434/mds2-4157","keyword":["Rydberg atoms","atomic physics","electric field","fields strength","receivers","volts/meter"],"last_harvested_date":"2026-09-02T19:19:36.584464","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"176f2a2d-ca9b-41f2-8df3-d93096ebdb85","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nist.png","name":"National Institute of Standards and Technology","organization_type":"Federal Government","slug":"nist"},"parent_identifier":null,"popularity":0,"publisher":"National Institute of Standards and Technology","slug":"data-associated-with-resolving-magnetic-sublevel-structure-in-rydberg-autler-townes-spectr","spatial_centroid":null,"spatial_shape":null,"theme":["Physics:Atomic, molecular, and quantum","Physics:Spectroscopy"],"title":"Data associated with \"Resolving magnetic-sublevel structure in Rydberg Autler-Townes spectra with arbitrary RF polarization\"","type":"dataset"},{"_score":2.992032,"_sort":[1788376775972,2.992032,0,"d034f1c1-28d0-4c2e-b434-41f027b9904a"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","accrualPeriodicity":"irregular","bureauCode":["006:55"],"contactPoint":{"fn":"Yamil Simon","hasEmail":"mailto:yamil.simon@nist.gov"},"description":"This mass spectrometry (MS) data set encompasses spectra of the extractables and leachables (E&L) of 100 polymer materials sourced from the Scientific Polymer Products Inc Polymer Samples Kit (see: SciPoly_PolymerSampleKit205_Items.xlsx). Extractions of these polymers were carried out using three HPLC-grade solvents of varying polarity (water, isopropanol, and hexane) with 10 mg polymer/mL solvent for 24 hours at 50 \u00b0C with shaking. To account for solvent volatility, extractions were carried out in 8 mL pressure tubes from Ace Glass Incorporated (Product #8648-25) (rated at 150 psig).\n\nExtraction solutions were subsequently analyzed using three ionization techniques: Electron Ionization (EI) with GC-MS and Electrospray Ionization (ESI) and Atmospheric Pressure Chemical Ionization (APCI) via LC-MS/MS on an Agilent QTOF 6530 and a Bruker timsTOF Pro 2, respectively.\n\nSeveral precautionary measures had to be taken following the extraction procedure. Extracts were centrifuged and filtered using 0.45-micron syringe filters to prevent prohibitively large particles from interfering with chromatography and MS analysis. Moreover, a guard column was used before the LC column to avoid contamination. As such, pressure build-up would often be a concern, so the LC and guard column had to be thoroughly flushed after each analysis batch.\n\nThousands of spectra were processed using in-house software, generating lists of identifications using the most recent versions of the NIST MS libraries via both direct and hybrid search methods. Some monomers were detected under the given extraction conditions, and many plastic additives (e.g., plasticizers, antioxidants, and processing agents) could be identified; some common examples found in many of the polymer standards include oleamide and palmitamide. High-quality unidentified spectra obtained from the extracts are included in a library of annotated recurrent unidentified spectra (ARUS).\n\nLC Chromatographic Separation Method: LC runs were performed using reversed-phase chromatography with an ACQUITY UPLC CSH C18 column (130 \u00c5 (13.0 nm), 1.7 \u00b5m, 2.1 mm x 100 mm), mobile phase A: water, and mobile phase B: acetonitrile (both mobile phases containing 0.1 % formic acid). The chromatographic separation method was as follows: injection volume: 10 \u00b5L, column temperature: 35\u00b0C, flow rate: 0.400 mL/min, and gradient: initial condition of 1.00% B, hold for 1.00 min, linear ramp to 80.00% B in 8.00 min, linear ramp to 99.00% B in 3.00 min, hold for 1.50 min, linear ramp to 1.00% B in 0.50 min, hold for 1.00 min. GC Chromatographic Separation Method: Spectra were obtained using an Agilent 5977B instrument, with GC runs performed using a Restek Rxi-5Sil MS GC Capillary Column (15 m x 250 \u00b5m x 0.25 \u00b5m) under 2 mL/min He flow. The initial oven temperature was 40\u00b0C (held for 3 min), with a ramp rate of 20\u00b0C/min, final temperature of 320\u00b0C, and final hold time of 3.75 min. \n\nReferences:\n\nBerthelette, K.; Walter, T. H. Column screening for the UPLC separation of plastic additives as part of extractables and leachables workflows; 720006777EN; Waters Corporation, MA, USA, 2020.\n\nLee, P. J.; Di Gioia, A. J. Rapid analysis of 25 common polymer additives; 720002488EN; Waters Corporation, Milford, MA, USA, 2008.\n\nSim\u00f3n-Manso, Y.; Erisman, E. P.; Mak, T. D.; Burke, M. C.; Zuber, A.; Yang, X.; Liang, Y.; Neta, P.; Bukhari, T.; Williams, A. J.; et al. NIST Mass Spectral Libraries in the Context of the Circular Economy of Plastics. J Am Soc Mass Spectrom 2025, 36 (2), 439\u2013445. 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Extractions of these polymers were carried out using three HPLC-grade solvents of varying polarity (water, isopropanol, and hexane) with 10 mg polymer/mL solvent for 24 hours at 50 \u00b0C with shaking. To account for solvent volatility, extractions were carried out in 8 mL pressure tubes from Ace Glass Incorporated (Product #8648-25) (rated at 150 psig).\n\nExtraction solutions were subsequently analyzed using three ionization techniques: Electron Ionization (EI) with GC-MS and Electrospray Ionization (ESI) and Atmospheric Pressure Chemical Ionization (APCI) via LC-MS/MS on an Agilent QTOF 6530 and a Bruker timsTOF Pro 2, respectively.\n\nSeveral precautionary measures had to be taken following the extraction procedure. Extracts were centrifuged and filtered using 0.45-micron syringe filters to prevent prohibitively large particles from interfering with chromatography and MS analysis. Moreover, a guard column was used before the LC column to avoid contamination. As such, pressure build-up would often be a concern, so the LC and guard column had to be thoroughly flushed after each analysis batch.\n\nThousands of spectra were processed using in-house software, generating lists of identifications using the most recent versions of the NIST MS libraries via both direct and hybrid search methods. Some monomers were detected under the given extraction conditions, and many plastic additives (e.g., plasticizers, antioxidants, and processing agents) could be identified; some common examples found in many of the polymer standards include oleamide and palmitamide. High-quality unidentified spectra obtained from the extracts are included in a library of annotated recurrent unidentified spectra (ARUS).\n\nLC Chromatographic Separation Method: LC runs were performed using reversed-phase chromatography with an ACQUITY UPLC CSH C18 column (130 \u00c5 (13.0 nm), 1.7 \u00b5m, 2.1 mm x 100 mm), mobile phase A: water, and mobile phase B: acetonitrile (both mobile phases containing 0.1 % formic acid). The chromatographic separation method was as follows: injection volume: 10 \u00b5L, column temperature: 35\u00b0C, flow rate: 0.400 mL/min, and gradient: initial condition of 1.00% B, hold for 1.00 min, linear ramp to 80.00% B in 8.00 min, linear ramp to 99.00% B in 3.00 min, hold for 1.50 min, linear ramp to 1.00% B in 0.50 min, hold for 1.00 min. GC Chromatographic Separation Method: Spectra were obtained using an Agilent 5977B instrument, with GC runs performed using a Restek Rxi-5Sil MS GC Capillary Column (15 m x 250 \u00b5m x 0.25 \u00b5m) under 2 mL/min He flow. The initial oven temperature was 40\u00b0C (held for 3 min), with a ramp rate of 20\u00b0C/min, final temperature of 320\u00b0C, and final hold time of 3.75 min. \n\nReferences:\n\nBerthelette, K.; Walter, T. H. Column screening for the UPLC separation of plastic additives as part of extractables and leachables workflows; 720006777EN; Waters Corporation, MA, USA, 2020.\n\nLee, P. J.; Di Gioia, A. J. Rapid analysis of 25 common polymer additives; 720002488EN; Waters Corporation, Milford, MA, USA, 2008.\n\nSim\u00f3n-Manso, Y.; Erisman, E. P.; Mak, T. D.; Burke, M. C.; Zuber, A.; Yang, X.; Liang, Y.; Neta, P.; Bukhari, T.; Williams, A. J.; et al. NIST Mass Spectral Libraries in the Context of the Circular Economy of Plastics. 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From numerical simulations of SWAP using our laser beam geometry, we find that SWAP provides greater cooling than triangle wave frequency modulation despite the complex polarization environment of a grating MOT. The simulation is confirmed by experimental results, which show a factor of two improvement in transfer efficiency between a dipole-allowed transition grating MOT and an intercombination transition grating MOT.\nThe data show that the intercombination line grating MOT can trap up to three million strontium atoms at an average temperature of 4.9 microkelvin with a lifetime of approximately 0.7 seconds.\n\nInstructions on reproducing the figures in the manuscript are included in 4097_README.txt.","distribution":[{"description":"README file for the .zip archive.","downloadURL":"https://data.nist.gov/od/ds/mds2-4097/4097_README.txt","format":".txt","mediaType":"text/plain","title":"README"},{"downloadURL":"https://data.nist.gov/od/ds/mds2-4097/figure_generation_data.zip","mediaType":"application/zip","title":"figure_generation_data"}],"identifier":"ark:/88434/mds2-4097","issued":"2026-05-21","keyword":["atomic physics","laser cooling","quantum physics"],"landingPage":"https://data.nist.gov/od/id/mds2-4097","language":["en"],"license":"https://www.nist.gov/open/license","modified":"2026-02-09 00:00:00","programCode":["006:045"],"publisher":{"@type":"org:Organization","name":"National Institute of Standards and Technology"},"references":["https://doi.org/10.48550/arXiv.2602.06230"],"theme":["Physics:Atomic, molecular, and quantum"],"title":"Data associated with \"Sawtooth wave adiabatic passage in a grating magneto-optical trap\""},"description":"Numerical values of data points and figure generation scripts for manuscript \"Sawtooth wave adiabatic passage in a grating magneto-optical trap\" submitted for publication and available on ArXiv (2602.06230).\n\nThis data set demonstrates sawtooth wave adiabatic passage (SWAP) in a grating magneto-optical trap (MOT) operating on the intercombination transition of neutral strontium. From numerical simulations of SWAP using our laser beam geometry, we find that SWAP provides greater cooling than triangle wave frequency modulation despite the complex polarization environment of a grating MOT. 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We have also extracted three exemplar channels that capture key features of a work-cell-sized industrial environment from measurements made with the same synthetic 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channel; industrial internet of things; industrial wireless systems; millimeter-wave wireless; synthetic aperture; wireless system."],"landingPage":"https://data.nist.gov/od/id/mds2-4030","language":["en"],"license":"https://www.nist.gov/open/license","modified":"2025-12-03 00:00:00","programCode":["006:045"],"publisher":{"@type":"org:Organization","name":"National Institute of Standards and Technology"},"theme":["Advanced Communications:Advanced Communications"],"title":"Standardized Approach for Assessing Wireless IoT Devices in Millimeter-Wave Industrial Work-Cell Channels"},"description":"In this paper, we present a standardized, repeatable test approach that replicates key features of measured industrial environments in a fully-characterized hybrid test chamber. The hybrid chamber consists of an anechoic chamber along with movable metallic spheres that provide discrete reconfigurable multipath components. The chamber is characterized by a synthetic-aperture system providing a reference measurement that captures the non-idealities of the chamber along with the intended spatial multipath, completing characterization of the test environment. A key feature of our approach is the propagation of correlated uncertainties through to the final system response \u2013 including uncertainties specific to synthetic apertures such as cable bending due to scanning and inexact positioner locations. The uncertainty analysis provides statistically accurate knowledge of the environment, allowing separation of measurement errors from errors related to the device or system under test. 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This data will be used to develop software solutions for detecting that trigger behavior in the trained AI models.","distribution_titles":["rl-safetygymnasium-oct2024-test"],"harvest_record":"https://catalog.data.gov/harvest_record/79dae698-3893-4218-b778-f33a54e498a3","harvest_record_raw":"https://catalog.data.gov/harvest_record/79dae698-3893-4218-b778-f33a54e498a3/raw","has_download":false,"has_spatial":false,"identifier":"ark:/88434/mds2-3899","keyword":["Trojan Detection; Artificial Intelligence; AI; Machine Learning; Adversarial Machine Learning;"],"last_harvested_date":"2026-09-02T19:19:20.089417","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"176f2a2d-ca9b-41f2-8df3-d93096ebdb85","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nist.png","name":"National Institute of Standards and Technology","organization_type":"Federal Government","slug":"nist"},"parent_identifier":null,"popularity":0,"publisher":"National Institute of Standards and Technology","slug":"trojan-detection-software-challenge-rl-safetygymnasium-oct2024-test","spatial_centroid":null,"spatial_shape":null,"theme":["Information Technology:Cybersecurity","Information Technology:Software research"],"title":"Trojan Detection Software Challenge - rl-safetygymnasium-oct2024-test","type":"dataset"},{"_score":21.794712,"_sort":[1788376754340,21.794712,1,"7c917a2d-7d31-4492-815f-a7b8d43b1439"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["006:55"],"contactPoint":{"fn":"Junxiao Shi","hasEmail":"mailto:junxiao.shi@nist.gov"},"description":"This is a set of scripts to deploy and control 5G network.\nIt is primarily useful for running an emulated 5G network in Docker Compose environment.","distribution":[{"accessURL":"https://github.com/usnistgov/5gdeploy","title":"GitHub repository"}],"identifier":"ark:/88434/mds2-3794","issued":"2025-04-10","keyword":["3GPP","5G core network","5G network","Docker Compose"],"language":["en"],"license":"https://www.nist.gov/open/license","modified":"2025-04-02 00:00:00","programCode":["006:045"],"publisher":{"@type":"org:Organization","name":"National Institute of Standards and Technology"},"theme":["Information Technology:Mobile","Information Technology:Networking"],"title":"5gdeploy: 5G Core Deployment Helper"},"description":"This is a set of scripts to deploy and control 5G network.\nIt is primarily useful for running an emulated 5G network in Docker Compose environment.","distribution_titles":["GitHub repository"],"harvest_record":"https://catalog.data.gov/harvest_record/16e5b218-3519-4961-a020-7413e2989f10","harvest_record_raw":"https://catalog.data.gov/harvest_record/16e5b218-3519-4961-a020-7413e2989f10/raw","has_download":false,"has_spatial":false,"identifier":"ark:/88434/mds2-3794","keyword":["3GPP","5G core network","5G network","Docker Compose"],"last_harvested_date":"2026-09-02T19:19:14.340266","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"176f2a2d-ca9b-41f2-8df3-d93096ebdb85","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nist.png","name":"National Institute of Standards and Technology","organization_type":"Federal Government","slug":"nist"},"parent_identifier":null,"popularity":1,"publisher":"National Institute of Standards and Technology","slug":"5gdeploy-5g-core-deployment-helper","spatial_centroid":null,"spatial_shape":null,"theme":["Information Technology:Mobile","Information Technology:Networking"],"title":"5gdeploy: 5G Core Deployment Helper","type":"dataset"},{"_score":15.05718,"_sort":[1788376752188,15.05718,2,"2c9d9995-294f-4529-91f9-36f59e0c8647"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","accrualPeriodicity":"R/PT1S","bureauCode":["006:55"],"contactPoint":{"fn":"Thomas Roth","hasEmail":"mailto:thomas.roth@nist.gov"},"description":"The Internet of Things (IoT) is comprised of networks of physical, computational, and human components that coordinate to fulfill time-sensitive functions in a shared operating environment. Development and testing of IoT systems often utilizes modeling and simulation, whether to analyze potential performance gains of new technologies or develop robust digital twins to support future operations and maintenance. However, the complexity and scale of IoT means that individual simulators are often inadequate to simulate the real-world dynamics of such systems, and simulators must be combined with other software or hardware.\n\nThe National Institute of Standards and Technology (NIST) has developed a software module that extends the ns-3 network simulator with a new capability to communicate with external software and hardware at runtime. This software facilitates the development of co-simulations where ns-3 models can synchronize and exchange data with external processes to develop higher-fidelity simulations. The software is open-source and available on the NIST GitHub.","distribution":[{"accessURL":"https://github.com/usnistgov/ns3-cosim","description":"A GitHub page that includes the documentation and source code for the software.","format":"GitHub Software Repository","title":"ns-3 Gateway Software Repository"}],"identifier":"ark:/88434/mds2-3738","issued":"2025-03-31","keyword":["automated vehicles","co-simulation","cyber-physical systems","internet of things","network simulation","ns-3","software"],"landingPage":"https://data.nist.gov/od/id/mds2-3738","language":["en"],"license":"https://www.nist.gov/open/license","modified":"2025-02-18 00:00:00","programCode":["006:045"],"publisher":{"@type":"org:Organization","name":"National Institute of Standards and Technology"},"theme":["Advanced Communications:Wireless (RF)","Information Technology:Cyber-physical systems","Information Technology:Internet of Things","Information Technology:Networking","Transportation:Automotive"],"title":"Gateway for Co-Simulation using ns-3"},"description":"The Internet of Things (IoT) is comprised of networks of physical, computational, and human components that coordinate to fulfill time-sensitive functions in a shared operating environment. Development and testing of IoT systems often utilizes modeling and simulation, whether to analyze potential performance gains of new technologies or develop robust digital twins to support future operations and maintenance. However, the complexity and scale of IoT means that individual simulators are often inadequate to simulate the real-world dynamics of such systems, and simulators must be combined with other software or hardware.\n\nThe National Institute of Standards and Technology (NIST) has developed a software module that extends the ns-3 network simulator with a new capability to communicate with external software and hardware at runtime. This software facilitates the development of co-simulations where ns-3 models can synchronize and exchange data with external processes to develop higher-fidelity simulations. The software is open-source and available on the NIST GitHub.","distribution_titles":["ns-3 Gateway Software Repository"],"harvest_record":"https://catalog.data.gov/harvest_record/15b3c00a-24e1-44e2-9629-b5a704ad4bb6","harvest_record_raw":"https://catalog.data.gov/harvest_record/15b3c00a-24e1-44e2-9629-b5a704ad4bb6/raw","has_download":false,"has_spatial":false,"identifier":"ark:/88434/mds2-3738","keyword":["automated vehicles","co-simulation","cyber-physical systems","internet of things","network simulation","ns-3","software"],"last_harvested_date":"2026-09-02T19:19:12.188135","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"176f2a2d-ca9b-41f2-8df3-d93096ebdb85","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nist.png","name":"National Institute of Standards and Technology","organization_type":"Federal Government","slug":"nist"},"parent_identifier":null,"popularity":2,"publisher":"National Institute of Standards and Technology","slug":"gateway-for-co-simulation-using-ns-3","spatial_centroid":null,"spatial_shape":null,"theme":["Advanced Communications:Wireless (RF)","Information Technology:Cyber-physical systems","Information Technology:Internet of Things","Information Technology:Networking","Transportation:Automotive"],"title":"Gateway for Co-Simulation using ns-3","type":"dataset"},{"_score":8.920153,"_sort":[1788376751219,8.920153,6,"f907a22c-7304-4e4c-b7d4-dc921d42c75a"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["006:55"],"contactPoint":{"fn":"Justyna Zwolak","hasEmail":"mailto:justyna.zwolak@nist.gov"},"description":"The dataset underlying the figures in the manuscript is \"Modular Autonomous Virtualization System for Two-Dimensional Semiconductor Quantum Dot Arrays.\"\n\nAbstract of the paper: Arrays of gate-defined semiconductor quantum dots are among the leading candidates for building scalable quantum processors. High-fidelity initialization, control, and readout of spin qubit registers require exquisite and targeted control over key Hamiltonian parameters that define the electrostatic environment. However, due to the tight gate pitch, capacitive crosstalk between gates hinders independent tuning of chemical potentials and interdot couplings. While virtual gates offer a practical solution, determining all the required cross-capacitance matrices accurately and efficiently in large quantum dot registers is an open challenge. Here, we establish a Modular Automated Virtualization System (MAViS) -- a general and modular framework for autonomously constructing a complete stack of multi-layer virtual gates in real time. Our method employs machine learning techniques to rapidly extract features from two-dimensional charge stability diagrams. We then utilize computer vision and regression models to self-consistently determine all relative capacitive couplings necessary for virtualizing plunger and barrier gates in both low- and high-tunnel-coupling regimes. Using MAViS, we successfully demonstrate accurate virtualization of a dense two-dimensional array comprising ten quantum dots defined in a high-quality Ge/SiGe heterostructure. Our work offers an elegant and practical solution for the efficient control of large-scale semiconductor quantum dot systems.\n\nData description: Each figure folder contains a complete set of files necessary to reproduce figures, including Jupyter Notebooks with the figure source code, Adobe Illustrator, and pre-processed data files (hdf5 and pkl). The complete set of all raw data files used in this study is available at Zenodo. [doi: 10.5281/zenodo.14173838].\n\nAcknowledgments: This research was sponsored in part by the Army Research Office (ARO) under Awards No. W911NF-23-1-0110 and W911NF-23-1-0258. We acknowledge support from the European Union through the IGNITE project with grant agreement No. 101069515 and from the Dutch Research Council (NWO) via the National Growth Fund program Quantum Delta NL (Grant No. NGF.1582.22.001). The views, conclusions, and recommendations contained in this paper are those of the authors and are not necessarily endorsed nor should they be interpreted as representing the official policies, either expressed or implied, of the Army Research Office (ARO) or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright noted herein. Any mention of commercial products is for information only; it does not imply recommendation or endorsement by the National Institute of Standards and Technology.","distribution":[{"downloadURL":"https://data.nist.gov/od/ds/mds2-3705/Figure-1.zip","mediaType":"application/zip","title":"Figure-1"},{"downloadURL":"https://data.nist.gov/od/ds/mds2-3705/Figure-2.zip","mediaType":"application/zip","title":"Figure-2"},{"downloadURL":"https://data.nist.gov/od/ds/mds2-3705/Figure-3.zip","mediaType":"application/zip","title":"Figure-3"},{"downloadURL":"https://data.nist.gov/od/ds/mds2-3705/Figure-4.zip","mediaType":"application/zip","title":"Figure-4"},{"downloadURL":"https://data.nist.gov/od/ds/mds2-3705/Figure-5.zip","mediaType":"application/zip","title":"Figure-5"},{"downloadURL":"https://data.nist.gov/od/ds/mds2-3705/Figure-SM1.zip","mediaType":"application/zip","title":"Figure-SM1"},{"downloadURL":"https://data.nist.gov/od/ds/mds2-3705/Figure-SM2.zip","mediaType":"application/zip","title":"Figure-SM2"},{"downloadURL":"https://data.nist.gov/od/ds/mds2-3705/Figure-SM3.zip","mediaType":"application/zip","title":"Figure-SM3"},{"downloadURL":"https://data.nist.gov/od/ds/mds2-3705/Figure-SM4.zip","mediaType":"application/zip","title":"Figure-SM4"},{"downloadURL":"https://data.nist.gov/od/ds/mds2-3705/Figure-SM5.zip","mediaType":"application/zip","title":"Figure-SM5"},{"downloadURL":"https://data.nist.gov/od/ds/mds2-3705/Figure-SM6.zip","mediaType":"application/zip","title":"Figure-SM6"},{"downloadURL":"https://data.nist.gov/od/ds/mds2-3705/Figure-SM7.zip","mediaType":"application/zip","title":"Figure-SM7"},{"downloadURL":"https://data.nist.gov/od/ds/mds2-3705/Figure-SM8.zip","mediaType":"application/zip","title":"Figure-SM8"},{"downloadURL":"https://data.nist.gov/od/ds/mds2-3705/README.txt","mediaType":"text/plain","title":"README"}],"identifier":"ark:/88434/mds2-3705","issued":"2025-03-17","keyword":["2D arrays","autonomous control","germanium quantum dots","machine learning","quantum dots"],"language":["en"],"license":"https://www.nist.gov/open/license","modified":"2025-02-03 00:00:00","programCode":["006:045"],"publisher":{"@type":"org:Organization","name":"National Institute of Standards and Technology"},"references":["https://doi.org/10.48550/arXiv.2411.12516"],"theme":["Information Technology:Data and informatics","Mathematics and Statistics:Image and signal processing","Mathematics and Statistics:Numerical methods and software","Physics:Condensed matter","Physics:Quantum information science"],"title":"Figure files for \"Modular Autonomous Virtualization System for Two-Dimensional Semiconductor Quantum Dot Arrays\" submitted to Physical Review X"},"description":"The dataset underlying the figures in the manuscript is \"Modular Autonomous Virtualization System for Two-Dimensional Semiconductor Quantum Dot Arrays.\"\n\nAbstract of the paper: Arrays of gate-defined semiconductor quantum dots are among the leading candidates for building scalable quantum processors. 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We then utilize computer vision and regression models to self-consistently determine all relative capacitive couplings necessary for virtualizing plunger and barrier gates in both low- and high-tunnel-coupling regimes. Using MAViS, we successfully demonstrate accurate virtualization of a dense two-dimensional array comprising ten quantum dots defined in a high-quality Ge/SiGe heterostructure. Our work offers an elegant and practical solution for the efficient control of large-scale semiconductor quantum dot systems.\n\nData description: Each figure folder contains a complete set of files necessary to reproduce figures, including Jupyter Notebooks with the figure source code, Adobe Illustrator, and pre-processed data files (hdf5 and pkl). The complete set of all raw data files used in this study is available at Zenodo. [doi: 10.5281/zenodo.14173838].\n\nAcknowledgments: This research was sponsored in part by the Army Research Office (ARO) under Awards No. W911NF-23-1-0110 and W911NF-23-1-0258. We acknowledge support from the European Union through the IGNITE project with grant agreement No. 101069515 and from the Dutch Research Council (NWO) via the National Growth Fund program Quantum Delta NL (Grant No. NGF.1582.22.001). The views, conclusions, and recommendations contained in this paper are those of the authors and are not necessarily endorsed nor should they be interpreted as representing the official policies, either expressed or implied, of the Army Research Office (ARO) or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright noted herein. Any mention of commercial products is for information only; it does not imply recommendation or endorsement by the National Institute of Standards and Technology.","distribution_titles":["Figure-1","Figure-2","Figure-3","Figure-4","Figure-5","Figure-SM1","Figure-SM2","Figure-SM3","Figure-SM4","Figure-SM5","Figure-SM6","Figure-SM7","Figure-SM8","README"],"harvest_record":"https://catalog.data.gov/harvest_record/7280205e-e86b-4879-b15f-cb0f896b964f","harvest_record_raw":"https://catalog.data.gov/harvest_record/7280205e-e86b-4879-b15f-cb0f896b964f/raw","has_download":true,"has_spatial":false,"identifier":"ark:/88434/mds2-3705","keyword":["2D arrays","autonomous control","germanium quantum dots","machine learning","quantum dots"],"last_harvested_date":"2026-09-02T19:19:11.219874","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"176f2a2d-ca9b-41f2-8df3-d93096ebdb85","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nist.png","name":"National Institute of Standards and Technology","organization_type":"Federal Government","slug":"nist"},"parent_identifier":null,"popularity":6,"publisher":"National Institute of Standards and Technology","slug":"figure-files-for-modular-autonomous-virtualization-system-for-two-dimensional-semiconducto","spatial_centroid":null,"spatial_shape":null,"theme":["Information Technology:Data and informatics","Mathematics and Statistics:Image and signal processing","Mathematics and Statistics:Numerical methods and software","Physics:Condensed matter","Physics:Quantum information science"],"title":"Figure files for \"Modular Autonomous Virtualization System for Two-Dimensional Semiconductor Quantum Dot Arrays\" submitted to Physical Review X","type":"dataset"},{"_score":20.86201,"_sort":[1788376750223,20.86201,35,"a3ff116f-9b4b-46c5-ae8f-082bb819ea1a"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","accrualPeriodicity":"irregular","bureauCode":["006:55"],"contactPoint":{"fn":"Tony Wang","hasEmail":"mailto:tony.wang@nist.gov"},"description":"AgentDojo-Inspect is a codebase created by the U.S. AI Safety Institute to facilitate research into agent hijacking and defenses against said hijacking. Agent hijacking is a type of indirect prompt injection\u00a0[1] in which an attacker inserts malicious instructions into data that may be ingested by an AI agent, causing it to take unintended, harmful actions.\n\nAgentDojo-Inspect is a fork of the original AgentDojo repository [2], which was created by\u00a0researchers at ETH Zurich [3]. This fork extends the upstream AgentDojo in four key ways:\n\n1. It adds an Inspect bridge that allows AgentDojo evaluations to be run using the Inspect evaluations framework [4] (see below for more details).\n\n2. It fixes some bugs in the upstream AgentDojo's task suites (most of these fixes have been merged upstream). It also removes certain tasks that are of low quality.\n\n3. It adds new injection tasks in the Workspace environment that have to do with mass data exfiltration (these have since been merged upstream).\n\n4. It adds a new terminal environment and associated tasks that test for remote code execution vulnerabilities in this environment.\n\n[1] Greshake K, Abdelnabi S, Mishra S, Endres C, Holz T, Fritz M (2023) Not what you?ve signed up for: Compromising Real-World LLM-Integrated Applications with Indirect Prompt Injection (arXiv), arXiv:2302.12173. https://doi.org/10.48550/arXiv.2302.12173\n\n[2] Edoardo Debenedetti (2025) ethz-spylab/agentdojo. Available at https://github.com/ethz-spylab/agentdojo.\n\n[3] Debenedetti E, Zhang J, Balunovi? M, Beurer-Kellner L, Fischer M, Tram\u00e8r F (2024) AgentDojo: A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents (arXiv), arXiv:2406.13352. https://doi.org/10.48550/arXiv.2406.13352\n\n[4] UK AI Safety Institute (2024) Inspect AI: Framework for Large Language Model\u00a0Evaluations. 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Agent hijacking is a type of indirect prompt injection\u00a0[1] in which an attacker inserts malicious instructions into data that may be ingested by an AI agent, causing it to take unintended, harmful actions.\n\nAgentDojo-Inspect is a fork of the original AgentDojo repository [2], which was created by\u00a0researchers at ETH Zurich [3]. This fork extends the upstream AgentDojo in four key ways:\n\n1. It adds an Inspect bridge that allows AgentDojo evaluations to be run using the Inspect evaluations framework [4] (see below for more details).\n\n2. It fixes some bugs in the upstream AgentDojo's task suites (most of these fixes have been merged upstream). It also removes certain tasks that are of low quality.\n\n3. It adds new injection tasks in the Workspace environment that have to do with mass data exfiltration (these have since been merged upstream).\n\n4. It adds a new terminal environment and associated tasks that test for remote code execution vulnerabilities in this environment.\n\n[1] Greshake K, Abdelnabi S, Mishra S, Endres C, Holz T, Fritz M (2023) Not what you?ve signed up for: Compromising Real-World LLM-Integrated Applications with Indirect Prompt Injection (arXiv), arXiv:2302.12173. https://doi.org/10.48550/arXiv.2302.12173\n\n[2] Edoardo Debenedetti (2025) ethz-spylab/agentdojo. Available at https://github.com/ethz-spylab/agentdojo.\n\n[3] Debenedetti E, Zhang J, Balunovi? M, Beurer-Kellner L, Fischer M, Tram\u00e8r F (2024) AgentDojo: A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents (arXiv), arXiv:2406.13352. https://doi.org/10.48550/arXiv.2406.13352\n\n[4] UK AI Safety Institute (2024) Inspect AI: Framework for Large Language Model\u00a0Evaluations. 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Trustworthy AI is: valid and reliable, safe, secure and resilient, accountable and transparent, explainable and interpretable, privacy-enhanced, and fair - with harmful bias managed1. Dioptra supports the Measure function of the NIST AI Risk Management Framework by providing functionality to assess, analyze, and track identified AI risks.\n\nDioptra provides a REST API, which can be controlled via an intuitive web interface, a Python client, or any REST client library of the user's choice for designing, managing, executing, and tracking experiments. Details are available in the project documentation available at https://pages.nist.gov/dioptra/.\n\nUse Cases\nWe envision the following primary use cases for Dioptra:\n- Model Testing:\n  -- 1st party - Assess AI models throughout the development lifecycle\n  -- 2nd party - Assess AI models during acquisition or in an evaluation lab environment\n  -- 3rd party - Assess AI models during auditing or compliance activities\n- Research: Aid trustworthy AI researchers in tracking experiments\n- Evaluations and Challenges: Provide a common platform and resources for participants\n- Red-Teaming: Expose models and resources to a red team in a controlled environment\n\nKey Properties\nDioptra strives for the following key properties:\n- Reproducible: Dioptra automatically creates snapshots of resources so experiments can be reproduced and validated\n- Traceable: The full history of experiments and their inputs are tracked\n- Extensible: Support for expanding functionality and importing existing Python packages via a plugin system\n- Interoperable: A type system promotes interoperability between plugins\n- Modular: New experiments can be composed from modular components in a simple yaml file\n- Secure: Dioptra provides user authentication with access controls coming soon\n- Interactive: Users can interact with Dioptra via an intuitive web interface\n- Shareable and Reusable: Dioptra can be deployed in a multi-tenant environment so users can share and reuse components\n","distribution":[{"accessURL":"https://github.com/usnistgov/dioptra","description":"The USNIST Github location where source code is located.","format":"Github Repository","title":"Dioptra Github Repository"}],"identifier":"ark:/88434/mds2-3398","issued":"2024-07-11","keyword":["AI; Trustworthy AI; Test; Evaluation; Adversarial Machine Learning; Machine Learning; TEVV"],"landingPage":"https://data.nist.gov/od/id/mds2-3398","language":["en"],"license":"https://www.nist.gov/open/license","modified":"2024-07-24 00:00:00","programCode":["006:045"],"publisher":{"@type":"org:Organization","name":"National Institute of Standards and Technology"},"theme":["Information Technology:Cybersecurity"],"title":"Dioptra Test Platform"},"description":"Source code, documentation, and examples of use of the source code for the Dioptra Test Platform.\n\nDioptra is a software test platform for assessing the trustworthy characteristics of artificial intelligence (AI). 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This dataset was generated by TechSolve Inc. (techsolve.org) as a collaborative effort with NIST. Respondents were asked to observe and evaluate a machining process in which a rotary bit (the \"tool\") removed layers of a workpiece until the tool was worn to exhaustion. One trial and 19 official experiments were completed, one for each of 20 tools. 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This data is published for research academic and related non-commercial purposes consistent with NIST?s mandate to further the science and the promulgation of appropriate standards. \n\nThis dataset was used in the following publication and this archive represents the static archive of the data used in the publication and is not updated or modified: \n \nSahu, S., Ahn, D., Loughner, C., and Dickerson, R., \"Influence of synoptic weather patterns on methane mixing ratios in the Baltimore/Washington region\", Atmospheric Environment, Volume 334, 2024, 120675, ISSN 1352-2310,\nhttps://doi.org/10.1016/j.atmosenv.2024.120675.\n\nData is described further in the Readme document and references cited 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gas measurements","Methane","Washington DC","northeast corridor","urban testbed"],"landingPage":"https://data.nist.gov/od/id/mds2-3200","language":["en"],"license":"https://www.nist.gov/open/license","modified":"2024-03-18 00:00:00","programCode":["006:047"],"publisher":{"@type":"org:Organization","name":"National Institute of Standards and Technology"},"references":["https://doi.org/10.1016/j.atmosenv.2024.120675","https://doi.org/10.5194/essd-12-699-2020"],"rights":"Non-commercial use only.","temporal":"2015-01-01/2022-12-31","theme":["Environment:Greenhouse gas measurements"],"title":"In situ methane mole fraction observations from three sites in the Washington DC region from the NIST Northeast Corridor Project: January 2015 - December 2022"},"description":"Methane (CH4) mole fraction data collected from three tower sites in the Washington DC area: Bucktown, MD (BUC, ghg01), Stafford, VA (SFD, ghg65), and Thurmont, MD (TMD, ghg61), as part \nof NIST's Northeast Corridor Urban Testbed project, presented as 1-minute averages.  This data is published for research academic and related non-commercial purposes consistent with NIST?s mandate to further the science and the promulgation of appropriate standards. \n\nThis dataset was used in the following publication and this archive represents the static archive of the data used in the publication and is not updated or modified: \n \nSahu, S., Ahn, D., Loughner, C., and Dickerson, R., \"Influence of synoptic weather patterns on methane mixing ratios in the Baltimore/Washington region\", Atmospheric Environment, Volume 334, 2024, 120675, ISSN 1352-2310,\nhttps://doi.org/10.1016/j.atmosenv.2024.120675.\n\nData is described further in the Readme document and references cited within.\n","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/a834fc0e-0589-4685-b89a-6125ced4b1f4","harvest_record_raw":"https://catalog.data.gov/harvest_record/a834fc0e-0589-4685-b89a-6125ced4b1f4/raw","has_download":true,"has_spatial":false,"identifier":"ark:/88434/mds2-3200","keyword":["Bucktown","Greenhouse gas measurements","Methane","Washington DC","northeast corridor","urban testbed"],"last_harvested_date":"2026-09-02T19:18:54.532225","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"176f2a2d-ca9b-41f2-8df3-d93096ebdb85","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nist.png","name":"National Institute of Standards and Technology","organization_type":"Federal Government","slug":"nist"},"parent_identifier":null,"popularity":2,"publisher":"National Institute of Standards and Technology","slug":"in-situ-methane-mole-fraction-observations-from-three-sites-in-the-washington-dc-regi-2022","spatial_centroid":null,"spatial_shape":null,"theme":["Environment:Greenhouse gas measurements"],"title":"In situ methane mole fraction observations from three sites in the Washington DC region from the NIST Northeast Corridor Project: January 2015 - December 2022","type":"dataset"},{"_score":27.847569,"_sort":[1788376731389,27.847569,2,"bc5de985-89d5-4fa6-8e85-0457e84284ef"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","accrualPeriodicity":"irregular","bureauCode":["006:55"],"contactPoint":{"fn":"Alain Rufenacht","hasEmail":"mailto:alain.rufenacht@nist.gov"},"description":"The abstract of the paper [1] is:\n\nThis paper describes differential sampling measurements of an ac source and a Josephson arbitrary waveform synthesizer (JAWS).\nA new iterative approach for aligning the phases of the JAWS and the source waveforms was implemented to minimize \nthe differential voltage at the digitizer. A type-A uncertainty of 45 nV/V after 10 min was measured for a commercial \nac source at 1 V rms amplitude and 1 kHz.\n\n[1] \"Differential Measurements of an AC Source with a Josephson Arbitrary Waveform Synthesizer\"submitted to Conference on Precision Electromagnetic Measurements (CPEM) 2024; will be published and available on IEEE website at a later date.\n\nData for figures 2 to 4 of the manuscript.\nFiles included in this publication:\n\n   Fig 2 FFT of the digitizer signal.csv\n\n    Figure 2\n    Fig. 2. 1 kHz component of the FFT of the digitizer signal (amplitude and phase) for Delta_V1=Source-JAWS1 and Delta_V2=Source-JAWS2 over 3.5 hours\n    Five columns: The first column is the time (x-axis), the second column is the amplitude in volt of the first measured difference voltage (shown as black solid circle in Fig. 2), \n    the third column is the phase in degree of the first measured difference voltage (shown as black open circle in Fig. 2),\n    the fourth column is the amplitude in volt of the second measured difference voltage (shown as red solid circle in Fig. 2),\n    the fifth column is the phase in degree of the second measured difference voltage (shown as red open circle in Fig. 2).\n    Format: CSV\n\n  Fig 3 Source rms amplitude and environment data.csv\n\n    Figure 3\n    Fig. 3. Room environment conditions recorded (temperature, atmospheric pressure, and relative humidity) and Reconstructed rms amplitude for the source at 1 kHz.\n    Five columns: The first column is the time (x-axis), the second column is the reconstructed amplitude in volt - 1 V (shown as blue solid circle in Fig. 3 bottom), \n    the third column is the temperature in degree C (shown as orange solid square in Fig. 3 top),\n    the fourth column is the atomsepheric pressure in hecto Pascal  (shown as green open triangle in Fig. 3 top),\n    the fifth column is the relative humidity in percent (shown as puple open circle in Fig. 2).\n    Format: CSV\n\n  Fig 4 Allan variance.csv\n\n    Figure 4\n    Fig. 4. Allan deviation of the source amplitude measured at 1 V and 1 kHz.\n    Five columns: The first column is the time (x-axis), the second column is the calculated Allan Deviation in volt (shown as blue solid circle in Fig. 4), \n    the third column is the fit on the results, representing the white noise with slope -0.5 (shown as black dash line in Fig. 4),\n    the fourth column is the is the time (x-axis) for the 1/f noise floor plot and the fifth column is the 1/f noise floor (shown as a black solid line in Fig. 4)\n    Format: CSV","distribution":[{"downloadURL":"https://data.nist.gov/od/ds/mds2-3162/3162_README.txt","mediaType":"text/plain","title":"3162_README"},{"downloadURL":"https://data.nist.gov/od/ds/mds2-3162/Fig%202%20FFT%20of%20the%20digitizer%20signal.csv","mediaType":"text/csv","title":"Fig 2 FFT of the digitizer signal"},{"downloadURL":"https://data.nist.gov/od/ds/mds2-3162/Fig%203%20Source%20rms%20amplitude%20and%20environment%20data.csv","mediaType":"text/csv","title":"Fig 3 Source rms amplitude and environment data"},{"downloadURL":"https://data.nist.gov/od/ds/mds2-3162/Fig%204%20Allan%20variance.csv","mediaType":"text/csv","title":"Fig 4 Allan variance"}],"identifier":"ark:/88434/mds2-3162","issued":"2024-02-13","keyword":["Josephson arrays","Measurement techniques","Standards","Superconducting integrated circuits","Voltage measurement"],"landingPage":"https://data.nist.gov/od/id/mds2-3162","language":["en"],"license":"https://www.nist.gov/open/license","modified":"2024-01-05 00:00:00","programCode":["006:045"],"publisher":{"@type":"org:Organization","name":"National Institute of Standards and Technology"},"theme":["Metrology:Electrical/electromagnetic metrology"],"title":"Differential Measurements of an AC Source with a Josephson Arbitrary Waveform Synthesizer"},"description":"The abstract of the paper [1] is:\n\nThis paper describes differential sampling measurements of an ac source and a Josephson arbitrary waveform synthesizer (JAWS).\nA new iterative approach for aligning the phases of the JAWS and the source waveforms was implemented to minimize \nthe differential voltage at the digitizer. A type-A uncertainty of 45 nV/V after 10 min was measured for a commercial \nac source at 1 V rms amplitude and 1 kHz.\n\n[1] \"Differential Measurements of an AC Source with a Josephson Arbitrary Waveform Synthesizer\"submitted to Conference on Precision Electromagnetic Measurements (CPEM) 2024; will be published and available on IEEE website at a later date.\n\nData for figures 2 to 4 of the manuscript.\nFiles included in this publication:\n\n   Fig 2 FFT of the digitizer signal.csv\n\n    Figure 2\n    Fig. 2. 1 kHz component of the FFT of the digitizer signal (amplitude and phase) for Delta_V1=Source-JAWS1 and Delta_V2=Source-JAWS2 over 3.5 hours\n    Five columns: The first column is the time (x-axis), the second column is the amplitude in volt of the first measured difference voltage (shown as black solid circle in Fig. 2), \n    the third column is the phase in degree of the first measured difference voltage (shown as black open circle in Fig. 2),\n    the fourth column is the amplitude in volt of the second measured difference voltage (shown as red solid circle in Fig. 2),\n    the fifth column is the phase in degree of the second measured difference voltage (shown as red open circle in Fig. 2).\n    Format: CSV\n\n  Fig 3 Source rms amplitude and environment data.csv\n\n    Figure 3\n    Fig. 3. Room environment conditions recorded (temperature, atmospheric pressure, and relative humidity) and Reconstructed rms amplitude for the source at 1 kHz.\n    Five columns: The first column is the time (x-axis), the second column is the reconstructed amplitude in volt - 1 V (shown as blue solid circle in Fig. 3 bottom), \n    the third column is the temperature in degree C (shown as orange solid square in Fig. 3 top),\n    the fourth column is the atomsepheric pressure in hecto Pascal  (shown as green open triangle in Fig. 3 top),\n    the fifth column is the relative humidity in percent (shown as puple open circle in Fig. 2).\n    Format: CSV\n\n  Fig 4 Allan variance.csv\n\n    Figure 4\n    Fig. 4. Allan deviation of the source amplitude measured at 1 V and 1 kHz.\n    Five columns: The first column is the time (x-axis), the second column is the calculated Allan Deviation in volt (shown as blue solid circle in Fig. 4), \n    the third column is the fit on the results, representing the white noise with slope -0.5 (shown as black dash line in Fig. 4),\n    the fourth column is the is the time (x-axis) for the 1/f noise floor plot and the fifth column is the 1/f noise floor (shown as a black solid line in Fig. 4)\n    Format: CSV","distribution_titles":["3162_README","Fig 2 FFT of the digitizer signal","Fig 3 Source rms amplitude and environment data","Fig 4 Allan variance"],"harvest_record":"https://catalog.data.gov/harvest_record/a388c5d5-7c17-4570-b60d-fa62500da89c","harvest_record_raw":"https://catalog.data.gov/harvest_record/a388c5d5-7c17-4570-b60d-fa62500da89c/raw","has_download":true,"has_spatial":false,"identifier":"ark:/88434/mds2-3162","keyword":["Josephson arrays","Measurement techniques","Standards","Superconducting integrated circuits","Voltage measurement"],"last_harvested_date":"2026-09-02T19:18:51.389318","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"176f2a2d-ca9b-41f2-8df3-d93096ebdb85","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nist.png","name":"National Institute of Standards and Technology","organization_type":"Federal Government","slug":"nist"},"parent_identifier":null,"popularity":2,"publisher":"National Institute of Standards and Technology","slug":"differential-measurements-of-an-ac-source-with-a-josephson-arbitrary-waveform-synthesizer","spatial_centroid":null,"spatial_shape":null,"theme":["Metrology:Electrical/electromagnetic metrology"],"title":"Differential Measurements of an AC Source with a Josephson Arbitrary Waveform Synthesizer","type":"dataset"},{"_score":18.585903,"_sort":[1788376724578,18.585903,1,"31e2c124-8e55-40e2-9979-6855ffe68e28"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["006:55"],"contactPoint":{"fn":"Michael Paul Majurski","hasEmail":"mailto:michael.majurski@nist.gov"},"description":"Round rl-randomized-lavaworld-aug2023-train Train Dataset\n\nThis is the training data used to create and evaluate trojan detection software solutions. 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This data, generated at NIST, consists of Reinforcement Learning agents trained to navigate the Lavaworld Minigrid environment. A known percentage of these trained AI models have been poisoned with a known trigger which induces incorrect behavior. 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The role of dual phosphorylation was explored by comparing 0P-ERK2 with 2P-ERK2 (two phosphate groups added at T183 and Y185). Both 0P-ERK2 and 2P-ERK2 models were treated with the ff19SB forcefield immersed in a solution of 0.15 M NaCl in OPC water. The results showed that the A-loop can adopt multiple long-lived (>5 microseconds) conformational states. A set of primary and secondary seeds were used to explore these novel states of the activation loop. Analysis scripts, dataframes, and all trajectories (stripped of explicit water and NaCl ions) are provided here to enhance the reproducibility of this complex study and aid future studies.\n \nTrajectories\n \nAs described in the associated publication, individual trajectories were run for (5-25) microseconds and totaled 727 microseconds. Multiple primary seeds (285 K, 300 K, 315 K, and 330 K) and secondary trajectory seeds (300 K) were run; all are available in this data publication. All frames for each trajectory were aligned to backbone atoms of residues 10-161 and 182-343 of the minimized 2ERK X-ray structures (0P and 2P). Modeled residue numbers are 1-353 and correspond to residues 6-358 of 2ERK and 5UMO (rat sequence numbering). The model built from 2Y9Q, which is a human kinase, was converted to correspond to the rat-derived models (2ERK, 5UMO) as described in the associated publication. Most primary seeds are greater than 10 microseconds while most secondary seeds are 5.7 microseconds. Angstrom units (0.1 nm) are used for trajectory coordinate storage and analysis. Three sets of trajectories are provided for convenience:\n \n1. The canonical set of trajectories are netcdf files (extension .nc) that are stripped of NaCl and water molecules and down-sampled to 2.5 ns between frames.\n \n2. The set of trajectory seeds with hydrogens removed and further down-sampling to 250 ns between frames is provided as DCD trajectory files. This is the smallest download that will be most convenient for visualization and initial development.\n \n3. Frames from the 300 K trajectories collated by the A-loop states. These trajectories should be treated as collections of frames without regard for any time information stored.\n \nStructures from RCSB.org\n \nThe associated publication analyzed the crystal packing environment of the activation loop. The structural data were collected in November 2021. All pdb files downloaded at that time are included in this data publication to aid the reproducibility of the analysis. The RCSB (Research Collaboratory for Structural Bioinformatics, https://www.rcsb.org) was the source of information and should be used directly for current versions of the associated entries. The RCSB entries pdbid 2ERK, pdbid 5UMO, and pdbid 2Y9Q were the structures used to build initial models for MD simulations.\n \nScripts\n \nRepresentative scripts are provided to aid future work. 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Similar products by other developers may be found to work as well or 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All frames for each trajectory were aligned to backbone atoms of residues 10-161 and 182-343 of the minimized 2ERK X-ray structures (0P and 2P). Modeled residue numbers are 1-353 and correspond to residues 6-358 of 2ERK and 5UMO (rat sequence numbering). The model built from 2Y9Q, which is a human kinase, was converted to correspond to the rat-derived models (2ERK, 5UMO) as described in the associated publication. Most primary seeds are greater than 10 microseconds while most secondary seeds are 5.7 microseconds. Angstrom units (0.1 nm) are used for trajectory coordinate storage and analysis. Three sets of trajectories are provided for convenience:\n \n1. The canonical set of trajectories are netcdf files (extension .nc) that are stripped of NaCl and water molecules and down-sampled to 2.5 ns between frames.\n \n2. The set of trajectory seeds with hydrogens removed and further down-sampling to 250 ns between frames is provided as DCD trajectory files. This is the smallest download that will be most convenient for visualization and initial development.\n \n3. Frames from the 300 K trajectories collated by the A-loop states. These trajectories should be treated as collections of frames without regard for any time information stored.\n \nStructures from RCSB.org\n \nThe associated publication analyzed the crystal packing environment of the activation loop. The structural data were collected in November 2021. All pdb files downloaded at that time are included in this data publication to aid the reproducibility of the analysis. The RCSB (Research Collaboratory for Structural Bioinformatics, https://www.rcsb.org) was the source of information and should be used directly for current versions of the associated entries. The RCSB entries pdbid 2ERK, pdbid 5UMO, and pdbid 2Y9Q were the structures used to build initial models for MD simulations.\n \nScripts\n \nRepresentative scripts are provided to aid future work. See README.md\n \nUnits\n \nQ-Aloop values are fractions. RMSD, distances, and coordinates are all reported in Angstroms (0.1 nm). Angles are reported in degrees.\n \nNOTE: Trade names are provided only to specify the source of information and procedures adequately and do not imply endorsement by the National Institute of Standards and Technology. 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The crystalline-rock aquifer underlies the Milford-Souhegan glacial-drift (MSGD) aquifer\n(a high water-producing aquifer) and the Savage Municipal Water-Supply Well Superfund site. \nResidential water-supply wells are within one-quarter of a mile of the PCE-contaminated \nmonitoring wells and many are likely installed in similar rock types and formations as those of\nthe monitoring wells. The need to understand and quantify flow and transport in the crystalline-\nrock aquifer is crucial in assessing strategies for remediation. The current, area-wide model \nsimulates flow in the crystalline-rock aquifer and covers a much larger area than previous models\nwith the goal of improving the computation of groundwater flow from distal locations to the \nresidential wells and the area. 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In addition, a previously\ndeveloped model (https://doi.org/10.3133/sir20045176 and https://doi.org/10.3133/ofr20121079)\nwas used with MOC3D to evaluate the solute-transport of tetrachloroethylene (PCE). In 2010 \nPCE, a chlorinated volatile organic compound, was detected in groundwater from monitoring \nwells tapping the deep (more than 300 feet below land surface) fractures in a crystalline-rock \naquifer. The crystalline-rock aquifer underlies the Milford-Souhegan glacial-drift (MSGD) aquifer\n(a high water-producing aquifer) and the Savage Municipal Water-Supply Well Superfund site. \nResidential water-supply wells are within one-quarter of a mile of the PCE-contaminated \nmonitoring wells and many are likely installed in similar rock types and formations as those of\nthe monitoring wells. The need to understand and quantify flow and transport in the crystalline-\nrock aquifer is crucial in assessing strategies for remediation. The current, area-wide model \nsimulates flow in the crystalline-rock aquifer and covers a much larger area than previous models\nwith the goal of improving the computation of groundwater flow from distal locations to the \nresidential wells and the area. 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The surface was generated from points collected by \nthe echosounder and real-time kinematic (RTK) GPS on cross-sections in the downstream project reach \nsurrounding the construction area at River Mile 770 below Gavins Point Dam on the Missouri River in \nSouth Dakota before and after construction of the sandbar.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P98YVECX","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.bab471f5-254a-4619-a308-17af1ab39dd0.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_bab471f5-254a-4619-a308-17af1ab39dd0","keyword":["Hydrographic Survey","USGS:bab471f5-254a-4619-a308-17af1ab39dd0","environment","geoscientificInformation","inlandWaters"],"modified":"2026-02-17T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-96.876334, 42.712792, -96.851104, 42.732505","theme":["geospatial"],"title":"Difference betweem postconstruction and preconstruction land surface elevation tins on the Missouri River Downstream from Gavins Point Dam near River Mile 769.8."},"description":"This geospatial data set contains an interpolated 3-D surface or, triangulated-irregular network (TIN), of \nthe change in elevation, in feet, of the substrate between cross-sections 22 and 35 following construction \nof Emergent Sandbar Habitat near River Mile 770.  The surface was generated from points collected by \nthe echosounder and real-time kinematic (RTK) GPS on cross-sections in the downstream project reach \nsurrounding the construction area at River Mile 770 below Gavins Point Dam on the Missouri River in \nSouth Dakota before and after construction of the sandbar.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/d15cfc90-a1ec-4004-8ab7-05a2ef54828f","harvest_record_raw":"https://catalog.data.gov/harvest_record/d15cfc90-a1ec-4004-8ab7-05a2ef54828f/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_bab471f5-254a-4619-a308-17af1ab39dd0","keyword":["Hydrographic Survey","USGS:bab471f5-254a-4619-a308-17af1ab39dd0","environment","geoscientificInformation","inlandWaters"],"last_harvested_date":"2026-09-02T19:03:39.060163","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":5,"publisher":"U.S. Geological Survey","slug":"difference-betweem-postconstruction-and-preconstruction-land-surface-elevation-tins-on-the-4e0f6","spatial_centroid":{"lat":42.7206772,"lon":-96.866242},"spatial_shape":{"coordinates":[[[-96.876334,42.712792],[-96.876334,42.732505],[-96.851104,42.732505],[-96.851104,42.712792],[-96.876334,42.712792]]],"type":"Polygon"},"theme":["geospatial"],"title":"Difference betweem postconstruction and preconstruction land surface elevation tins on the Missouri River Downstream from Gavins Point Dam near River Mile 769.8.","type":"dataset"},{"_score":10.179567,"_sort":[1788375764643,10.179567,1,"da73e18a-7c5e-401a-bdb1-0c3d66eb2ccc"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Ryan F. 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The benefits of the Healthy Nail Salon Program include: \r\n\r\n- Enhanced health and well being of staff \r\n- Safer environment for customers\r\n- Recognition and promotion by San Francisco\u2019s Department of Environment \r\n- Potential to attract new customers \r\n\r\nThe data set is a list of all certified Healthy Nail Salons recognized by San Francisco Department of the Environment.","distribution":[{"@type":"dcat:Distribution","describedBy":"https://data.sf.gov/api/views/vwjj-xa8f/columns.json","describedByType":"application/json","downloadURL":"https://data.sf.gov/api/v3/views/vwjj-xa8f/query.json?accessType=DOWNLOAD","mediaType":"application/json"},{"@type":"dcat:Distribution","describedBy":"https://data.sf.gov/api/views/vwjj-xa8f/columns.xml","describedByType":"application/xml","downloadURL":"https://data.sf.gov/api/v3/views/vwjj-xa8f/query.xml?accessType=DOWNLOAD","mediaType":"application/xml"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/vwjj-xa8f/export.csv?accessType=DOWNLOAD","mediaType":"text/csv"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/vwjj-xa8f/export.kml?accessType=DOWNLOAD","mediaType":"application/vnd.google-earth.kml+xml"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/vwjj-xa8f/export.kmz?accessType=DOWNLOAD","mediaType":"application/vnd.google-earth.kmz"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/vwjj-xa8f/query.geojson?accessType=DOWNLOAD","mediaType":"application/geo+json"}],"identifier":"https://data.sf.gov/api/views/vwjj-xa8f","issued":"2020-10-02","keyword":["untagged"],"landingPage":"https://data.sf.gov/d/vwjj-xa8f","license":"http://opendatacommons.org/licenses/pddl/1.0/","modified":"2024-03-13","publisher":{"@type":"org:Organization","name":"data.sf.gov"},"theme":["Energy and Environment"],"title":"Recognized Healthy Nail Salons in San Francisco"},"description":"The San Francisco Healthy Nail Salon Program is a free and voluntary program open to all nail salons in the City. The goal of the Healthy Nail Salon Program is to reduce exposure of nail salon employees and residents to the toxic chemicals in nail products. The benefits of the Healthy Nail Salon Program include: \r\n\r\n- Enhanced health and well being of staff \r\n- Safer environment for customers\r\n- Recognition and promotion by San Francisco\u2019s Department of Environment \r\n- Potential to attract new customers \r\n\r\nThe data set is a list of all certified Healthy Nail Salons recognized by San Francisco Department of the Environment.","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/832ba527-5cf0-4ccf-b6a8-71f25318ad90","harvest_record_raw":"https://catalog.data.gov/harvest_record/832ba527-5cf0-4ccf-b6a8-71f25318ad90/raw","has_download":true,"has_spatial":false,"identifier":"https://data.sf.gov/api/views/vwjj-xa8f","keyword":["untagged"],"last_harvested_date":"2026-09-02T18:56:40.088219","organization":{"aliases":["sf","california"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"7f3c6c7a-ef5f-4ee0-87ce-a0300ba767d5","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/city_san_francisco_ca.png","name":"City of San Francisco","organization_type":"City Government","slug":"san-francisco-ca"},"parent_identifier":null,"popularity":1,"publisher":"data.sf.gov","slug":"recognized-healthy-nail-salons-in-san-francisco","spatial_centroid":null,"spatial_shape":null,"theme":["Energy and Environment"],"title":"Recognized Healthy Nail Salons in San Francisco","type":"dataset"},{"_score":34.572704,"_sort":[1788375399586,34.572704,0,"52e706f6-a6f2-4e64-862a-28a705db307f"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","contactPoint":{"@type":"vcard:Contact","fn":"mikewynne","hasEmail":"mailto:no-reply@data.sf.gov"},"description":"This is the plant list used by the SF Plant Finder (https://sfplanninggis.org/plantsf/).  \n\nThe San Francisco Plant Finder is a resource for gardeners, designers, ecologists and anyone who is interested in greening neighborhoods, enhancing our urban ecology and surviving the drought. The Plant Finder recommends appropriate habitat-building plants for sidewalks, gardens and roofs that are adapted to San Francisco's unique environment and climate.\n\nThe plants in the database include California natives and Mediterranean climate exotics. A large subset of the California natives are actually local San Francisco natives. We strongly recommend local natives since they provide the best habitat for local pollinators and other wildlife with whom they have co-evolved. San Francisco natives are the most closely adapted to the climate and environment of the San Francisco peninsula of course, and so they are the best in terms of water and soil conservation, ecosystem health, and overall sustainability.\n\nThe geographic boundaries for plant communities used in SF Plant Finder are here: https://data.sfgov.org/d/27u4-a5b3","distribution":[{"@type":"dcat:Distribution","describedBy":"https://data.sf.gov/api/views/vmnk-skih/columns.json","describedByType":"application/json","downloadURL":"https://data.sf.gov/api/v3/views/vmnk-skih/query.json?accessType=DOWNLOAD","mediaType":"application/json"},{"@type":"dcat:Distribution","describedBy":"https://data.sf.gov/api/views/vmnk-skih/columns.xml","describedByType":"application/xml","downloadURL":"https://data.sf.gov/api/v3/views/vmnk-skih/query.xml?accessType=DOWNLOAD","mediaType":"application/xml"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/vmnk-skih/export.csv?accessType=DOWNLOAD","mediaType":"text/csv"}],"identifier":"https://data.sf.gov/api/views/vmnk-skih","issued":"2025-07-10","keyword":["environment","green connections","planning","plant","plantfinder","plants","sf plant finder"],"landingPage":"https://data.sf.gov/d/vmnk-skih","license":"http://opendatacommons.org/licenses/pddl/1.0/","modified":"2025-07-10","publisher":{"@type":"org:Organization","name":"data.sf.gov"},"theme":["Energy and Environment"],"title":"San Francisco Plant Finder Data"},"description":"This is the plant list used by the SF Plant Finder (https://sfplanninggis.org/plantsf/).  \n\nThe San Francisco Plant Finder is a resource for gardeners, designers, ecologists and anyone who is interested in greening neighborhoods, enhancing our urban ecology and surviving the drought. The Plant Finder recommends appropriate habitat-building plants for sidewalks, gardens and roofs that are adapted to San Francisco's unique environment and climate.\n\nThe plants in the database include California natives and Mediterranean climate exotics. A large subset of the California natives are actually local San Francisco natives. We strongly recommend local natives since they provide the best habitat for local pollinators and other wildlife with whom they have co-evolved. San Francisco natives are the most closely adapted to the climate and environment of the San Francisco peninsula of course, and so they are the best in terms of water and soil conservation, ecosystem health, and overall sustainability.\n\nThe geographic boundaries for plant communities used in SF Plant Finder are here: https://data.sfgov.org/d/27u4-a5b3","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/1aa0febb-120d-4928-bf02-f70ef3e232b3","harvest_record_raw":"https://catalog.data.gov/harvest_record/1aa0febb-120d-4928-bf02-f70ef3e232b3/raw","has_download":true,"has_spatial":false,"identifier":"https://data.sf.gov/api/views/vmnk-skih","keyword":["environment","green connections","planning","plant","plantfinder","plants","sf plant finder"],"last_harvested_date":"2026-09-02T18:56:39.586390","organization":{"aliases":["sf","california"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"7f3c6c7a-ef5f-4ee0-87ce-a0300ba767d5","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/city_san_francisco_ca.png","name":"City of San Francisco","organization_type":"City Government","slug":"san-francisco-ca"},"parent_identifier":null,"popularity":0,"publisher":"data.sf.gov","slug":"san-francisco-plant-finder-data","spatial_centroid":null,"spatial_shape":null,"theme":["Energy and Environment"],"title":"San Francisco Plant Finder Data","type":"dataset"},{"_score":34.83094,"_sort":[1788375398889,34.83094,4,"374f22e6-71ff-41c8-ad59-226d7c041e6e"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","contactPoint":{"@type":"vcard:Contact","fn":"OpenData","hasEmail":"mailto:no-reply@data.sf.gov"},"description":"<strong>A. SUMMARY</strong>\nThe Municipal Natural Gas Equipment Inventory serves to catalog natural gas-fueled equipment used in municipally owned buildings. \nThis inventory, implemented by the SF Environment Department, aims to establish an understanding of the scope of work needed to electrify municipal buildings and inform an effective and collaborative planning process.\nThis effort was identified as an action in Section BO-2.4 of the  <u><a href=\"https://www.sfenvironment.org/files/events/2021_climate_action_plan.pdf\">2021 Climate Action Plan</a></u> and is included in the <u><a href=\"https://codelibrary.amlegal.com/codes/san_francisco/latest/sf_environment/0-0-0-577\">Environment Code Chapter 7</a></u> (Municipal Green Building Requirements). \n\n<strong>B. HOW THE DATASET IS CREATED</strong>\nThe list of buildings required to report data for the Municipal Natural Gas Equipment Inventory was compiled by cross-referencing the City\u2019s  <u><a href=\"https://data.sfgov.org/City-Infrastructure/City-Facilities/nc68-ngbr/about_datax\">Facility Systems of Record</a></u> and the  <u><a href=\"https://sfpuc.org/about-us/reports/municipal-buildings-energy-benchmarking\">2020 municipal benchmarking report</a></u> to identify all city-owned buildings with non-zero carbon emissions. Numerous municipal buildings are exempt from these reporting requirements, including facilities of the Port of San Francisco and buildings with a primary purpose of providing collection, storage, treatment, delivery, distribution, and/or transmission of water, wastewater, and/or power utilities. \nEach department received an inventory template, provided by the Environment Department, to submit high level building data and detailed information on each piece of natural gas equipment in use in these buildings. Departments were asked to self-report the required building and equipment data over the course of a 6-month data collection period in 2023 and are asked to keep this inventory up to date in the following years as equipment is replaced. \n\n<strong>C. UPDATE PROCESS</strong>\nThe inventory will be regularly updated by department representatives via the inventory PowerApp. When a gas-powered equipment item is retired or replaced, departments are asked to mark it as no longer in use and provide information on any electric replacement equipment, if applicable. While departments have the flexibility to update the inventory at any time, they are encouraged to do so at 6 month intervals at the minimum. \n\nUpdated inventory data will be automatically reflected in this dataset. \n\n<strong>D. HOW TO USE THIS DATASET</strong>\nIt is important to note that this dataset does not include facilities of the Port of San Francisco and buildings with a primary purpose of providing collection, storage, treatment, delivery, distribution, and/or transmission of water, wastewater, and/or power utilities, in accordance with Environment Code Chapter 7 exemptions.","distribution":[{"@type":"dcat:Distribution","describedBy":"https://data.sf.gov/api/views/vc6r-v7av/columns.json","describedByType":"application/json","downloadURL":"https://data.sf.gov/api/v3/views/vc6r-v7av/query.json?accessType=DOWNLOAD","mediaType":"application/json"},{"@type":"dcat:Distribution","describedBy":"https://data.sf.gov/api/views/vc6r-v7av/columns.xml","describedByType":"application/xml","downloadURL":"https://data.sf.gov/api/v3/views/vc6r-v7av/query.xml?accessType=DOWNLOAD","mediaType":"application/xml"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/vc6r-v7av/export.csv?accessType=DOWNLOAD","mediaType":"text/csv"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/vc6r-v7av/export.kml?accessType=DOWNLOAD","mediaType":"application/vnd.google-earth.kml+xml"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/vc6r-v7av/export.kmz?accessType=DOWNLOAD","mediaType":"application/vnd.google-earth.kmz"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/vc6r-v7av/query.geojson?accessType=DOWNLOAD","mediaType":"application/geo+json"}],"identifier":"https://data.sf.gov/api/views/vc6r-v7av","issued":"2024-03-28","keyword":["environment","environmental health","greenhouse gas emissions","natural gas"],"landingPage":"https://data.sf.gov/d/vc6r-v7av","modified":"2026-08-28","publisher":{"@type":"org:Organization","name":"data.sf.gov"},"theme":["Energy and Environment"],"title":"San Francisco Municipal Natural Gas Equipment Inventory"},"description":"<strong>A. 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HOW THE DATASET IS CREATED</strong>\nThe list of buildings required to report data for the Municipal Natural Gas Equipment Inventory was compiled by cross-referencing the City\u2019s  <u><a href=\"https://data.sfgov.org/City-Infrastructure/City-Facilities/nc68-ngbr/about_datax\">Facility Systems of Record</a></u> and the  <u><a href=\"https://sfpuc.org/about-us/reports/municipal-buildings-energy-benchmarking\">2020 municipal benchmarking report</a></u> to identify all city-owned buildings with non-zero carbon emissions. Numerous municipal buildings are exempt from these reporting requirements, including facilities of the Port of San Francisco and buildings with a primary purpose of providing collection, storage, treatment, delivery, distribution, and/or transmission of water, wastewater, and/or power utilities. \nEach department received an inventory template, provided by the Environment Department, to submit high level building data and detailed information on each piece of natural gas equipment in use in these buildings. Departments were asked to self-report the required building and equipment data over the course of a 6-month data collection period in 2023 and are asked to keep this inventory up to date in the following years as equipment is replaced. \n\n<strong>C. UPDATE PROCESS</strong>\nThe inventory will be regularly updated by department representatives via the inventory PowerApp. When a gas-powered equipment item is retired or replaced, departments are asked to mark it as no longer in use and provide information on any electric replacement equipment, if applicable. While departments have the flexibility to update the inventory at any time, they are encouraged to do so at 6 month intervals at the minimum. \n\nUpdated inventory data will be automatically reflected in this dataset. \n\n<strong>D. HOW TO USE THIS DATASET</strong>\nIt is important to note that this dataset does not include facilities of the Port of San Francisco and buildings with a primary purpose of providing collection, storage, treatment, delivery, distribution, and/or transmission of water, wastewater, and/or power utilities, in accordance with Environment Code Chapter 7 exemptions.","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/6bc8420b-1643-4be1-b0ee-0dd225c00c2f","harvest_record_raw":"https://catalog.data.gov/harvest_record/6bc8420b-1643-4be1-b0ee-0dd225c00c2f/raw","has_download":true,"has_spatial":false,"identifier":"https://data.sf.gov/api/views/vc6r-v7av","keyword":["environment","environmental health","greenhouse gas emissions","natural gas"],"last_harvested_date":"2026-09-02T18:56:38.889822","organization":{"aliases":["sf","california"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"7f3c6c7a-ef5f-4ee0-87ce-a0300ba767d5","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/city_san_francisco_ca.png","name":"City of San Francisco","organization_type":"City Government","slug":"san-francisco-ca"},"parent_identifier":null,"popularity":4,"publisher":"data.sf.gov","slug":"san-francisco-municipal-natural-gas-equipment-inventory","spatial_centroid":null,"spatial_shape":null,"theme":["Energy and Environment"],"title":"San Francisco Municipal Natural Gas Equipment Inventory","type":"dataset"},{"_score":4.666744,"_sort":[1788375398528,4.666744,0,"c3fbbc59-9995-4c16-9025-36785ce5b8e9"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","contactPoint":{"@type":"vcard:Contact","fn":"OpenData","hasEmail":"mailto:no-reply@data.sf.gov"},"description":"Projects that are located on sites with known or suspected soil and/or groundwater contamination are subject to the provisions of Health Code Article 22A, which is administered by the Department of Public Health (DPH). Submittal of the Maher Application to and coordination with DPH may be required. Applicants may contact DPH for assistance.\n\nFor more information, please see:\n<a href=\"http://www.sfdph.org/dph/eh/HazWaste/hazWasteSiteMitigation.asp\" target=\"_blank\">http://www.sfdph.org/dph/eh/HazWaste/hazWasteSiteMitigation.asp</a>","distribution":[{"@type":"dcat:Distribution","describedBy":"https://data.sf.gov/api/views/v5ic-hjgw/columns.json","describedByType":"application/json","downloadURL":"https://data.sf.gov/api/v3/views/v5ic-hjgw/query.json?accessType=DOWNLOAD","mediaType":"application/json"},{"@type":"dcat:Distribution","describedBy":"https://data.sf.gov/api/views/v5ic-hjgw/columns.xml","describedByType":"application/xml","downloadURL":"https://data.sf.gov/api/v3/views/v5ic-hjgw/query.xml?accessType=DOWNLOAD","mediaType":"application/xml"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/v5ic-hjgw/export.csv?accessType=DOWNLOAD","mediaType":"text/csv"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/v5ic-hjgw/export.kml?accessType=DOWNLOAD","mediaType":"application/vnd.google-earth.kml+xml"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/v5ic-hjgw/export.kmz?accessType=DOWNLOAD","mediaType":"application/vnd.google-earth.kmz"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/v5ic-hjgw/query.geojson?accessType=DOWNLOAD","mediaType":"application/geo+json"}],"identifier":"https://data.sf.gov/api/views/v5ic-hjgw","issued":"2025-03-12","keyword":["untagged"],"landingPage":"https://data.sf.gov/d/v5ic-hjgw","license":"http://opendatacommons.org/licenses/pddl/1.0/","modified":"2026-09-02","publisher":{"@type":"org:Organization","name":"data.sf.gov"},"theme":["Energy and Environment"],"title":"Maher"},"description":"Projects that are located on sites with known or suspected soil and/or groundwater contamination are subject to the provisions of Health Code Article 22A, which is administered by the Department of Public Health (DPH). Submittal of the Maher Application to and coordination with DPH may be required. Applicants may contact DPH for assistance.\n\nFor more information, please see:\n<a href=\"http://www.sfdph.org/dph/eh/HazWaste/hazWasteSiteMitigation.asp\" target=\"_blank\">http://www.sfdph.org/dph/eh/HazWaste/hazWasteSiteMitigation.asp</a>","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/6ce8c1e8-c10b-44aa-a5bb-2d568c9ea873","harvest_record_raw":"https://catalog.data.gov/harvest_record/6ce8c1e8-c10b-44aa-a5bb-2d568c9ea873/raw","has_download":true,"has_spatial":false,"identifier":"https://data.sf.gov/api/views/v5ic-hjgw","keyword":["untagged"],"last_harvested_date":"2026-09-02T18:56:38.528089","organization":{"aliases":["sf","california"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"7f3c6c7a-ef5f-4ee0-87ce-a0300ba767d5","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/city_san_francisco_ca.png","name":"City of San Francisco","organization_type":"City Government","slug":"san-francisco-ca"},"parent_identifier":null,"popularity":0,"publisher":"data.sf.gov","slug":"maher","spatial_centroid":null,"spatial_shape":null,"theme":["Energy and Environment"],"title":"Maher","type":"dataset"},{"_score":4.7407475,"_sort":[1788375398182,4.7407475,3,"d022b2b1-1d17-4c36-b522-eee1d1b6260a"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","contactPoint":{"@type":"vcard:Contact","fn":"OpenData","hasEmail":"mailto:no-reply@data.sf.gov"},"description":"Working with the San Francisco Department of Public Health (SFDPH), we jointly administer the beach water quality monitoring program in San Francisco. Both agencies participate in sample collection; the San Francisco Water, Power and Sewer Microbiology Laboratory performs bacteriological analyses.\n\nMore information: \nhttps://sfwater.org/index.aspx?page=87\nhttps://sfwater.org/sapps/beachesandbay.html","distribution":[{"@type":"dcat:Distribution","describedBy":"https://data.sf.gov/api/views/v3fv-x3ux/columns.json","describedByType":"application/json","downloadURL":"https://data.sf.gov/api/v3/views/v3fv-x3ux/query.json?accessType=DOWNLOAD","mediaType":"application/json"},{"@type":"dcat:Distribution","describedBy":"https://data.sf.gov/api/views/v3fv-x3ux/columns.xml","describedByType":"application/xml","downloadURL":"https://data.sf.gov/api/v3/views/v3fv-x3ux/query.xml?accessType=DOWNLOAD","mediaType":"application/xml"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/v3fv-x3ux/export.csv?accessType=DOWNLOAD","mediaType":"text/csv"}],"identifier":"https://data.sf.gov/api/views/v3fv-x3ux","issued":"2024-04-25","keyword":["untagged"],"landingPage":"https://data.sf.gov/d/v3fv-x3ux","license":"http://opendatacommons.org/licenses/pddl/1.0/","modified":"2026-09-02","publisher":{"@type":"org:Organization","name":"data.sf.gov"},"theme":["Energy and Environment"],"title":"Beach Water Quality Monitoring"},"description":"Working with the San Francisco Department of Public Health (SFDPH), we jointly administer the beach water quality monitoring program in San Francisco. Both agencies participate in sample collection; the San Francisco Water, Power and Sewer Microbiology Laboratory performs bacteriological analyses.\n\nMore information: \nhttps://sfwater.org/index.aspx?page=87\nhttps://sfwater.org/sapps/beachesandbay.html","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/1eb71a04-fb53-4f11-8e8d-3933df65bd02","harvest_record_raw":"https://catalog.data.gov/harvest_record/1eb71a04-fb53-4f11-8e8d-3933df65bd02/raw","has_download":true,"has_spatial":false,"identifier":"https://data.sf.gov/api/views/v3fv-x3ux","keyword":["untagged"],"last_harvested_date":"2026-09-02T18:56:38.182973","organization":{"aliases":["sf","california"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"7f3c6c7a-ef5f-4ee0-87ce-a0300ba767d5","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/city_san_francisco_ca.png","name":"City of San Francisco","organization_type":"City Government","slug":"san-francisco-ca"},"parent_identifier":null,"popularity":3,"publisher":"data.sf.gov","slug":"beach-water-quality-monitoring","spatial_centroid":null,"spatial_shape":null,"theme":["Energy and Environment"],"title":"Beach Water Quality Monitoring","type":"dataset"},{"_score":8.005266,"_sort":[1788375392347,8.005266,5,"64bcfbd6-6d7a-46f7-a6dc-144564a8da25"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","contactPoint":{"@type":"vcard:Contact","fn":"mikewynne","hasEmail":"mailto:no-reply@data.sf.gov"},"description":"<b>SUMMARY</b>\nThe Air Pollutant Exposure Zone (APEZ) map identifies areas in San Francisco where air modeling indicates higher levels of air pollution. This map is required to be updated every 5 years, as established in <a href=\"https://codelibrary.amlegal.com/codes/san_francisco/latest/sf_health/0-0-0-6054\" target=\"_blank\">San Francisco Health Code article 38</a>. The 2025 Air Pollutant Exposure Zone map is an update to the 2020 map. Additional information may be found at <a href=\"https://sfplanning.org/air-quality\" target=\"_blank\">Air Quality Review | SF Planning.</a>\n\nThe map can be viewed on the <a href=\"https://sfplanninggis.org/pim/map/?layers=Air+Pollutant+Exposure+Zone\" target=\"_blank\">San Francisco Property Information Map</a>.\n\n<b>HOW THE DATASET IS CREATED</b>\nThe 2025 APEZ update modeled areas of the city where: particulate matter (PM2.5) is greater than or equal to 9 \u00b5g/m3 or where the risk of cancer from air pollutants is greater than or equal to 100 in a million; in health vulnerable ZIP codes (94102, 94103, 94110, 94124, and 94134), where the risk of cancer from air pollutants is greater than or equal to 90 in a million; locations within 500 feet of freeways; or locations within 1,000 feet of roadways with a daily average of 100,000 vehicles. To learn more, visit <a href=\"https://citypln-m-extnl.sfgov.org/external/link.ashx?Action=Download&ObjectVersion=-1&vault={A4A7DACD-B0DC-4322-BD29-F6F07103C6E0}&objectGUID={7095FD25-19FC-4EC5-BE89-27CA111949A8}&fileGUID={03888D2B-28F3-40FC-971B-B9D158D5F873}\" target=\"_blank\">San Francisco Citywide Health Risk Assessment: Technical Support Documentation, Air Pollutant Exposure Zone Handout</a> and <a href=\"https://storymaps.arcgis.com/stories/3df9534ee9ac4652805bc0b6b73fb1ec\" target=\"_blank\">Air Pollutant Exposure Zone Story Map.</a>\n\n<b>UPDATE PROCESS</b>\nUpdated every five years.\n\n<b>HOW TO USE THIS DATASET</b>\nThe City uses this dataset as follows. <a href=\"https://codelibrary.amlegal.com/codes/san_francisco/latest/sf_health/0-0-0-6054\" target=\"_blank\">San Francisco Health Code article 38</a> requires new developments or major renovations within the APEZ with sensitive receptors, like housing or preschools, to include a ventilation system that sufficiently removes fine particulate matter (minimum efficiency reporting volume [MERV] 13 or equivalent filtration). In addition, <a href=\"https://codelibrary.amlegal.com/codes/san_francisco/latest/sf_environment/0-0-0-46889\" target=\"_blank\">Environment Code Chapter 25</a> requires public agencies implementing projects within the APEZ to use the cleanest construction equipment available. The City\u2019s environmental review under the California Environmental Quality Act (CEQA) uses the APEZ in its analysis to mandate the use of clean construction equipment, when applicable. To learn more, visit <a href=\"https://sfplanning.org/air-quality\" target=\"_blank\">Air Quality Review | SF Planning.</a>","distribution":[{"@type":"dcat:Distribution","describedBy":"https://data.sf.gov/api/views/t65d-x6p8/columns.json","describedByType":"application/json","downloadURL":"https://data.sf.gov/api/v3/views/t65d-x6p8/query.json?accessType=DOWNLOAD","mediaType":"application/json"},{"@type":"dcat:Distribution","describedBy":"https://data.sf.gov/api/views/t65d-x6p8/columns.xml","describedByType":"application/xml","downloadURL":"https://data.sf.gov/api/v3/views/t65d-x6p8/query.xml?accessType=DOWNLOAD","mediaType":"application/xml"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/t65d-x6p8/export.csv?accessType=DOWNLOAD","mediaType":"text/csv"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/t65d-x6p8/export.kml?accessType=DOWNLOAD","mediaType":"application/vnd.google-earth.kml+xml"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/t65d-x6p8/export.kmz?accessType=DOWNLOAD","mediaType":"application/vnd.google-earth.kmz"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/t65d-x6p8/query.geojson?accessType=DOWNLOAD","mediaType":"application/geo+json"}],"identifier":"https://data.sf.gov/api/views/t65d-x6p8","issued":"2025-03-11","keyword":["untagged"],"landingPage":"https://data.sf.gov/d/t65d-x6p8","license":"https://www.usa.gov/government-works","modified":"2025-08-26","publisher":{"@type":"org:Organization","name":"data.sf.gov"},"theme":["Geographic Locations and Boundaries"],"title":"Air Pollutant Exposure Zone"},"description":"<b>SUMMARY</b>\nThe Air Pollutant Exposure Zone (APEZ) map identifies areas in San Francisco where air modeling indicates higher levels of air pollution. This map is required to be updated every 5 years, as established in <a href=\"https://codelibrary.amlegal.com/codes/san_francisco/latest/sf_health/0-0-0-6054\" target=\"_blank\">San Francisco Health Code article 38</a>. The 2025 Air Pollutant Exposure Zone map is an update to the 2020 map. Additional information may be found at <a href=\"https://sfplanning.org/air-quality\" target=\"_blank\">Air Quality Review | SF Planning.</a>\n\nThe map can be viewed on the <a href=\"https://sfplanninggis.org/pim/map/?layers=Air+Pollutant+Exposure+Zone\" target=\"_blank\">San Francisco Property Information Map</a>.\n\n<b>HOW THE DATASET IS CREATED</b>\nThe 2025 APEZ update modeled areas of the city where: particulate matter (PM2.5) is greater than or equal to 9 \u00b5g/m3 or where the risk of cancer from air pollutants is greater than or equal to 100 in a million; in health vulnerable ZIP codes (94102, 94103, 94110, 94124, and 94134), where the risk of cancer from air pollutants is greater than or equal to 90 in a million; locations within 500 feet of freeways; or locations within 1,000 feet of roadways with a daily average of 100,000 vehicles. To learn more, visit <a href=\"https://citypln-m-extnl.sfgov.org/external/link.ashx?Action=Download&ObjectVersion=-1&vault={A4A7DACD-B0DC-4322-BD29-F6F07103C6E0}&objectGUID={7095FD25-19FC-4EC5-BE89-27CA111949A8}&fileGUID={03888D2B-28F3-40FC-971B-B9D158D5F873}\" target=\"_blank\">San Francisco Citywide Health Risk Assessment: Technical Support Documentation, Air Pollutant Exposure Zone Handout</a> and <a href=\"https://storymaps.arcgis.com/stories/3df9534ee9ac4652805bc0b6b73fb1ec\" target=\"_blank\">Air Pollutant Exposure Zone Story Map.</a>\n\n<b>UPDATE PROCESS</b>\nUpdated every five years.\n\n<b>HOW TO USE THIS DATASET</b>\nThe City uses this dataset as follows. <a href=\"https://codelibrary.amlegal.com/codes/san_francisco/latest/sf_health/0-0-0-6054\" target=\"_blank\">San Francisco Health Code article 38</a> requires new developments or major renovations within the APEZ with sensitive receptors, like housing or preschools, to include a ventilation system that sufficiently removes fine particulate matter (minimum efficiency reporting volume [MERV] 13 or equivalent filtration). In addition, <a href=\"https://codelibrary.amlegal.com/codes/san_francisco/latest/sf_environment/0-0-0-46889\" target=\"_blank\">Environment Code Chapter 25</a> requires public agencies implementing projects within the APEZ to use the cleanest construction equipment available. The City\u2019s environmental review under the California Environmental Quality Act (CEQA) uses the APEZ in its analysis to mandate the use of clean construction equipment, when applicable. To learn more, visit <a href=\"https://sfplanning.org/air-quality\" target=\"_blank\">Air Quality Review | SF Planning.</a>","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/3528fc77-65df-4cca-8061-1c5a4e1189cf","harvest_record_raw":"https://catalog.data.gov/harvest_record/3528fc77-65df-4cca-8061-1c5a4e1189cf/raw","has_download":true,"has_spatial":false,"identifier":"https://data.sf.gov/api/views/t65d-x6p8","keyword":["untagged"],"last_harvested_date":"2026-09-02T18:56:32.347034","organization":{"aliases":["sf","california"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"7f3c6c7a-ef5f-4ee0-87ce-a0300ba767d5","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/city_san_francisco_ca.png","name":"City of San Francisco","organization_type":"City Government","slug":"san-francisco-ca"},"parent_identifier":null,"popularity":5,"publisher":"data.sf.gov","slug":"air-pollutant-exposure-zone","spatial_centroid":null,"spatial_shape":null,"theme":["Geographic Locations and Boundaries"],"title":"Air Pollutant Exposure Zone","type":"dataset"},{"_score":16.207855,"_sort":[1788375384790,16.207855,1,"42ee8343-dc2b-42aa-b03b-1ffb0b8897d1"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","contactPoint":{"@type":"vcard:Contact","fn":"Alex Morrison","hasEmail":"mailto:no-reply@data.sf.gov"},"description":"<strong>Please see the updated </strong><u><a href=\"https://data.sfgov.org/Energy-and-Environment/Tsunami-Inundation-Hazard-Zone-2021-Update-/7p2k-c3z6/about_data\">2021 Dataset</a></u>. </strong>\n\nThis dataset displays areas of the city vulnerable to damage from likely tsunami scenarios and displays what can be considered hazard zones of inundation. This data was created by SFDEM in 2015 based on data provided by the following agencies, and informs evacuation procedures: California Geological Survey and California Governor\u2019s Office of Emergency Services. This was used for the 2019 HCR update process. However, this does not reflect the 2021 California Geological Survey, the California Governor's Office of Emergency Services, and AECOM update to the Tsunami Hazard zone. That can be found here:","distribution":[{"@type":"dcat:Distribution","describedBy":"https://data.sf.gov/api/views/q7uq-hghg/columns.json","describedByType":"application/json","downloadURL":"https://data.sf.gov/api/v3/views/q7uq-hghg/query.json?accessType=DOWNLOAD","mediaType":"application/json"},{"@type":"dcat:Distribution","describedBy":"https://data.sf.gov/api/views/q7uq-hghg/columns.xml","describedByType":"application/xml","downloadURL":"https://data.sf.gov/api/v3/views/q7uq-hghg/query.xml?accessType=DOWNLOAD","mediaType":"application/xml"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/q7uq-hghg/export.csv?accessType=DOWNLOAD","mediaType":"text/csv"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/q7uq-hghg/export.kml?accessType=DOWNLOAD","mediaType":"application/vnd.google-earth.kml+xml"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/q7uq-hghg/export.kmz?accessType=DOWNLOAD","mediaType":"application/vnd.google-earth.kmz"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/q7uq-hghg/query.geojson?accessType=DOWNLOAD","mediaType":"application/geo+json"}],"identifier":"https://data.sf.gov/api/views/q7uq-hghg","issued":"2020-02-25","keyword":["geologic","hcr","tsunami"],"landingPage":"https://data.sf.gov/d/q7uq-hghg","modified":"2025-07-30","publisher":{"@type":"org:Organization","name":"data.sf.gov"},"theme":["Public Safety"],"title":"Tsunami Inundation Hazard Zone (Outdated, 2015)"},"description":"<strong>Please see the updated </strong><u><a href=\"https://data.sfgov.org/Energy-and-Environment/Tsunami-Inundation-Hazard-Zone-2021-Update-/7p2k-c3z6/about_data\">2021 Dataset</a></u>. </strong>\n\nThis dataset displays areas of the city vulnerable to damage from likely tsunami scenarios and displays what can be considered hazard zones of inundation. This data was created by SFDEM in 2015 based on data provided by the following agencies, and informs evacuation procedures: California Geological Survey and California Governor\u2019s Office of Emergency Services. This was used for the 2019 HCR update process. However, this does not reflect the 2021 California Geological Survey, the California Governor's Office of Emergency Services, and AECOM update to the Tsunami Hazard zone. That can be found here:","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/58887100-bdd5-4099-8daa-32c04b2561e7","harvest_record_raw":"https://catalog.data.gov/harvest_record/58887100-bdd5-4099-8daa-32c04b2561e7/raw","has_download":true,"has_spatial":false,"identifier":"https://data.sf.gov/api/views/q7uq-hghg","keyword":["geologic","hcr","tsunami"],"last_harvested_date":"2026-09-02T18:56:24.790617","organization":{"aliases":["sf","california"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"7f3c6c7a-ef5f-4ee0-87ce-a0300ba767d5","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/city_san_francisco_ca.png","name":"City of San Francisco","organization_type":"City Government","slug":"san-francisco-ca"},"parent_identifier":null,"popularity":1,"publisher":"data.sf.gov","slug":"tsunami-inundation-hazard-zone-outdated-2015","spatial_centroid":null,"spatial_shape":null,"theme":["Public Safety"],"title":"Tsunami Inundation Hazard Zone (Outdated, 2015)","type":"dataset"},{"_score":17.021162,"_sort":[1788375384300,17.021162,0,"6b70e363-ea61-4e41-ac1f-36bf2378cf0c"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","contactPoint":{"@type":"vcard:Contact","fn":"OpenData","hasEmail":"mailto:no-reply@data.sf.gov"},"description":"<strong>Note 5/1/2026: This dataset has known errors and we do not recommend using it at this time. Thank you for your patience while we work on correcting the dataset.</strong>\n\n<strong>A. SUMMARY</strong>\nThis database lists records of rodent treatments primarily in the City's combined sewer system. The data is collected and submitted by the current holder of the Citywide Integrated Pest Management contract. Rodent treatments are listed by location and by number of products used. These data will be linked with other public data to provide informational tools in support of the City's Integrated Pest Management (IPM) Program and Vector Control Program, administered by the Department of the Environment and Department of Public Health, respectively. Providing public access to such data is in keeping with the record-keeping and transparency requirements of the IPM Ordinance, Environment Code, Chapt. 3.\n\n<li>For more information on San Francisco's IPM program, see https://www.sfenvironment.org/what-integrated-pest-management-ipm \n<li>For information on the City's Vector Control Program, see https://www.sf.gov/get-help-vermin-your-building\n<li>For more information on data set data custodian, see https://www.civichub.us/ca/sf/open-data\n\n<strong>B. HOW THE DATASET IS CREATED</strong>\nThe data is collected and submitted by the current holder of the Citywide Integrated Pest Management contract. Data is collected by the field technicians and added to a service database from there the data is being published to the SF Open Data portal.\n\n<strong>C. UPDATE PROCESS</strong>\nThis feed is updated daily and reflects service and product application from the previous calendar day.","distribution":[{"@type":"dcat:Distribution","describedBy":"https://data.sf.gov/api/views/pyt2-uhqw/columns.json","describedByType":"application/json","downloadURL":"https://data.sf.gov/api/v3/views/pyt2-uhqw/query.json?accessType=DOWNLOAD","mediaType":"application/json"},{"@type":"dcat:Distribution","describedBy":"https://data.sf.gov/api/views/pyt2-uhqw/columns.xml","describedByType":"application/xml","downloadURL":"https://data.sf.gov/api/v3/views/pyt2-uhqw/query.xml?accessType=DOWNLOAD","mediaType":"application/xml"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/pyt2-uhqw/export.csv?accessType=DOWNLOAD","mediaType":"text/csv"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/pyt2-uhqw/export.kml?accessType=DOWNLOAD","mediaType":"application/vnd.google-earth.kml+xml"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/pyt2-uhqw/export.kmz?accessType=DOWNLOAD","mediaType":"application/vnd.google-earth.kmz"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/pyt2-uhqw/query.geojson?accessType=DOWNLOAD","mediaType":"application/geo+json"}],"identifier":"https://data.sf.gov/api/views/pyt2-uhqw","issued":"2024-04-03","keyword":["untagged"],"landingPage":"https://data.sf.gov/d/pyt2-uhqw","license":"http://opendatacommons.org/licenses/pddl/1.0/","modified":"2026-09-02","publisher":{"@type":"org:Organization","name":"data.sf.gov"},"theme":["City Infrastructure"],"title":"Rodent control by citywide contractor"},"description":"<strong>Note 5/1/2026: This dataset has known errors and we do not recommend using it at this time. Thank you for your patience while we work on correcting the dataset.</strong>\n\n<strong>A. SUMMARY</strong>\nThis database lists records of rodent treatments primarily in the City's combined sewer system. The data is collected and submitted by the current holder of the Citywide Integrated Pest Management contract. Rodent treatments are listed by location and by number of products used. These data will be linked with other public data to provide informational tools in support of the City's Integrated Pest Management (IPM) Program and Vector Control Program, administered by the Department of the Environment and Department of Public Health, respectively. Providing public access to such data is in keeping with the record-keeping and transparency requirements of the IPM Ordinance, Environment Code, Chapt. 3.\n\n<li>For more information on San Francisco's IPM program, see https://www.sfenvironment.org/what-integrated-pest-management-ipm \n<li>For information on the City's Vector Control Program, see https://www.sf.gov/get-help-vermin-your-building\n<li>For more information on data set data custodian, see https://www.civichub.us/ca/sf/open-data\n\n<strong>B. HOW THE DATASET IS CREATED</strong>\nThe data is collected and submitted by the current holder of the Citywide Integrated Pest Management contract. Data is collected by the field technicians and added to a service database from there the data is being published to the SF Open Data portal.\n\n<strong>C. UPDATE PROCESS</strong>\nThis feed is updated daily and reflects service and product application from the previous calendar day.","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/988bc22a-fdbc-4a97-9d1c-7c43da672de6","harvest_record_raw":"https://catalog.data.gov/harvest_record/988bc22a-fdbc-4a97-9d1c-7c43da672de6/raw","has_download":true,"has_spatial":false,"identifier":"https://data.sf.gov/api/views/pyt2-uhqw","keyword":["untagged"],"last_harvested_date":"2026-09-02T18:56:24.300093","organization":{"aliases":["sf","california"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"7f3c6c7a-ef5f-4ee0-87ce-a0300ba767d5","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/city_san_francisco_ca.png","name":"City of San Francisco","organization_type":"City Government","slug":"san-francisco-ca"},"parent_identifier":null,"popularity":0,"publisher":"data.sf.gov","slug":"rodent-control-by-citywide-contractor","spatial_centroid":null,"spatial_shape":null,"theme":["City Infrastructure"],"title":"Rodent control by citywide contractor","type":"dataset"},{"_score":26.470499,"_sort":[1788375384045,26.470499,0,"e263fdc3-2713-4c14-a744-42bfd7933ea5"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","contactPoint":{"@type":"vcard:Contact","fn":"OpenData","hasEmail":"mailto:no-reply@data.sf.gov"},"description":"The purpose of the San Francisco Municipal Greenhouse Gas Inventory is to measure and track departmental greenhouse gas emissions as part of the City's climate action strategy. Per Environment Code Chapter 9, this data is collected and calculated by the Department of the Environment.\n\n\nNote: Data as of 10/20/18. San Francisco municipal greenhouse gas inventory for Fiscal Years 2012 per the California Air Resources Board's Local Government Operations Protocol Version 1.1 (May 2010). Third-party verification of Fiscal Year 2012 which was completed in March 2015 is available at http://sfenvironment.org/download/fiscal-year-2012-municipal-ghg-inventory-memo","distribution":[{"@type":"dcat:Distribution","describedBy":"https://data.sf.gov/api/views/pxac-sadh/columns.json","describedByType":"application/json","downloadURL":"https://data.sf.gov/api/v3/views/pxac-sadh/query.json?accessType=DOWNLOAD","mediaType":"application/json"},{"@type":"dcat:Distribution","describedBy":"https://data.sf.gov/api/views/pxac-sadh/columns.xml","describedByType":"application/xml","downloadURL":"https://data.sf.gov/api/v3/views/pxac-sadh/query.xml?accessType=DOWNLOAD","mediaType":"application/xml"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/pxac-sadh/export.csv?accessType=DOWNLOAD","mediaType":"text/csv"}],"identifier":"https://data.sf.gov/api/views/pxac-sadh","issued":"2016-01-21","keyword":["untagged"],"landingPage":"https://data.sf.gov/d/pxac-sadh","license":"http://opendatacommons.org/licenses/pddl/1.0/","modified":"2024-06-20","publisher":{"@type":"org:Organization","name":"data.sf.gov"},"theme":["Energy and Environment"],"title":"San Francisco Municipal Greenhouse Gas Inventory"},"description":"The purpose of the San Francisco Municipal Greenhouse Gas Inventory is to measure and track departmental greenhouse gas emissions as part of the City's climate action strategy. Per Environment Code Chapter 9, this data is collected and calculated by the Department of the Environment.\n\n\nNote: Data as of 10/20/18. San Francisco municipal greenhouse gas inventory for Fiscal Years 2012 per the California Air Resources Board's Local Government Operations Protocol Version 1.1 (May 2010). Third-party verification of Fiscal Year 2012 which was completed in March 2015 is available at http://sfenvironment.org/download/fiscal-year-2012-municipal-ghg-inventory-memo","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/a9776654-4081-44cb-9f6c-c9ca70b207aa","harvest_record_raw":"https://catalog.data.gov/harvest_record/a9776654-4081-44cb-9f6c-c9ca70b207aa/raw","has_download":true,"has_spatial":false,"identifier":"https://data.sf.gov/api/views/pxac-sadh","keyword":["untagged"],"last_harvested_date":"2026-09-02T18:56:24.045675","organization":{"aliases":["sf","california"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"7f3c6c7a-ef5f-4ee0-87ce-a0300ba767d5","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/city_san_francisco_ca.png","name":"City of San Francisco","organization_type":"City Government","slug":"san-francisco-ca"},"parent_identifier":null,"popularity":0,"publisher":"data.sf.gov","slug":"san-francisco-municipal-greenhouse-gas-inventory","spatial_centroid":null,"spatial_shape":null,"theme":["Energy and Environment"],"title":"San Francisco Municipal Greenhouse Gas Inventory","type":"dataset"},{"_score":4.666744,"_sort":[1788375380108,4.666744,0,"728f25d0-74a8-420f-aae0-5c267fe1aec8"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","contactPoint":{"@type":"vcard:Contact","fn":"Alex Morrison","hasEmail":"mailto:no-reply@data.sf.gov"},"description":"Heat and air quality issues caused by climate change and gas-powered vehicles affect San Francisco communities differently. Tree canopy that would buffer the effects is not equally distributed due to historic racial inequities in infrastructure investment.\n\nTo positively affect public health and leverage new federal funding sources, the City and other stakeholders are planning for green infrastructure investments, such as tree planting, sidewalk landscape zones, cool pavement, structural shading,\ngreen schoolyards, and increased areas of stormwater management. This dataset identifies locations where these strategies could have the highest benefit\nto community health and make the most effective use of City investment.\n\nSF Public Works mapped a combination of environmental and health data to identify the priority zones. The study layers exposure to fine particulate matter (PM2.5), satellite temperature readings from a recent heat wave, and tree canopy data to identify where exposure is the highest. To further refine the prioritization zone, data was added for residents experiencing asthma or diabetes hospitalizations\nwhich are both exacerbated by heat and air quality issues. \n\nThis created two final maps focused on heat and air quality that combine environmental data and human health. These maps were combined to produce the final priority zones.","distribution":[{"@type":"dcat:Distribution","describedBy":"https://data.sf.gov/api/views/nn26-kuy2/columns.json","describedByType":"application/json","downloadURL":"https://data.sf.gov/api/v3/views/nn26-kuy2/query.json?accessType=DOWNLOAD","mediaType":"application/json"},{"@type":"dcat:Distribution","describedBy":"https://data.sf.gov/api/views/nn26-kuy2/columns.xml","describedByType":"application/xml","downloadURL":"https://data.sf.gov/api/v3/views/nn26-kuy2/query.xml?accessType=DOWNLOAD","mediaType":"application/xml"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/nn26-kuy2/export.csv?accessType=DOWNLOAD","mediaType":"text/csv"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/nn26-kuy2/export.kml?accessType=DOWNLOAD","mediaType":"application/vnd.google-earth.kml+xml"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/nn26-kuy2/export.kmz?accessType=DOWNLOAD","mediaType":"application/vnd.google-earth.kmz"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/nn26-kuy2/query.geojson?accessType=DOWNLOAD","mediaType":"application/geo+json"}],"identifier":"https://data.sf.gov/api/views/nn26-kuy2","issued":"2024-06-20","keyword":["untagged"],"landingPage":"https://data.sf.gov/d/nn26-kuy2","modified":"2024-06-21","publisher":{"@type":"org:Organization","name":"data.sf.gov"},"theme":["Energy and Environment"],"title":"HAQR Priority Green Infrastructure Zones"},"description":"Heat and air quality issues caused by climate change and gas-powered vehicles affect San Francisco communities differently. Tree canopy that would buffer the effects is not equally distributed due to historic racial inequities in infrastructure investment.\n\nTo positively affect public health and leverage new federal funding sources, the City and other stakeholders are planning for green infrastructure investments, such as tree planting, sidewalk landscape zones, cool pavement, structural shading,\ngreen schoolyards, and increased areas of stormwater management. This dataset identifies locations where these strategies could have the highest benefit\nto community health and make the most effective use of City investment.\n\nSF Public Works mapped a combination of environmental and health data to identify the priority zones. The study layers exposure to fine particulate matter (PM2.5), satellite temperature readings from a recent heat wave, and tree canopy data to identify where exposure is the highest. To further refine the prioritization zone, data was added for residents experiencing asthma or diabetes hospitalizations\nwhich are both exacerbated by heat and air quality issues. \n\nThis created two final maps focused on heat and air quality that combine environmental data and human health. These maps were combined to produce the final priority zones.","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/6d254ee6-5c2a-4d45-aab6-d337b3ccbd8a","harvest_record_raw":"https://catalog.data.gov/harvest_record/6d254ee6-5c2a-4d45-aab6-d337b3ccbd8a/raw","has_download":true,"has_spatial":false,"identifier":"https://data.sf.gov/api/views/nn26-kuy2","keyword":["untagged"],"last_harvested_date":"2026-09-02T18:56:20.108177","organization":{"aliases":["sf","california"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"7f3c6c7a-ef5f-4ee0-87ce-a0300ba767d5","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/city_san_francisco_ca.png","name":"City of San Francisco","organization_type":"City Government","slug":"san-francisco-ca"},"parent_identifier":null,"popularity":0,"publisher":"data.sf.gov","slug":"haqr-priority-green-infrastructure-zones","spatial_centroid":null,"spatial_shape":null,"theme":["Energy and Environment"],"title":"HAQR Priority Green Infrastructure Zones","type":"dataset"},{"_score":4.666744,"_sort":[1788375379558,4.666744,5,"af6981a5-53ac-43cf-bc35-1c095b07aefb"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","contactPoint":{"@type":"vcard:Contact","fn":"OpenData","hasEmail":"mailto:no-reply@data.sf.gov"},"description":"In preparation for the San Francisco Urban Forest Plan (2013), the Planning Department performed an Urban Tree Canopy (UTC) Analysis using aerial imagery and additional data sets to determine a canopy estimate for the City & County of San Francisco. This analysis estimated San Francisco's tree canopy at 13.7%. This number supersedes a 2007 canopy estimate of 11.9% (USDA Forest Service, 2007). Given the differing methodologies used to arrive at these two numbers it is difficult to draw conclusions regarding urban forest growth or decline based on a comparison. The current analysis establishes a baseline and methodology from which future canopy analyses can be conducted and compared over subsequent years to track San Francisco's urban forest growth or decline over time. See the attachment under About for more on the methodology.","distribution":[{"@type":"dcat:Distribution","describedBy":"https://data.sf.gov/api/views/ni2e-vpbg/columns.json","describedByType":"application/json","downloadURL":"https://data.sf.gov/api/v3/views/ni2e-vpbg/query.json?accessType=DOWNLOAD","mediaType":"application/json"},{"@type":"dcat:Distribution","describedBy":"https://data.sf.gov/api/views/ni2e-vpbg/columns.xml","describedByType":"application/xml","downloadURL":"https://data.sf.gov/api/v3/views/ni2e-vpbg/query.xml?accessType=DOWNLOAD","mediaType":"application/xml"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/ni2e-vpbg/export.csv?accessType=DOWNLOAD","mediaType":"text/csv"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/ni2e-vpbg/export.kml?accessType=DOWNLOAD","mediaType":"application/vnd.google-earth.kml+xml"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/ni2e-vpbg/export.kmz?accessType=DOWNLOAD","mediaType":"application/vnd.google-earth.kmz"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/ni2e-vpbg/query.geojson?accessType=DOWNLOAD","mediaType":"application/geo+json"}],"identifier":"https://data.sf.gov/api/views/ni2e-vpbg","issued":"2016-07-12","keyword":["canopy"],"landingPage":"https://data.sf.gov/d/ni2e-vpbg","license":"http://opendatacommons.org/licenses/pddl/1.0/","modified":"2024-03-13","publisher":{"@type":"org:Organization","name":"data.sf.gov"},"theme":["Energy and Environment"],"title":"Urban Tree Canopy"},"description":"In preparation for the San Francisco Urban Forest Plan (2013), the Planning Department performed an Urban Tree Canopy (UTC) Analysis using aerial imagery and additional data sets to determine a canopy estimate for the City & County of San Francisco. This analysis estimated San Francisco's tree canopy at 13.7%. This number supersedes a 2007 canopy estimate of 11.9% (USDA Forest Service, 2007). Given the differing methodologies used to arrive at these two numbers it is difficult to draw conclusions regarding urban forest growth or decline based on a comparison. The current analysis establishes a baseline and methodology from which future canopy analyses can be conducted and compared over subsequent years to track San Francisco's urban forest growth or decline over time. See the attachment under About for more on the methodology.","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/3653cbdb-9b81-4d82-b048-c4443f6f5955","harvest_record_raw":"https://catalog.data.gov/harvest_record/3653cbdb-9b81-4d82-b048-c4443f6f5955/raw","has_download":true,"has_spatial":false,"identifier":"https://data.sf.gov/api/views/ni2e-vpbg","keyword":["canopy"],"last_harvested_date":"2026-09-02T18:56:19.558511","organization":{"aliases":["sf","california"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"7f3c6c7a-ef5f-4ee0-87ce-a0300ba767d5","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/city_san_francisco_ca.png","name":"City of San Francisco","organization_type":"City Government","slug":"san-francisco-ca"},"parent_identifier":null,"popularity":5,"publisher":"data.sf.gov","slug":"urban-tree-canopy","spatial_centroid":null,"spatial_shape":null,"theme":["Energy and Environment"],"title":"Urban Tree Canopy","type":"dataset"},{"_score":26.47227,"_sort":[1788375372830,26.47227,0,"857be423-36b5-410e-9739-045558e27105"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","contactPoint":{"@type":"vcard:Contact","fn":"SFEBO Help Desk","hasEmail":"mailto:no-reply@data.sf.gov"},"description":"<strong>As of March 20, 2026, this dataset will no longer update. To access new and historical data going forward, navigate to the <u><a href=\"https://data.sfgov.org/d/bfhx-j6n5/\">dataset here</a></u>.</strong>\n\n<strong>A. SUMMARY</strong>\nSan Francisco\u2019s Existing Buildings Energy Performance Ordinance requires owners of non-residential buildings over 10,000 square feet to annually benchmark and disclose energy performance. On behalf of City agencies, the San Francisco Public Utilities Commission (SFPUC) benchmarks and reports energy use for a portfolio of approximately 500 public facilities buildings. The performance of public facilities can be examined in an interactive report at bit.ly/SFMunicipalBenchmarking, and annual reports from 2011-present are available there as well.\n \nThis dataset presents the energy performance and basic characteristics for public facilities that is visualized by the SFPUC\u2019s interactive report.  \n \nIn addition, energy performance data for non-municipal buildings (i.e. commercial buildings of 10,000 square feet or larger, and multifamily & mixed-use buildings of 50,000 square feet or larger) is available at: bit.ly/ExistingBuildingsReport\n\n<strong>B. HOW THE DATASET IS CREATED</strong>\nIn compliance with California Energy Benchmarking Regulations (CA Public Resources Code Section 25402.10 and CCR Title 20 Section 1680), and San Francisco Existing Buildings Energy Ordinance (Environment Code Chapter 20), the San Francisco Public Utilities Commission provides energy benchmarking services on behalf of municipal facilities. Details for public facilities are compiled from city records, and energy usage is compiled from utility records; related metrics such as energy use intensity are calculated from the combination of such records. Data is subjected to quality assurance validation prior to publication. For additional information regarding data sources and assumptions, please review the \"Data Sources and Assumptions\" page of the Municipal Facilities Energy Benchmarking dashboard: https://bit.ly/SFMunicipalBenchmarking.\n\n<strong>C. UPDATE PROCESS</strong>\nUpdated Annually.","distribution":[{"@type":"dcat:Distribution","describedBy":"https://data.sf.gov/api/views/k3fc-45qw/columns.json","describedByType":"application/json","downloadURL":"https://data.sf.gov/api/v3/views/k3fc-45qw/query.json?accessType=DOWNLOAD","mediaType":"application/json"},{"@type":"dcat:Distribution","describedBy":"https://data.sf.gov/api/views/k3fc-45qw/columns.xml","describedByType":"application/xml","downloadURL":"https://data.sf.gov/api/v3/views/k3fc-45qw/query.xml?accessType=DOWNLOAD","mediaType":"application/xml"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/k3fc-45qw/export.csv?accessType=DOWNLOAD","mediaType":"text/csv"}],"identifier":"https://data.sf.gov/api/views/k3fc-45qw","issued":"2024-10-25","keyword":["climate change","energy","environment","sustainability"],"landingPage":"https://data.sf.gov/d/k3fc-45qw","license":"http://opendatacommons.org/licenses/pddl/1.0/","modified":"2026-03-20","publisher":{"@type":"org:Organization","name":"data.sf.gov"},"theme":["Energy and Environment"],"title":"[DEPRECATED] San Francisco Municipal Energy Benchmarking"},"description":"<strong>As of March 20, 2026, this dataset will no longer update. To access new and historical data going forward, navigate to the <u><a href=\"https://data.sfgov.org/d/bfhx-j6n5/\">dataset here</a></u>.</strong>\n\n<strong>A. SUMMARY</strong>\nSan Francisco\u2019s Existing Buildings Energy Performance Ordinance requires owners of non-residential buildings over 10,000 square feet to annually benchmark and disclose energy performance. On behalf of City agencies, the San Francisco Public Utilities Commission (SFPUC) benchmarks and reports energy use for a portfolio of approximately 500 public facilities buildings. The performance of public facilities can be examined in an interactive report at bit.ly/SFMunicipalBenchmarking, and annual reports from 2011-present are available there as well.\n \nThis dataset presents the energy performance and basic characteristics for public facilities that is visualized by the SFPUC\u2019s interactive report.  \n \nIn addition, energy performance data for non-municipal buildings (i.e. commercial buildings of 10,000 square feet or larger, and multifamily & mixed-use buildings of 50,000 square feet or larger) is available at: bit.ly/ExistingBuildingsReport\n\n<strong>B. HOW THE DATASET IS CREATED</strong>\nIn compliance with California Energy Benchmarking Regulations (CA Public Resources Code Section 25402.10 and CCR Title 20 Section 1680), and San Francisco Existing Buildings Energy Ordinance (Environment Code Chapter 20), the San Francisco Public Utilities Commission provides energy benchmarking services on behalf of municipal facilities. Details for public facilities are compiled from city records, and energy usage is compiled from utility records; related metrics such as energy use intensity are calculated from the combination of such records. Data is subjected to quality assurance validation prior to publication. For additional information regarding data sources and assumptions, please review the \"Data Sources and Assumptions\" page of the Municipal Facilities Energy Benchmarking dashboard: https://bit.ly/SFMunicipalBenchmarking.\n\n<strong>C. UPDATE PROCESS</strong>\nUpdated Annually.","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/c0fbdaaf-1042-4dcd-9884-7b8a7c021926","harvest_record_raw":"https://catalog.data.gov/harvest_record/c0fbdaaf-1042-4dcd-9884-7b8a7c021926/raw","has_download":true,"has_spatial":false,"identifier":"https://data.sf.gov/api/views/k3fc-45qw","keyword":["climate change","energy","environment","sustainability"],"last_harvested_date":"2026-09-02T18:56:12.830800","organization":{"aliases":["sf","california"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"7f3c6c7a-ef5f-4ee0-87ce-a0300ba767d5","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/city_san_francisco_ca.png","name":"City of San Francisco","organization_type":"City Government","slug":"san-francisco-ca"},"parent_identifier":null,"popularity":0,"publisher":"data.sf.gov","slug":"deprecated-san-francisco-municipal-energy-benchmarking","spatial_centroid":null,"spatial_shape":null,"theme":["Energy and Environment"],"title":"[DEPRECATED] San Francisco Municipal Energy Benchmarking","type":"dataset"},{"_score":4.666744,"_sort":[1788375372227,4.666744,1,"51a7f365-55bb-46f5-adf7-fdf8dcc4fa92"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","contactPoint":{"@type":"vcard:Contact","fn":"Alex Morrison","hasEmail":"mailto:no-reply@data.sf.gov"},"description":"A) This data describes the Special Flood Hazard Areas (SFHA's) pursuant to the Federal Emergency Management Agency's (FEMA's) Flood Insurance Rate Map (FIRM) for the City and County of San Francisco. \n\nB) These map products were created by FEMA and you can find more information on their creation on the following page: https://www.fema.gov/flood-maps/products-tools/products\n\nC) These maps are updated periodically in light of new information if flooding conditions change for a jurisdiction. This occurs on an as needed basis and is coordinated through the \n\nD) In order to use this dataset it is important to know what each zone designation means. You can find these designations below -- \nZone AE, AO, and VE (AREAS WITH HIGH FLOOD RISK (SPECIAL FLOOD HAZARD AREAS;  REGULATIONS APPLY): Properties within SFHAs are subject to flooding during the 1-percent-chance flood, a flood with a 1 percent chance of occurrence in any given year (also referred to as the Base Flood or 100-year flood).\n\nZone D (AREA OF UNDETERMINED FLOOD RISK): In San Francisco, Zone D is an area of possible, but undefined, flood risk for waterfront piers operated by the Port of San Francisco.\n\nZone X Shaded or Unshaded (AREA OF LOW OR MINIMAL FLOOD RISK): \"Shaded\" Zone X represents areas of moderate or low flood risk \u2013 these areas are subject to inundation during a flood having a 0.2-percent-annual-chance of occurrence, or during the 1-percent-annual-chance flood with depth less than 1 foot. \"Unshaded\" Zone X represents areas of minimal flood risk or areas that FEMA did not study or map.\n\nE) For regulatory implications of map, see: https://onesanfrancisco.org/San-Francisco-Floodplain-Management-Program\n\nFor more detailed information on specific properties impacted by FIRM Map, see: https://sfplanninggis.org/PIM/","distribution":[{"@type":"dcat:Distribution","describedBy":"https://data.sf.gov/api/views/jyce-e25k/columns.json","describedByType":"application/json","downloadURL":"https://data.sf.gov/api/v3/views/jyce-e25k/query.json?accessType=DOWNLOAD","mediaType":"application/json"},{"@type":"dcat:Distribution","describedBy":"https://data.sf.gov/api/views/jyce-e25k/columns.xml","describedByType":"application/xml","downloadURL":"https://data.sf.gov/api/v3/views/jyce-e25k/query.xml?accessType=DOWNLOAD","mediaType":"application/xml"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/jyce-e25k/export.csv?accessType=DOWNLOAD","mediaType":"text/csv"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/jyce-e25k/export.kml?accessType=DOWNLOAD","mediaType":"application/vnd.google-earth.kml+xml"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/jyce-e25k/export.kmz?accessType=DOWNLOAD","mediaType":"application/vnd.google-earth.kmz"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/jyce-e25k/query.geojson?accessType=DOWNLOAD","mediaType":"application/geo+json"}],"identifier":"https://data.sf.gov/api/views/jyce-e25k","issued":"2021-01-12","keyword":["hcr"],"landingPage":"https://data.sf.gov/d/jyce-e25k","modified":"2024-06-26","publisher":{"@type":"org:Organization","name":"data.sf.gov"},"theme":["Energy and Environment"],"title":"FEMA FIRM Flood Hazards (Coastal) - 2021 Update"},"description":"A) This data describes the Special Flood Hazard Areas (SFHA's) pursuant to the Federal Emergency Management Agency's (FEMA's) Flood Insurance Rate Map (FIRM) for the City and County of San Francisco. \n\nB) These map products were created by FEMA and you can find more information on their creation on the following page: https://www.fema.gov/flood-maps/products-tools/products\n\nC) These maps are updated periodically in light of new information if flooding conditions change for a jurisdiction. This occurs on an as needed basis and is coordinated through the \n\nD) In order to use this dataset it is important to know what each zone designation means. You can find these designations below -- \nZone AE, AO, and VE (AREAS WITH HIGH FLOOD RISK (SPECIAL FLOOD HAZARD AREAS;  REGULATIONS APPLY): Properties within SFHAs are subject to flooding during the 1-percent-chance flood, a flood with a 1 percent chance of occurrence in any given year (also referred to as the Base Flood or 100-year flood).\n\nZone D (AREA OF UNDETERMINED FLOOD RISK): In San Francisco, Zone D is an area of possible, but undefined, flood risk for waterfront piers operated by the Port of San Francisco.\n\nZone X Shaded or Unshaded (AREA OF LOW OR MINIMAL FLOOD RISK): \"Shaded\" Zone X represents areas of moderate or low flood risk \u2013 these areas are subject to inundation during a flood having a 0.2-percent-annual-chance of occurrence, or during the 1-percent-annual-chance flood with depth less than 1 foot. \"Unshaded\" Zone X represents areas of minimal flood risk or areas that FEMA did not study or map.\n\nE) For regulatory implications of map, see: https://onesanfrancisco.org/San-Francisco-Floodplain-Management-Program\n\nFor more detailed information on specific properties impacted by FIRM Map, see: https://sfplanninggis.org/PIM/","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/b7b47990-0fd7-4f14-a5e7-17e51b5f3df6","harvest_record_raw":"https://catalog.data.gov/harvest_record/b7b47990-0fd7-4f14-a5e7-17e51b5f3df6/raw","has_download":true,"has_spatial":false,"identifier":"https://data.sf.gov/api/views/jyce-e25k","keyword":["hcr"],"last_harvested_date":"2026-09-02T18:56:12.227688","organization":{"aliases":["sf","california"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"7f3c6c7a-ef5f-4ee0-87ce-a0300ba767d5","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/city_san_francisco_ca.png","name":"City of San Francisco","organization_type":"City Government","slug":"san-francisco-ca"},"parent_identifier":null,"popularity":1,"publisher":"data.sf.gov","slug":"fema-firm-flood-hazards-coastal-2021-update","spatial_centroid":null,"spatial_shape":null,"theme":["Energy and Environment"],"title":"FEMA FIRM Flood Hazards (Coastal) - 2021 Update","type":"dataset"},{"_score":4.875887,"_sort":[1788375361043,4.875887,14,"226cdf4a-2b0b-4a8a-ba80-b39129e9c996"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","contactPoint":{"@type":"vcard:Contact","fn":"OpenData","hasEmail":"mailto:no-reply@data.sf.gov"},"description":"This data set includes monthly utility consumption separated between tenant owned and commission owned (City of SF owned) end uses. The utilities analyzed are natural gas, electricity and water.","distribution":[{"@type":"dcat:Distribution","describedBy":"https://data.sf.gov/api/views/gcjv-3mzf/columns.json","describedByType":"application/json","downloadURL":"https://data.sf.gov/api/v3/views/gcjv-3mzf/query.json?accessType=DOWNLOAD","mediaType":"application/json"},{"@type":"dcat:Distribution","describedBy":"https://data.sf.gov/api/views/gcjv-3mzf/columns.xml","describedByType":"application/xml","downloadURL":"https://data.sf.gov/api/v3/views/gcjv-3mzf/query.xml?accessType=DOWNLOAD","mediaType":"application/xml"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/gcjv-3mzf/export.csv?accessType=DOWNLOAD","mediaType":"text/csv"}],"identifier":"https://data.sf.gov/api/views/gcjv-3mzf","issued":"2018-06-13","keyword":["airport","energy","greenhouse gas emissions","sfo","utilities","utility consumption"],"landingPage":"https://data.sf.gov/d/gcjv-3mzf","license":"http://opendatacommons.org/licenses/pddl/1.0/","modified":"2024-03-13","publisher":{"@type":"org:Organization","name":"data.sf.gov"},"theme":["Energy and Environment"],"title":"SFO Airport Monthly Utility Consumption for Natural Gas, Water, and Electricity"},"description":"This data set includes monthly utility consumption separated between tenant owned and commission owned (City of SF owned) end uses. 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The Department of the Environment collects this data from various sources and calculates the emissions per current greenhouse gas protocols. This data supports San Francisco's climate change planning and mitigation strategies.\n\nNote: Greenhouse gas emissions were calculated based on the ICLEI 2012 U.S. Community Protocol Version 1.0. San Francisco inventories are completed in accordance with the ICLEI U.S. Community Protocol (USCP) for Accounting and Reporting of Greenhouse Gas Emissions. The methodology and sectors tracked were third party verified in inventory year 2012. The subsequent inventories are completed according to the guidance of the verifiers. The third-party verification memo for 2010 is available at http://sfenvironment.org/download/2010-community-greenhouse-gas-inventory-3rd-party-verification-memo-march-2013 and for 2012 at http://sfenvironment.org/download/2012-community-greenhouse-gas-inventory-3rd-party-verification-memo-january-2015. In 2015, the City began reporting its emissions to C40 to improve its GHG emissions inventory by using a newer protocol to estimate emissions referred to as the Global Protocol for Community-Scale Greenhouse Gas Emissions Inventories (GPC). GPC is a framework unifying emissions inventories globally while incorporating new categories to track. San Francisco has been tracking its emissions since 1990; hence, it continues to use the ICLEI USCP. Today, San Francisco continues to disclose emissions under the GPC framework for reporting purposes to and compliance with the Global Covenant of Mayors (GCOM).","distribution":[{"@type":"dcat:Distribution","describedBy":"https://data.sf.gov/api/views/btm4-e4ak/columns.json","describedByType":"application/json","downloadURL":"https://data.sf.gov/api/v3/views/btm4-e4ak/query.json?accessType=DOWNLOAD","mediaType":"application/json"},{"@type":"dcat:Distribution","describedBy":"https://data.sf.gov/api/views/btm4-e4ak/columns.xml","describedByType":"application/xml","downloadURL":"https://data.sf.gov/api/v3/views/btm4-e4ak/query.xml?accessType=DOWNLOAD","mediaType":"application/xml"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/btm4-e4ak/export.csv?accessType=DOWNLOAD","mediaType":"text/csv"}],"identifier":"https://data.sf.gov/api/views/btm4-e4ak","issued":"2018-10-31","keyword":["carbon emissions","climate","climate change","communitywide","environment","ghg inventory","greenhouse gas emissions","san francisco climate action strategy","sustainability"],"landingPage":"https://data.sf.gov/d/btm4-e4ak","license":"http://opendatacommons.org/licenses/pddl/1.0/","modified":"2024-06-20","publisher":{"@type":"org:Organization","name":"data.sf.gov"},"theme":["Energy and Environment"],"title":"San Francisco Communitywide Greenhouse Gas Inventory"},"description":"The purpose of the San Francisco Communitywide Greenhouse Gas Inventory is to measure and track greenhouse gas emissions to determine progress towards meeting the City's climate action goals. The Department of the Environment collects this data from various sources and calculates the emissions per current greenhouse gas protocols. This data supports San Francisco's climate change planning and mitigation strategies.\n\nNote: Greenhouse gas emissions were calculated based on the ICLEI 2012 U.S. Community Protocol Version 1.0. San Francisco inventories are completed in accordance with the ICLEI U.S. Community Protocol (USCP) for Accounting and Reporting of Greenhouse Gas Emissions. The methodology and sectors tracked were third party verified in inventory year 2012. The subsequent inventories are completed according to the guidance of the verifiers. The third-party verification memo for 2010 is available at http://sfenvironment.org/download/2010-community-greenhouse-gas-inventory-3rd-party-verification-memo-march-2013 and for 2012 at http://sfenvironment.org/download/2012-community-greenhouse-gas-inventory-3rd-party-verification-memo-january-2015. In 2015, the City began reporting its emissions to C40 to improve its GHG emissions inventory by using a newer protocol to estimate emissions referred to as the Global Protocol for Community-Scale Greenhouse Gas Emissions Inventories (GPC). GPC is a framework unifying emissions inventories globally while incorporating new categories to track. San Francisco has been tracking its emissions since 1990; hence, it continues to use the ICLEI USCP. Today, San Francisco continues to disclose emissions under the GPC framework for reporting purposes to and compliance with the Global Covenant of Mayors (GCOM).","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/489ec520-c15c-4376-b979-dde4739fa34f","harvest_record_raw":"https://catalog.data.gov/harvest_record/489ec520-c15c-4376-b979-dde4739fa34f/raw","has_download":true,"has_spatial":false,"identifier":"https://data.sf.gov/api/views/btm4-e4ak","keyword":["carbon emissions","climate","climate change","communitywide","environment","ghg inventory","greenhouse gas emissions","san francisco climate action strategy","sustainability"],"last_harvested_date":"2026-09-02T18:55:48.420868","organization":{"aliases":["sf","california"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"7f3c6c7a-ef5f-4ee0-87ce-a0300ba767d5","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/city_san_francisco_ca.png","name":"City of San Francisco","organization_type":"City Government","slug":"san-francisco-ca"},"parent_identifier":null,"popularity":3,"publisher":"data.sf.gov","slug":"san-francisco-communitywide-greenhouse-gas-inventory","spatial_centroid":null,"spatial_shape":null,"theme":["Energy and Environment"],"title":"San Francisco Communitywide Greenhouse Gas Inventory","type":"dataset"},{"_score":14.948668,"_sort":[1788375346739,14.948668,0,"f2b18b37-ce39-494f-9079-cbdf746bfce6"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","contactPoint":{"@type":"vcard:Contact","fn":"OpenData","hasEmail":"mailto:no-reply@data.sf.gov"},"description":"<strong>This dataset will replace the <u><a href=\"https://data.sfgov.org/d/k3fc-45qw/\">previous version of this dataset</a></u>, which will no longer be updated.</strong>\n\n<strong>A. SUMMARY</strong>\nSan Francisco\u2019s Existing Buildings Energy Performance Ordinance requires owners of non-residential buildings over 10,000 square feet to annually benchmark and disclose energy performance. On behalf of City agencies, the San Francisco Public Utilities Commission (SFPUC) benchmarks and reports energy use for a portfolio of approximately 500 public facilities buildings. The performance of public facilities can be examined in an interactive report at https://bit.ly/SFMunicipalBenchmarking, and annual reports from 2011-present are available there as well.\n\nThis dataset presents the energy performance and basic characteristics for public facilities that is visualized by the SFPUC\u2019s interactive report.\n\nIn addition, energy performance data for non-municipal buildings (i.e. commercial buildings of 10,000 square feet or larger, and multifamily & mixed-use buildings of 50,000 square feet or larger) is available at: https://bit.ly/ExistingBuildingsReport\n\n<strong>B. HOW THE DATASET IS CREATED</strong>\nIn compliance with California Energy Benchmarking Regulations (CA Public Resources Code Section 25402.10 and CCR Title 20 Section 1680), and San Francisco Existing Buildings Energy Ordinance (Environment Code Chapter 20), the San Francisco Public Utilities Commission provides energy benchmarking services on behalf of municipal facilities. Details for public facilities are compiled from city records, and energy usage is compiled from utility records; related metrics such as energy use intensity are calculated from the combination of such records. Data is subjected to quality assurance validation prior to publication. For additional information regarding data sources and assumptions, please review the \"Data Sources and Assumptions\" page of the Municipal Facilities Energy Benchmarking dashboard: https://bit.ly/SFMunicipalBenchmarking.\n\n<strong>C. UPDATE PROCESS</strong>\nUpdated Annually, but any adjustments may be made throughout the year.\n\n<strong>E. RELATED DATASETS</strong>\n<u><a href=\"https://data.sfgov.org/d/96ck-qcfe/\">Existing Buildings Energy Performance Ordinance Report</a></u>","distribution":[{"@type":"dcat:Distribution","describedBy":"https://data.sf.gov/api/views/bfhx-j6n5/columns.json","describedByType":"application/json","downloadURL":"https://data.sf.gov/api/v3/views/bfhx-j6n5/query.json?accessType=DOWNLOAD","mediaType":"application/json"},{"@type":"dcat:Distribution","describedBy":"https://data.sf.gov/api/views/bfhx-j6n5/columns.xml","describedByType":"application/xml","downloadURL":"https://data.sf.gov/api/v3/views/bfhx-j6n5/query.xml?accessType=DOWNLOAD","mediaType":"application/xml"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/bfhx-j6n5/export.csv?accessType=DOWNLOAD","mediaType":"text/csv"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/bfhx-j6n5/export.kml?accessType=DOWNLOAD","mediaType":"application/vnd.google-earth.kml+xml"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/bfhx-j6n5/export.kmz?accessType=DOWNLOAD","mediaType":"application/vnd.google-earth.kmz"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/bfhx-j6n5/query.geojson?accessType=DOWNLOAD","mediaType":"application/geo+json"}],"identifier":"https://data.sf.gov/api/views/bfhx-j6n5","issued":"2026-03-19","keyword":["untagged"],"landingPage":"https://data.sf.gov/d/bfhx-j6n5","license":"http://opendatacommons.org/licenses/pddl/1.0/","modified":"2026-03-20","publisher":{"@type":"org:Organization","name":"data.sf.gov"},"theme":["Energy and Environment"],"title":"San Francisco Municipal Energy Benchmarking"},"description":"<strong>This dataset will replace the <u><a href=\"https://data.sfgov.org/d/k3fc-45qw/\">previous version of this dataset</a></u>, which will no longer be updated.</strong>\n\n<strong>A. SUMMARY</strong>\nSan Francisco\u2019s Existing Buildings Energy Performance Ordinance requires owners of non-residential buildings over 10,000 square feet to annually benchmark and disclose energy performance. On behalf of City agencies, the San Francisco Public Utilities Commission (SFPUC) benchmarks and reports energy use for a portfolio of approximately 500 public facilities buildings. The performance of public facilities can be examined in an interactive report at https://bit.ly/SFMunicipalBenchmarking, and annual reports from 2011-present are available there as well.\n\nThis dataset presents the energy performance and basic characteristics for public facilities that is visualized by the SFPUC\u2019s interactive report.\n\nIn addition, energy performance data for non-municipal buildings (i.e. commercial buildings of 10,000 square feet or larger, and multifamily & mixed-use buildings of 50,000 square feet or larger) is available at: https://bit.ly/ExistingBuildingsReport\n\n<strong>B. HOW THE DATASET IS CREATED</strong>\nIn compliance with California Energy Benchmarking Regulations (CA Public Resources Code Section 25402.10 and CCR Title 20 Section 1680), and San Francisco Existing Buildings Energy Ordinance (Environment Code Chapter 20), the San Francisco Public Utilities Commission provides energy benchmarking services on behalf of municipal facilities. Details for public facilities are compiled from city records, and energy usage is compiled from utility records; related metrics such as energy use intensity are calculated from the combination of such records. Data is subjected to quality assurance validation prior to publication. For additional information regarding data sources and assumptions, please review the \"Data Sources and Assumptions\" page of the Municipal Facilities Energy Benchmarking dashboard: https://bit.ly/SFMunicipalBenchmarking.\n\n<strong>C. UPDATE PROCESS</strong>\nUpdated Annually, but any adjustments may be made throughout the year.\n\n<strong>E. RELATED DATASETS</strong>\n<u><a href=\"https://data.sfgov.org/d/96ck-qcfe/\">Existing Buildings Energy Performance Ordinance Report</a></u>","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/e93fd7a5-15b1-4e30-9950-2817015fecce","harvest_record_raw":"https://catalog.data.gov/harvest_record/e93fd7a5-15b1-4e30-9950-2817015fecce/raw","has_download":true,"has_spatial":false,"identifier":"https://data.sf.gov/api/views/bfhx-j6n5","keyword":["untagged"],"last_harvested_date":"2026-09-02T18:55:46.739728","organization":{"aliases":["sf","california"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"7f3c6c7a-ef5f-4ee0-87ce-a0300ba767d5","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/city_san_francisco_ca.png","name":"City of San Francisco","organization_type":"City Government","slug":"san-francisco-ca"},"parent_identifier":null,"popularity":0,"publisher":"data.sf.gov","slug":"san-francisco-municipal-energy-benchmarking","spatial_centroid":null,"spatial_shape":null,"theme":["Energy and Environment"],"title":"San Francisco Municipal Energy Benchmarking","type":"dataset"},{"_score":24.897373,"_sort":[1788375340760,24.897373,5,"e9cc3219-428a-4043-b409-3b1fcfdb865d"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","contactPoint":{"@type":"vcard:Contact","fn":"OpenData","hasEmail":"mailto:no-reply@data.sf.gov"},"description":"<strong>A. SUMMARY</strong>\nThe Existing Buildings Energy Performance Ordinance (Environment Code Chapter 20) requires that each non-residential building with at least 10,000 square feet of conditioned (heated or cooled) space and each residential building with at least 50,000 square feet of conditioned space must be benchmarked annually using Energy Star Portfolio Manager. Each non-residential building specified above is also required to undergo an energy audit, retrocommissioning, or develop a plan for decarbonization at least once every 5 years.\n\nMore information:\n<u><a href=\"http://www.sfenvironment.org/ebo\">San Francisco Existing Buildings Energy Ordinance Website</a></u>\n\n<strong>B. HOW THE DATASET IS CREATED</strong>\nThe data is sourced from the benchmark and energy audit reports submitted for compliance with Environment Code Chapter 20. The dataset is presented in two tables which together provide basic characteristics, compliance status, and a public record of reported energy performance.\n\n<strong>C. UPDATE PROCESS</strong>\nThis dataset will be updated on a monthly basis.\n\n<strong>D. HOW TO USE THIS DATASET</strong>\n<u><a href=\"https://data.sfgov.org/Energy-and-Environment/Existing-Buildings-Basic-Info-and-Audit-Compliance/vgqy-2ca4\">Existing Buildings - Basic Info and Audit Compliance Status</a></u> -- This filtered view contains one record per building and provides basic characteristics (such as size and vintage). For commercial buildings, the table indicates when an energy audit or decarbonization plan is due.\n\n<u><a href=\"https://data.sfgov.org/Energy-and-Environment/Existing-Buildings-Benchmark-Reports/4ua7-5sfx\">Existing Buildings - Benchmark Reports</a></u> -- Each row of this filtered view presents one year of benchmarking data for one building \u2013 so there are multiple records per building. One year of data includes compliance status, and if the building complied it also presents energy use data including gas, electricity, steam and EPA-estimated operational carbon emissions.\n\nThis dataset contains the information of the two views joined on Parcel Number.\n\n<strong>E. RELATED DATASETS</strong>\n<u><a href=\"https://data.sfgov.org/d/bfhx-j6n5/\">San Francisco Municipal Energy Benchmarking</a></u>","distribution":[{"@type":"dcat:Distribution","describedBy":"https://data.sf.gov/api/views/96ck-qcfe/columns.json","describedByType":"application/json","downloadURL":"https://data.sf.gov/api/v3/views/96ck-qcfe/query.json?accessType=DOWNLOAD","mediaType":"application/json"},{"@type":"dcat:Distribution","describedBy":"https://data.sf.gov/api/views/96ck-qcfe/columns.xml","describedByType":"application/xml","downloadURL":"https://data.sf.gov/api/v3/views/96ck-qcfe/query.xml?accessType=DOWNLOAD","mediaType":"application/xml"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/96ck-qcfe/export.csv?accessType=DOWNLOAD","mediaType":"text/csv"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/96ck-qcfe/export.kml?accessType=DOWNLOAD","mediaType":"application/vnd.google-earth.kml+xml"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/96ck-qcfe/export.kmz?accessType=DOWNLOAD","mediaType":"application/vnd.google-earth.kmz"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/96ck-qcfe/query.geojson?accessType=DOWNLOAD","mediaType":"application/geo+json"}],"identifier":"https://data.sf.gov/api/views/96ck-qcfe","issued":"2023-09-14","keyword":["benchmark","benchmarking","building","buildings","carbon emissions","energy","greenhouse gas emissions"],"landingPage":"https://data.sf.gov/d/96ck-qcfe","license":"http://opendatacommons.org/licenses/pddl/1.0/","modified":"2026-08-29","publisher":{"@type":"org:Organization","name":"data.sf.gov"},"theme":["Energy and Environment"],"title":"Existing Buildings Energy Performance Ordinance Report"},"description":"<strong>A. SUMMARY</strong>\nThe Existing Buildings Energy Performance Ordinance (Environment Code Chapter 20) requires that each non-residential building with at least 10,000 square feet of conditioned (heated or cooled) space and each residential building with at least 50,000 square feet of conditioned space must be benchmarked annually using Energy Star Portfolio Manager. Each non-residential building specified above is also required to undergo an energy audit, retrocommissioning, or develop a plan for decarbonization at least once every 5 years.\n\nMore information:\n<u><a href=\"http://www.sfenvironment.org/ebo\">San Francisco Existing Buildings Energy Ordinance Website</a></u>\n\n<strong>B. HOW THE DATASET IS CREATED</strong>\nThe data is sourced from the benchmark and energy audit reports submitted for compliance with Environment Code Chapter 20. The dataset is presented in two tables which together provide basic characteristics, compliance status, and a public record of reported energy performance.\n\n<strong>C. UPDATE PROCESS</strong>\nThis dataset will be updated on a monthly basis.\n\n<strong>D. HOW TO USE THIS DATASET</strong>\n<u><a href=\"https://data.sfgov.org/Energy-and-Environment/Existing-Buildings-Basic-Info-and-Audit-Compliance/vgqy-2ca4\">Existing Buildings - Basic Info and Audit Compliance Status</a></u> -- This filtered view contains one record per building and provides basic characteristics (such as size and vintage). For commercial buildings, the table indicates when an energy audit or decarbonization plan is due.\n\n<u><a href=\"https://data.sfgov.org/Energy-and-Environment/Existing-Buildings-Benchmark-Reports/4ua7-5sfx\">Existing Buildings - Benchmark Reports</a></u> -- Each row of this filtered view presents one year of benchmarking data for one building \u2013 so there are multiple records per building. One year of data includes compliance status, and if the building complied it also presents energy use data including gas, electricity, steam and EPA-estimated operational carbon emissions.\n\nThis dataset contains the information of the two views joined on Parcel Number.\n\n<strong>E. RELATED DATASETS</strong>\n<u><a href=\"https://data.sfgov.org/d/bfhx-j6n5/\">San Francisco Municipal Energy Benchmarking</a></u>","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/1e50b0bd-b8e5-4ec4-b90e-28d68f4470ee","harvest_record_raw":"https://catalog.data.gov/harvest_record/1e50b0bd-b8e5-4ec4-b90e-28d68f4470ee/raw","has_download":true,"has_spatial":false,"identifier":"https://data.sf.gov/api/views/96ck-qcfe","keyword":["benchmark","benchmarking","building","buildings","carbon emissions","energy","greenhouse gas emissions"],"last_harvested_date":"2026-09-02T18:55:40.760442","organization":{"aliases":["sf","california"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"7f3c6c7a-ef5f-4ee0-87ce-a0300ba767d5","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/city_san_francisco_ca.png","name":"City of San Francisco","organization_type":"City Government","slug":"san-francisco-ca"},"parent_identifier":null,"popularity":5,"publisher":"data.sf.gov","slug":"existing-buildings-energy-performance-ordinance-report","spatial_centroid":null,"spatial_shape":null,"theme":["Energy and Environment"],"title":"Existing Buildings Energy Performance Ordinance Report","type":"dataset"},{"_score":4.6192837,"_sort":[1788375336824,4.6192837,0,"cf7b9796-b7dd-4a66-8b2e-fba3e4d647da"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","contactPoint":{"@type":"vcard:Contact","fn":"Alex Morrison","hasEmail":"mailto:no-reply@data.sf.gov"},"description":"California Tsunami Hazard Area Maps and data are prepared to assist cities and counties in identifying their tsunami hazard for tsunami response planning. The maps and data are compiled with the best currently available scientific information and represent areas that could be exposed to tsunami hazards during a tsunami event. They are primarily based on inundation limits corresponding to a 975-year average return period tsunami event model. These limits have been extended to reflect potential local tsunami sources not considered in probabilistic analysis and are also modified to reflect the practical need to define limits that coincide with geographic features or city streets.\n\nState of California, 2021, Tsunami Hazard Area Map, County name County; produced by the California Geological Survey, the California Governor's Office of Emergency Services, and AECOM; dated date on the map, mapped at multiple scales.","distribution":[{"@type":"dcat:Distribution","describedBy":"https://data.sf.gov/api/views/7p2k-c3z6/columns.json","describedByType":"application/json","downloadURL":"https://data.sf.gov/api/v3/views/7p2k-c3z6/query.json?accessType=DOWNLOAD","mediaType":"application/json"},{"@type":"dcat:Distribution","describedBy":"https://data.sf.gov/api/views/7p2k-c3z6/columns.xml","describedByType":"application/xml","downloadURL":"https://data.sf.gov/api/v3/views/7p2k-c3z6/query.xml?accessType=DOWNLOAD","mediaType":"application/xml"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/7p2k-c3z6/export.csv?accessType=DOWNLOAD","mediaType":"text/csv"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/7p2k-c3z6/export.kml?accessType=DOWNLOAD","mediaType":"application/vnd.google-earth.kml+xml"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/7p2k-c3z6/export.kmz?accessType=DOWNLOAD","mediaType":"application/vnd.google-earth.kmz"},{"@type":"dcat:Distribution","downloadURL":"https://data.sf.gov/api/v3/views/7p2k-c3z6/query.geojson?accessType=DOWNLOAD","mediaType":"application/geo+json"}],"identifier":"https://data.sf.gov/api/views/7p2k-c3z6","issued":"2021-08-03","keyword":["untagged"],"landingPage":"https://data.sf.gov/d/7p2k-c3z6","modified":"2024-12-17","publisher":{"@type":"org:Organization","name":"data.sf.gov"},"theme":["Energy and Environment"],"title":"Tsunami Inundation Hazard Zone (2021 Update)"},"description":"California Tsunami Hazard Area Maps and data are prepared to assist cities and counties in identifying their tsunami hazard for tsunami response planning. The maps and data are compiled with the best currently available scientific information and represent areas that could be exposed to tsunami hazards during a tsunami event. They are primarily based on inundation limits corresponding to a 975-year average return period tsunami event model. These limits have been extended to reflect potential local tsunami sources not considered in probabilistic analysis and are also modified to reflect the practical need to define limits that coincide with geographic features or city streets.\n\nState of California, 2021, Tsunami Hazard Area Map, County name County; produced by the California Geological Survey, the California Governor's Office of Emergency Services, and AECOM; dated date on the map, mapped at multiple scales.","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/599a6e76-6033-4c3b-9119-fd080cd27f72","harvest_record_raw":"https://catalog.data.gov/harvest_record/599a6e76-6033-4c3b-9119-fd080cd27f72/raw","has_download":true,"has_spatial":false,"identifier":"https://data.sf.gov/api/views/7p2k-c3z6","keyword":["untagged"],"last_harvested_date":"2026-09-02T18:55:36.824806","organization":{"aliases":["sf","california"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"7f3c6c7a-ef5f-4ee0-87ce-a0300ba767d5","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/city_san_francisco_ca.png","name":"City of San Francisco","organization_type":"City Government","slug":"san-francisco-ca"},"parent_identifier":null,"popularity":0,"publisher":"data.sf.gov","slug":"tsunami-inundation-hazard-zone-2021-update","spatial_centroid":null,"spatial_shape":null,"theme":["Energy and Environment"],"title":"Tsunami Inundation Hazard Zone (2021 Update)","type":"dataset"}],"sort":"last_harvested_date"}