Timeline / Data.gov — Health Datasets
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Evidence
| Source | Data.gov — Health Datasets |
|---|---|
| Agency | Data.gov |
| URL | https://api.gsa.gov/technology/datagov/v4/search?q=health&sort=last_harvested_date&per_page=100&api_key=${DATAGOV_API_KEY} |
| Observed by | Civic Memory, directly, on 2026-10-08T00:16:47+00:00 |
| Content type | application/json |
| Current object |
4568eddd01a2689f1b337c495afa5fbfca685058bb17e36acc5fa75ab2558efe
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| Previous object |
6746cecdaadf866faed0cca69a15c4bed06ef24569b797d8601afa274f7029db
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What changed derived
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civic-memory.diff_engine 1.1.0 at
2026-10-08T00:16:47+00:00 by normalizing the two archived objects above. The
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without loss. 3646 line(s) added, 3783 line(s) removed.
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Such infor- mation enables system operators to make informed maintenance decisions and streamline operational and mission-level activities. We develop a model-based prognostics method- ology for pneumatic valves used in ground support equipment for cryogenic propellant loading operations. These valves are used to control the ow of propellant, so failures may have a signi cant impact on launch availability. Therefore, correctly predicting when valves will fail enables timely maintenance that avoids launch delays and aborts. The approach utilizes mathematical models describing the underlying physics of valve degradation, and, employing the particle ltering algorithm for joint state-parameter estimation, determines the health state of the valve and the rate of damage progression, from which EOL and RUL predictions are made. We develop a prototype user interface for valve prognostics, and demonstrate the prognostics approach using historical pneumatic valve data from the Space Shuttle refueling system.", - "distribution": [ - { - "@type": "dcat:Distribution", - "description": "2011_AIAA_Valves.pdf", - "downloadURL": "https://c3.nasa.gov/dashlink/static/media/publication/2011_AIAA_Valves.pdf", - "format": "PDF", - "mediaType": "application/pdf", - "title": "2011_AIAA_Valves.pdf" - } - ], - "identifier": "DASHLINK_779", - "issued": "2013-06-19", - "keyword": [ - "ames", - "dashlink", - "nasa" - ], - "landingPage": "https://c3.nasa.gov/dashlink/resources/779/", - "modified": "2025-03-31", - "programCode": [ - "026:029" - ], - "publisher": { - "@type": "org:Organization", - "name": "Dashlink" - }, - "title": "Prognostics for Ground Support Systems: Case Study on Pneumatic Valves" - }, - "description": "Prognostics technologies determine the health (or damage) state of a component or sub- system, and make end of life (EOL) and remaining useful life (RUL) predictions. 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We develop a prototype user interface for valve prognostics, and demonstrate the prognostics approach using historical pneumatic valve data from the Space Shuttle refueling system.", - "distribution_titles": [ - "2011_AIAA_Valves.pdf" - ], - "harvest_record": "https://catalog.data.gov/harvest_record/22d11cfd-f7ef-4d7b-a469-9fc0cdcd1ecf", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/22d11cfd-f7ef-4d7b-a469-9fc0cdcd1ecf/raw", - "has_download": true, - "has_spatial": false, - "identifier": "DASHLINK_779", - "keyword": [ - "ames", - "dashlink", - "nasa" - ], - "last_harvested_date": "2026-10-07T01:03:48.960810", - "organization": { - "aliases": [ - "" - ], - "code_repo_exempt": false, - "code_repo_url": null, - "description": null, - "id": "f4ca4614-8901-409b-8553-2e994ad10023", - "logo": "https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png", - "name": "National Aeronautics and Space Administration", - "organization_type": "Federal Government", - "slug": "nasa" - }, - "parent_identifier": null, - "popularity": 2, - "publisher": "Dashlink", - "slug": "prognostics-for-ground-support-systems-case-study-on-pneumatic-valves", - "spatial_centroid": null, - "spatial_shape": null, - "theme": [], - "title": "Prognostics for Ground Support Systems: Case Study on Pneumatic Valves", - "type": "dataset" - }, - { - "_score": 19.734165, - "_sort": [ - 1791335003631, - 19.734165, - 2, - "0ae31ee6-9a12-4b92-8011-14fc29df5084" - ], - "access_level": "public", - "dcat": { - "@type": "dcat:Dataset", - "accessLevel": "public", - "accrualPeriodicity": "irregular", - "bureauCode": [ - "026:00" - ], - "contactPoint": { - "@type": "vcard:Contact", - "fn": "Indir Jaganjac", - "hasEmail": "mailto:ijaganjac@yahoo.com" - }, - "description": "FLTz flight simulator RecorderRun9 data are analyzed in order \r\nto compute systems health score using Granger causal connectovity \r\nanalysis. 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First G-causality is computed, and then causal density (cd) is \r\ncomputed in interval [0,1]. Numerical value of causal density for this data file is 0.4711, which corresponds to systems health score.", - "distribution_titles": [ - "FLTz FOQA G-causality Run9.zip" - ], - "harvest_record": "https://catalog.data.gov/harvest_record/486f586b-3644-4b0b-8947-b1a1f8813a5e", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/486f586b-3644-4b0b-8947-b1a1f8813a5e/raw", - "has_download": true, - "has_spatial": false, - "identifier": "DASHLINK_625", - "keyword": [ - "ames", - "dashlink", - "nasa" - ], - "last_harvested_date": "2026-10-07T01:03:23.631189", - "organization": { - "aliases": [ - "" - ], - "code_repo_exempt": false, - "code_repo_url": null, - "description": null, - "id": "f4ca4614-8901-409b-8553-2e994ad10023", - "logo": "https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png", - "name": "National Aeronautics and Space Administration", - "organization_type": "Federal Government", - "slug": "nasa" - }, - "parent_identifier": null, - "popularity": 2, - "publisher": "Dashlink", - "slug": "indir-jaganjac", - "spatial_centroid": null, - "spatial_shape": null, - "theme": [], - "title": "Indir Jaganjac", - "type": "dataset" - }, - { - "_score": 37.268044, - "_sort": [ - 1791334966628, - 37.268044, - 3, - "18013d92-714b-4c50-a948-1e628b94e9ee" - ], - "access_level": "public", - "dcat": { - "@type": "dcat:Dataset", - "accessLevel": "public", - "accrualPeriodicity": "irregular", - "bureauCode": [ - "026:00" - ], - "contactPoint": { - "@type": "vcard:Contact", - "fn": "Carlton Allen", - "hasEmail": "mailto:carlton.c.allen@nasa.gov" - }, - "description": "Structural damage to ball grid array interconnects incurred during vibration testing has been monitored in the prefailure space using resistance spectroscopy-based state space vectors, rate of change of the state variable, and acceleration of the state variable. The technique is intended for condition monitoring in high reliability applications where the knowledge of impending failure is critical and the risks in terms of loss of functionality are too high to bear. Future state of the system has been estimated based on a second-order Kalman Filter model and a Bayesian Framework. The measured state variable has been related to the underlying interconnect damage in the form of inelastic strain energy density. Performance of the prognostic health management algorithm during the vibration test has been quantified using performance evaluation metrics. The method- ology has been demonstrated on leadfree area-array electronic assemblies subjected to vibration. Model predictions have been correlated with experimental data. The presented approach is applicable to functional systems where corner interconnects in area-array packages may be often redundant. Prognostic metrics including α − λ precision, β accuracy, and relative accuracy have been used to assess the performance of the damage proxies. The presented approach enables the estimation of residual life based on level of risk averseness.", - "distribution": [ - { - "@type": "dcat:Distribution", - "downloadURL": "http://curator.jsc.nasa.gov/lunar/catalogs/other/A16_4_10mm.pdf", - "format": "PDF", - "mediaType": "application/pdf" - } - ], - "identifier": "DASHLINK_760", - "issued": "2013-06-19", - "keyword": [ - "ames", - "dashlink", - "nasa" - ], - "landingPage": "https://c3.nasa.gov/dashlink/resources/760/", - "modified": "2025-03-31", - "programCode": [ - "026:029" - ], - "publisher": { - "@type": "org:Organization", - "name": "Dashlink" - }, - "title": "Prognostics Health Management of Electronic Systems Under Mechanical Shock and Vibration Using Kalman Filter Models and Metrics" - }, - "description": "Structural damage to ball grid array interconnects incurred during vibration testing has been monitored in the prefailure space using resistance spectroscopy-based state space vectors, rate of change of the state variable, and acceleration of the state variable. The technique is intended for condition monitoring in high reliability applications where the knowledge of impending failure is critical and the risks in terms of loss of functionality are too high to bear. Future state of the system has been estimated based on a second-order Kalman Filter model and a Bayesian Framework. The measured state variable has been related to the underlying interconnect damage in the form of inelastic strain energy density. Performance of the prognostic health management algorithm during the vibration test has been quantified using performance evaluation metrics. The method- ology has been demonstrated on leadfree area-array electronic assemblies subjected to vibration. Model predictions have been correlated with experimental data. The presented approach is applicable to functional systems where corner interconnects in area-array packages may be often redundant. Prognostic metrics including α − λ precision, β accuracy, and relative accuracy have been used to assess the performance of the damage proxies. The presented approach enables the estimation of residual life based on level of risk averseness.", - "distribution_titles": [], - "harvest_record": "https://catalog.data.gov/harvest_record/84d2c31b-f859-4166-9701-56919e7f66ca", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/84d2c31b-f859-4166-9701-56919e7f66ca/raw", - "has_download": true, - "has_spatial": false, - "identifier": "DASHLINK_760", - "keyword": [ - "ames", - "dashlink", - "nasa" - ], - "last_harvested_date": "2026-10-07T01:02:46.628214", - "organization": { - "aliases": [ - "" - ], - "code_repo_exempt": false, - "code_repo_url": null, - "description": null, - "id": "f4ca4614-8901-409b-8553-2e994ad10023", - "logo": "https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png", - "name": "National Aeronautics and Space Administration", - "organization_type": "Federal Government", - "slug": "nasa" - }, - "parent_identifier": null, - "popularity": 3, - "publisher": "Dashlink", - "slug": "prognostics-health-management-of-electronic-systems-under-mechanical-shock-and-vibration-u", - "spatial_centroid": null, - "spatial_shape": null, - "theme": [], - "title": "Prognostics Health Management of Electronic Systems Under Mechanical Shock and Vibration Using Kalman Filter Models and Metrics", - "type": "dataset" - }, - { - "_score": 15.6816025, - "_sort": [ - 1791334933955, - 15.6816025, - 1, - "31f584dc-749e-43ab-8e07-c1a266d71ef7" - ], - "access_level": "public", - "dcat": { - "@type": "dcat:Dataset", - "accessLevel": "public", - "accrualPeriodicity": "irregular", - "bureauCode": [ - "026:00" - ], - "contactPoint": { - "@type": "vcard:Contact", - "fn": "Jose Celaya Galvan", - "hasEmail": "mailto:jose.r.celayagalvan@nasa.gov" - }, - "description": "A remaining useful life prediction methodology for electrolytic capacitors is presented. This methodology is based on the Kalman filter framework and an empirical degradation model. Electrolytic capacitors are used in several applications ranging from power supplies on critical avionics equipment to power drivers for electro-mechanical actuators. These devices are known for their comparatively low reliability and given their criticality in electronics subsystems they are a good candidate for component level prognostics and health management. Prognostics provides a way to assess remaining useful life of a capacitor based on its current state of health and its anticipated future usage and operational conditions. We present here also, experimental results of an accelerated aging test under electrical stresses. The data obtained in this test form the basis for a remaining life prediction algorithm where a model of the degradation process is suggested. This preliminary remaining life prediction algorithm serves as a demonstration of how prognostics methodologies could be used for electrolytic capacitors. In addition, the use degradation progression data from accelerated aging, provides an avenue for validation of applications of the Kalman filter based prognostics methods typically used for remaining useful life predictions in other applications.", - "distribution": [ - { - "@type": "dcat:Distribution", - "description": "Access the data via HTTPS.", - "downloadURL": "https://acdisc.gesdisc.eosdis.nasa.gov/data/UARS_Correlative_Level4/UARZCUKM/", - "format": "HTML", - "mediaType": "text/html", - "title": "Download this dataset through a directory map" - }, - { - "@type": "dcat:Distribution", - "description": "Access the dataset landing page from the GES DISC website.", - "downloadURL": "https://disc.gsfc.nasa.gov/datacollection/UARZCUKM_001.html", - "format": "HTML", - "mediaType": "text/html", - "title": "This dataset's landing page" - }, - { - "@type": "dcat:Distribution", - "description": "README Document", - "downloadURL": "https://acdisc.gesdisc.eosdis.nasa.gov/data/UARS_Correlative_Level4/UARZCUKM/doc/README.UARCorr.doc", - "format": "DOC", - "mediaType": "application/msword", - "title": "View this dataset's read me document" - }, - { - "@type": "dcat:Distribution", - "description": "The UARS Project Homepage.", - "downloadURL": "https://uars.gsfc.nasa.gov/", - "format": "HTML", - "mediaType": "text/html", - "title": "The dataset's project home page" - }, - { - "@type": "dcat:Distribution", - "description": "Use the Earthdata Search to find and retrieve data sets across multiple data centers.", - "downloadURL": "https://search.earthdata.nasa.gov/search?q=UARZCUKM", - "format": "HTML", - "mediaType": "text/html", - "title": "Download this dataset through Earthdata Search" - }, - { - "@type": "dcat:Distribution", - "downloadURL": "https://docserver.gesdisc.eosdis.nasa.gov/public/project/Images/UARZCUKM_001.png", - "format": "PNG", - "mediaType": "image/png", - "title": "Get a related visualization" - } - ], - "identifier": "DASHLINK_856", - "issued": "2013-12-12", - "keyword": [ - "ames", - "dashlink", - "nasa" - ], - "landingPage": "https://c3.nasa.gov/dashlink/resources/856/", - "modified": "2025-03-31", - "programCode": [ - "026:029" - ], - "publisher": { - "@type": "org:Organization", - "name": "Dashlink" - }, - "title": "A Model-Based Prognostics Methodology For Electrolytic Capacitors Based On Electrical Overstress Accelerated Aging" - }, - "description": "A remaining useful life prediction methodology for electrolytic capacitors is presented. This methodology is based on the Kalman filter framework and an empirical degradation model. Electrolytic capacitors are used in several applications ranging from power supplies on critical avionics equipment to power drivers for electro-mechanical actuators. These devices are known for their comparatively low reliability and given their criticality in electronics subsystems they are a good candidate for component level prognostics and health management. Prognostics provides a way to assess remaining useful life of a capacitor based on its current state of health and its anticipated future usage and operational conditions. We present here also, experimental results of an accelerated aging test under electrical stresses. The data obtained in this test form the basis for a remaining life prediction algorithm where a model of the degradation process is suggested. This preliminary remaining life prediction algorithm serves as a demonstration of how prognostics methodologies could be used for electrolytic capacitors. In addition, the use degradation progression data from accelerated aging, provides an avenue for validation of applications of the Kalman filter based prognostics methods typically used for remaining useful life predictions in other applications.", - "distribution_titles": [ - "Download this dataset through a directory map", - "This dataset's landing page", - "View this dataset's read me document", - "The dataset's project home page", - "Download this dataset through Earthdata Search", - "Get a related visualization" - ], - "harvest_record": "https://catalog.data.gov/harvest_record/153123fc-2888-4331-bc9e-32a744203c54", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/153123fc-2888-4331-bc9e-32a744203c54/raw", - "has_download": true, - "has_spatial": false, - "identifier": "DASHLINK_856", - "keyword": [ - "ames", - "dashlink", - "nasa" - ], - "last_harvested_date": "2026-10-07T01:02:13.955422", - "organization": { - "aliases": [ - "" - ], - "code_repo_exempt": false, - "code_repo_url": null, - "description": null, - "id": "f4ca4614-8901-409b-8553-2e994ad10023", - "logo": "https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png", - "name": "National Aeronautics and Space Administration", - "organization_type": "Federal Government", - "slug": "nasa" - }, - "parent_identifier": null, - "popularity": 1, - "publisher": "Dashlink", - "slug": "a-model-based-prognostics-methodology-for-electrolytic-capacitors-based-on-electrical-over-fbaca", - "spatial_centroid": null, - "spatial_shape": null, - "theme": [], - "title": "A Model-Based Prognostics Methodology For Electrolytic Capacitors Based On Electrical Overstress Accelerated Aging", - "type": "dataset" - }, - { - "_score": 10.07247, - "_sort": [ - 1791334929679, - 10.07247, - 1, - "284dd584-765a-4c8b-ab9c-2b77ea99f501" - ], - "access_level": "public", - "dcat": { - "@type": "dcat:Dataset", - "accessLevel": "public", - "accrualPeriodicity": "irregular", - "bureauCode": [ - "026:00" - ], - "contactPoint": { - "@type": "vcard:Contact", - "fn": "Beth Beck", - "hasEmail": "mailto:beth.beck@nasa.gov" - }, - "description": "Prognostics is an emerging concept in condition basedmaintenance(CBM)ofcriticalsystems.Alongwith developing the fundamentals of being able to confidently predict Remaining Useful Life (RUL), the technology calls for fielded applications as it inches towards maturation. This requires a stringent performance evaluation so that the significance of the concept can be fully exploited. Currently, prognostics concepts lack standard definitions and suffer from ambiguous and inconsistent interpretations. This lack of standards is in part due to the varied end-user requirements for different applications, time scales, available information, domain dynamics, etc. to name a few issues. Instead, the research community has used a variety of metrics based largely on convenience with respect to their respective requirements. Very little attention has been focused on establishing a common ground to compare different efforts. This paper surveys the metrics that are already used for prognostics in a variety of domains including medicine, nuclear, automotive, aerospace, and electronics. It also considers other domains that involve prediction-related tasks, such as weather and finance. Differences and similarities between these domains and health maintenancehave been analyzed to help understand what performance evaluation methods may or may not be borrowed. Further, these metrics have been categorized in several ways that may be useful in deciding upon a suitable subset for a specific application. Some important prognostic concepts have been defined using a notational framework that enables interpretation of different metrics coherently. Last, but not the least, a list of metrics has been suggested to assess critical aspects of RUL predictions before they are fielded in real applications.", - "distribution": [ - { - "@type": "dcat:Distribution", - "downloadURL": "http://nasa3d.arc.nasa.gov/shared_assets/models/agena-c/agena-c.zip", - "format": "BIN", - "mediaType": "application/octet-stream" - } - ], - "identifier": "DASHLINK_739", - "issued": "2013-05-13", - "keyword": [ - "ames", - "dashlink", - "nasa" - ], - "landingPage": "https://c3.nasa.gov/dashlink/resources/739/", - "modified": "2025-03-31", - "programCode": [ - "026:029" - ], - "publisher": { - "@type": "org:Organization", - "name": "Dashlink" - }, - "title": "A Survey of Metrics for Performance Evaluation of Prognostics" - }, - "description": "Prognostics is an emerging concept in condition basedmaintenance(CBM)ofcriticalsystems.Alongwith developing the fundamentals of being able to confidently predict Remaining Useful Life (RUL), the technology calls for fielded applications as it inches towards maturation. This requires a stringent performance evaluation so that the significance of the concept can be fully exploited. Currently, prognostics concepts lack standard definitions and suffer from ambiguous and inconsistent interpretations. This lack of standards is in part due to the varied end-user requirements for different applications, time scales, available information, domain dynamics, etc. to name a few issues. Instead, the research community has used a variety of metrics based largely on convenience with respect to their respective requirements. Very little attention has been focused on establishing a common ground to compare different efforts. This paper surveys the metrics that are already used for prognostics in a variety of domains including medicine, nuclear, automotive, aerospace, and electronics. It also considers other domains that involve prediction-related tasks, such as weather and finance. Differences and similarities between these domains and health maintenancehave been analyzed to help understand what performance evaluation methods may or may not be borrowed. Further, these metrics have been categorized in several ways that may be useful in deciding upon a suitable subset for a specific application. Some important prognostic concepts have been defined using a notational framework that enables interpretation of different metrics coherently. Last, but not the least, a list of metrics has been suggested to assess critical aspects of RUL predictions before they are fielded in real applications.", - "distribution_titles": [], - "harvest_record": "https://catalog.data.gov/harvest_record/5cc880dc-c860-406e-a39b-c3d25e75928c", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/5cc880dc-c860-406e-a39b-c3d25e75928c/raw", - "has_download": true, - "has_spatial": false, - "identifier": "DASHLINK_739", - "keyword": [ - "ames", - "dashlink", - "nasa" - ], - "last_harvested_date": "2026-10-07T01:02:09.679890", - "organization": { - "aliases": [ - "" - ], - "code_repo_exempt": false, - "code_repo_url": null, - "description": null, - "id": "f4ca4614-8901-409b-8553-2e994ad10023", - "logo": "https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png", - "name": "National Aeronautics and Space Administration", - "organization_type": "Federal Government", - "slug": "nasa" - }, - "parent_identifier": null, - "popularity": 1, - "publisher": "Dashlink", - "slug": "a-survey-of-metrics-for-performance-evaluation-of-prognostics", - "spatial_centroid": null, - "spatial_shape": null, - "theme": [], - "title": "A Survey of Metrics for Performance Evaluation of Prognostics", - "type": "dataset" - }, - { - "_score": 16.38534, - "_sort": [ - 1791334926801, - 16.38534, - 7, - "a35e6d84-5722-4711-bba9-b664f1486b01" - ], - "access_level": "public", - "dcat": { - "@type": "dcat:Dataset", - "accessLevel": "public", - "accrualPeriodicity": "irregular", - "bureauCode": [ - "026:00" - ], - "contactPoint": { - "@type": "vcard:Contact", - "fn": "Kai Goebel", - "hasEmail": "mailto:kai.goebel@nasa.gov" - }, - "description": "Prognostics has received considerable attention recently as an emerging sub-discipline within SHM. Prognosis is here strictly defined as “predicting the time at which a component will no longer perform its intended function”. Loss of function is often times the time at which a component fails. The predicted time to that point becomes then the remaining useful life (RUL). For prognostics to be effective, it must be performed well before deviations from normal performance propagate to a critical effect. This enables a failure preclusion or prevention function to repair or replace the offending components, or if the components cannot be repaired, to retire the system (or vehicle) before the critical failure occurs. Therefore, prognosis has the promise to provide critical information to system operators that will enable safer operation and more cost-efficient use. To that end, Department of Defense (DoD), NASA, and industry have been investigating this technology for use in their vehicle health management solutions. Dedicated prognostic algorithms (in conjunction with failure detection and fault isolation algorithms) must be developed that are capable of operating in an autonomous and real-time vehicle health management system software architecture that is possibly distributed in nature. This envisioned prognostic and health management system will be realized in a vehicle-level reasoner that must have visibility and insight into the results of local diagnostic and prognostic technologies implemented at the LRU and subsystem levels. Accomplishing this effectively requires an integrated suite of prognostic technologies that compute failure effect propagation through diverse subsystems and that can capture interactions that occur in these subsystems. 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In the event of disease outbreak, the\ndepartment investigates to determine the source of the infection, and prevent\nfurther illness.\n\n<p>This dataset captures the restaurants that are\ninspected.<span> </span>The data set is geocoded\nbased on address with approximately 85% of the locations having a valid\ngeo-location.<span> </span></p>\n\n<p>You can find out additional information about our restaurant\ninspections on our website:<span> </span><a href='https://www.wake.gov/departments-government/environmental-health-safety' rel='nofollow ugc'>Food Safety and Sanitation</a></p>\n\n<p>This table captures all Wake County sanitation\ninspections from September 20, 2012 to Present.</p><p>\n\n</p><p>This table is part of a set of data that combined will give\nyou a picture of all restaurant inspections.<span> \n</span>Those three tables are:</p>\n\n<p style='margin-bottom:0in; margin-bottom:.0001pt; text-indent:-.25in;'><span style='color:black;'><span>1.<span style='font:7.0pt "Times New Roman";'> </span></span></span><b><span style='color:black;'>Restaurants:\n</span></b><span style='color:black;'>This table captures all active facilities\nwhere Wake County performs sanitations inspections.<span> </span>Facilities that are closed are removed from\nall three files in this dataset.<span> </span>Per NC\nState regulations, facilities that have a change in ownership are considered\nclosed and the restaurant re-opens under a new permit, even if there is not a change\nin the name of the restaurant.</span></p>\n\n<p style='margin-bottom:0in; margin-bottom:.0001pt; text-indent:-.25in;'><span style='color:black;'><span>2.<span style='font:7.0pt "Times New Roman";'> </span></span></span><b><span style='color:black;'>Food Inspections:\n</span></b><span style='color:black;'>This table captures all Wake County\nperforms sanitations inspections at active restaurants since September 20, 2012</span></p>\n\n<p style='margin-bottom:0in; margin-bottom:.0001pt; text-indent:-.25in;'><span style='color:black;'><span>3.<span style='font:7.0pt "Times New Roman";'> </span></span></span><b><span style='color:black;'><span style='color:rgb(76, 76, 76);'>Food Inspection </span>Violations:\n</span></b><span style='color:black;'>This table captures all violations\nidentified during specific Wake County sanitations inspections at active\nrestaurants since September 20, 2012.<span> </span>It\nreports the results in code violations and according to CDC Risk Factors.<span> </span></span>You can find additional information\nabout the CDC Risk Factors on the FDA website: <a href='https://www.fda.gov/food/retail-food-protection/retail-food-risk-factor-study' rel='nofollow ugc'><span style='font-size:10.0pt; font-family:"Helv","sans-serif"; color:blue; text-decoration:none;'>Retail Risk Factor\nStudy</span></a><span style='color:black;'></span></p>\n\n<p> </p>\n\n<p>The tables can be connected through the <span style='color:black;'>HSISID\nfield.<span> </span></span></p>\n\n\n\n<p style='text-indent:-.25in;'><span style='font-family:Symbol;'><span><span style='font:7.0pt "Times New Roman";'></span></span></span>The frequency of facility inspections fall under\nthe following rules:</p>\n\n<p style='margin-left:.5in;'><b><u><span style='font-family:"Calibri","sans-serif";'>Inspected once per year:</span></u></b></p>\n\n<p style='margin-left:.5in;'><b><span style='font-family:"Calibri","sans-serif";'>Risk Category I </span></b><span style='font-family:"Calibri","sans-serif";'>applies to food service\nestablishments that prepare only non-potentially hazardous foods.</span></p><p style='margin-left:.5in;'><b><u><span style='font-family:"Calibri","sans-serif";'>Inspected twice per year:</span></u></b></p>\n\n<p style='margin-left:.5in;'><b><span style='font-family:"Calibri","sans-serif";'>Risk Category II </span></b><span style='font-family:"Calibri","sans-serif";'>applies to food service\nestablishments that cook and cool no more than two potentially hazardous foods.\nPotentially hazardous raw ingredients shall be received in a ready-to-cook\nform.</span></p><p style='margin-left:.5in;'><b><u><span style='font-family:"Calibri","sans-serif";'>Inspected three times per year</span></u></b></p>\n\n<p style='margin-left:.5in;'><b><span style='font-family:"Calibri","sans-serif";'>Risk Category III </span></b><span style='font-family:"Calibri","sans-serif";'>applies to food service\nestablishments that cook and cool no more than three potentially hazardous\nfoods.</span></p><p style='margin-left:.5in;'><b><u><span style='font-family:"Calibri","sans-serif";'>Inspected four times per year</span></u></b></p>\n\n<p style='margin-left:.5in;'><b><span style='font-size:12.0pt;'>Risk Category IV </span></b><span style='font-size:12.0pt;'>applies to\nfood service establishments that cook and cool an unlimited number of\npotentially hazardous foods. This category also includes those facilities using\nspecialized processes or serving a highly susceptible population.</span></p><span style='color:black;'><span><br /></span></span>\n\n<table border='0' cellpadding='0' cellspacing='0' style='width:513.0pt; border-collapse:collapse; margin-left:6.75pt; margin-right:6.75pt;' width='684'>\n <tbody><tr style='height:30.0pt;'>\n <td style='width:1.75in; padding:0in 5.4pt 0in 5.4pt; height:30.0pt;' valign='bottom' width='168'>\n <p style='margin-bottom:0in; margin-bottom:.0001pt;'><b><span style='color:black;'> </span></b></p>\n \n \n <p style='margin-bottom:0in; margin-bottom:.0001pt;'><b><span style='color:black;'>Field</span></b></p>\n </td>\n <td style='width:387.0pt; padding:0in 5.4pt 0in 5.4pt; height:30.0pt;' valign='bottom' width='516'>\n <p style='margin-bottom:0in; margin-bottom:.0001pt;'><b><span style='color:black;'>Description</span></b></p>\n </td>\n </tr>\n <tr style='height:15.0pt;'>\n <td style='width:1.75in; padding:0in 5.4pt 0in 5.4pt; height:15.0pt;' valign='top' width='168'>\n <p style='margin-bottom:0in; margin-bottom:.0001pt;'><span style='color:black;'>HSISID</span></p>\n </td>\n <td style='width:387.0pt; padding:0in 5.4pt 0in 5.4pt; height:15.0pt;' valign='top' width='516'>\n <p style='margin-bottom:0in; margin-bottom:.0001pt;'><span style='color:black;'>State code identifying the\n restaurant (also the primary key to identify the restaurant)</span></p>\n </td>\n </tr>\n <tr style='height:15.0pt;'>\n <td style='width:1.75in; padding:0in 5.4pt 0in 5.4pt; height:15.0pt;' valign='top' width='168'>\n <p style='margin-bottom:0in; margin-bottom:.0001pt;'><span style='color:black;'>Score</span></p>\n </td>\n <td style='width:387.0pt; padding:0in 5.4pt 0in 5.4pt; height:15.0pt;' valign='top' width='516'>\n <p style='margin-bottom:0in; margin-bottom:.0001pt;'><span style='color:black;'>Final score for this inspection</span></p>\n </td>\n </tr>\n <tr style='height:15.0pt;'>\n <td style='width:1.75in; padding:0in 5.4pt 0in 5.4pt; height:15.0pt;' valign='top' width='168'>\n <p style='margin-bottom:0in; margin-bottom:.0001pt;'><span style='color:black;'>Date</span></p>\n </td>\n <td style='width:387.0pt; padding:0in 5.4pt 0in 5.4pt; height:15.0pt;' valign='top' width='516'>\n <p style='margin-bottom:0in; margin-bottom:.0001pt;'><span style='color:black;'>Date of inspection</span></p>\n </td>\n </tr>\n <tr style='height:15.0pt;'>\n <td style='width:1.75in; padding:0in 5.4pt 0in 5.4pt; height:15.0pt;' valign='top' width='168'>\n <p style='margin-bottom:0in; margin-bottom:.0001pt;'><span style='color:black;'>Description</span></p>\n </td>\n <td style='width:387.0pt; padding:0in 5.4pt 0in 5.4pt; height:15.0pt;' valign='top' width='516'>\n <p style='margin-bottom:0in; margin-bottom:.0001pt;'><span style='color:black;'>General comments not that may or\n may not be tied to a inspection question</span></p>\n </td>\n </tr>\n <tr style='height:15.0pt;'>\n <td style='width:1.75in; padding:0in 5.4pt 0in 5.4pt; height:15.0pt;' valign='top' width='168'>\n <p style='margin-bottom:0in; margin-bottom:.0001pt;'><span style='color:black;'>Type</span></p>\n </td>\n <td style='width:387.0pt; padding:0in 5.4pt 0in 5.4pt; height:15.0pt;' valign='top' width='516'>\n <p style='margin-bottom:0in; margin-bottom:.0001pt;'><span style='color:black;'>Type of inspection: Inspection, Re-inspection,\n Visit</span></p>\n </td>\n </tr>\n \n <tr style='height:15.0pt;'>\n <td style='width:1.75in; padding:0in 5.4pt 0in 5.4pt; height:15.0pt;' valign='top' width='168'>\n <p style='margin-bottom:0in; margin-bottom:.0001pt;'><span style='color:black;'>PermitID</span></p>\n </td>\n <td style='width:387.0pt; padding:0in 5.4pt 0in 5.4pt; height:15.0pt;' valign='top' width='516'>\n <p style='margin-bottom:0in; margin-bottom:.0001pt;'><span style='color:black;'>Deprecated. No longer provided.</span></p>\n </td>\n </tr>\n</tbody></table>", "distribution": [ { "@type": "dcat:Distribution", - "downloadURL": "https://data.nasa.gov/docs/legacy/ames/2.Battery_Uniform_Distribution_Discharge_Room_Temp_DataSet_2Post.zip", + "accessURL": "https://data-wake.opendata.arcgis.com/api/download/v1/items/ebe3ae7f76954fad81411612d7c4fb17/csv?layers=1", + "format": "CSV", + "mediaType": "text/csv", + "title": "CSV" + }, + { + "@type": "dcat:Distribution", + "accessURL": "https://data-wake.opendata.arcgis.com/api/download/v1/items/ebe3ae7f76954fad81411612d7c4fb17/geojson?layers=1", + "format": "GeoJSON", + "mediaType": "application/vnd.geo+json", + "title": "GeoJSON" + }, + { + "@type": "dcat:Distribution", + "accessURL": "https://data-wake.opendata.arcgis.com/api/download/v1/items/ebe3ae7f76954fad81411612d7c4fb17/kml?layers=1", + "format": "KML", + "mediaType": "application/vnd.google-earth.kml+xml", + "title": "KML" + }, + { + "@type": "dcat:Distribution", + "accessURL": "https://data-wake.opendata.arcgis.com/api/download/v1/items/ebe3ae7f76954fad81411612d7c4fb17/shapefile?layers=1", "format": "ZIP", "mediaType": "application/zip", - "title": "Battery_Uniform_Distribution_Discharge_Room_Temp_DataSet_2Post.zip" + "title": "Shapefile" + }, + { + "@type": "dcat:Distribution", + "accessURL": "https://data-wake.opendata.arcgis.com/datasets/Wake::food-inspections", + "format": "Web Page", + "mediaType": "text/html", + "title": "ArcGIS Hub Dataset" + }, + { + "@type": "dcat:Distribution", + "accessURL": "https://maps.wake.gov/arcgis/rest/services/Inspections/RestaurantInspectionsOpenData/MapServer/1", + "format": "ArcGIS GeoServices REST API", + "mediaType": "application/json", + "title": "ArcGIS GeoService" } ], - "identifier": "https://data.nasa.gov/api/views/qghr-qkfw", - "issued": "2022-10-20", - "keyword": [ - "batteries", - "degradation", - "phm", - "prognostics" - ], - "landingPage": "https://data.nasa.gov/dataset/randomized-battery-usage-2-room-temperature-random-walk", - "license": "https://www.usa.gov/government-works", - "modified": "2025-12-09", - "programCode": [ - "026:021" - ], + "identifier": "https://www.arcgis.com/home/item.html?id=ebe3ae7f76954fad81411612d7c4fb17&sublayer=1", + "issued": "2016-08-12T18:31:22.000Z", + "keyword": [ + "Food Safety", + "Inspections", + "NC", + "North Carolina", + "Permit", + "Restaurants", + "Wake", + "Wake County" + ], + "landingPage": "https://data-wake.opendata.arcgis.com/datasets/Wake::food-inspections", + "license": "https://creativecommons.org/licenses/by/4.0", + "modified": "2026-10-07T04:30:19.000Z", "publisher": { - "@type": "org:Organization", - "name": "PCoE" - }, - "theme": [ - "Raw Data" - ], - "title": "Randomized Battery Usage 2: Room Temperature Random Walk" - }, - "description": "This dataset is part of a series of datasets, where batteries are continuously cycled with randomly generated current profiles. Reference charging and discharging cycles are also performed after a fixed interval of randomized usage to provide reference benchmarks for battery state of health.\n\nIn this dataset, four 18650 Li-ion batteries (Identified as RW3, RW4, RW5 and RW6) were continuously operated by repeatedly charging them to 4.2V and then discharging them to 3.2V using a randomized sequence of discharging currents between 0.5A and 4A. This type of discharging profile is referred to here as random walk (RW) discharging. After every fifty RW cycles a series of reference charging and discharging cycles were performed in order to provide reference benchmarks for battery state health.", + "name": "Wake County" + }, + "spatial": "-78.9451,35.5378,-78.2691,36.0477", + "theme": [ + "geospatial" + ], + "title": "Food Inspections" + }, + "description": "The Wake County health department inspects food service facilities\nthroughout Wake County. The department permits and inspects these facilities,\nand responds to citizen complaints. In the event of disease outbreak, the\ndepartment investigates to determine the source of the infection, and prevent\nfurther illness.\n\n<p>This dataset captures the restaurants that are\ninspected.<span> </span>The data set is geocoded\nbased on address with approximately 85% of the locations having a valid\ngeo-location.<span> </span></p>\n\n<p>You can find out additional information about our restaurant\ninspections on our website:<span> </span><a href='https://www.wake.gov/departments-government/environmental-health-safety' rel='nofollow ugc'>Food Safety and Sanitation</a></p>\n\n<p>This table captures all Wake County sanitation\ninspections from September 20, 2012 to Present.</p><p>\n\n</p><p>This table is part of a set of data that combined will give\nyou a picture of all restaurant inspections.<span> \n</span>Those three tables are:</p>\n\n<p style='margin-bottom:0in; margin-bottom:.0001pt; text-indent:-.25in;'><span style='color:black;'><span>1.<span style='font:7.0pt "Times New Roman";'> </span></span></span><b><span style='color:black;'>Restaurants:\n</span></b><span style='color:black;'>This table captures all active facilities\nwhere Wake County performs sanitations inspections.<span> </span>Facilities that are closed are removed from\nall three files in this dataset.<span> </span>Per NC\nState regulations, facilities that have a change in ownership are considered\nclosed and the restaurant re-opens under a new permit, even if there is not a change\nin the name of the restaurant.</span></p>\n\n<p style='margin-bottom:0in; margin-bottom:.0001pt; text-indent:-.25in;'><span style='color:black;'><span>2.<span style='font:7.0pt "Times New Roman";'> </span></span></span><b><span style='color:black;'>Food Inspections:\n</span></b><span style='color:black;'>This table captures all Wake County\nperforms sanitations inspections at active restaurants since September 20, 2012</span></p>\n\n<p style='margin-bottom:0in; margin-bottom:.0001pt; text-indent:-.25in;'><span style='color:black;'><span>3.<span style='font:7.0pt "Times New Roman";'> </span></span></span><b><span style='color:black;'><span style='color:rgb(76, 76, 76);'>Food Inspection </span>Violations:\n</span></b><span style='color:black;'>This table captures all violations\nidentified during specific Wake County sanitations inspections at active\nrestaurants since September 20, 2012.<span> </span>It\nreports the results in code violations and according to CDC Risk Factors.<span> </span></span>You can find additional information\nabout the CDC Risk Factors on the FDA website: <a href='https://www.fda.gov/food/retail-food-protection/retail-food-risk-factor-study' rel='nofollow ugc'><span style='font-size:10.0pt; font-family:"Helv","sans-serif"; color:blue; text-decoration:none;'>Retail Risk Factor\nStudy</span></a><span style='color:black;'></span></p>\n\n<p> </p>\n\n<p>The tables can be connected through the <span style='color:black;'>HSISID\nfield.<span> </span></span></p>\n\n\n\n<p style='text-indent:-.25in;'><span style='font-family:Symbol;'><span><span style='font:7.0pt "Times New Roman";'></span></span></span>The frequency of facility inspections fall under\nthe following rules:</p>\n\n<p style='margin-left:.5in;'><b><u><span style='font-family:"Calibri","sans-serif";'>Inspected once per year:</span></u></b></p>\n\n<p style='margin-left:.5in;'><b><span style='font-family:"Calibri","sans-serif";'>Risk Category I </span></b><span style='font-family:"Calibri","sans-serif";'>applies to food service\nestablishments that prepare only non-potentially hazardous foods.</span></p><p style='margin-left:.5in;'><b><u><span style='font-family:"Calibri","sans-serif";'>Inspected twice per year:</span></u></b></p>\n\n<p style='margin-left:.5in;'><b><span style='font-family:"Calibri","sans-serif";'>Risk Category II </span></b><span style='font-family:"Calibri","sans-serif";'>applies to food service\nestablishments that cook and cool no more than two potentially hazardous foods.\nPotentially hazardous raw ingredients shall be received in a ready-to-cook\nform.</span></p><p style='margin-left:.5in;'><b><u><span style='font-family:"Calibri","sans-serif";'>Inspected three times per year</span></u></b></p>\n\n<p style='margin-left:.5in;'><b><span style='font-family:"Calibri","sans-serif";'>Risk Category III </span></b><span style='font-family:"Calibri","sans-serif";'>applies to food service\nestablishments that cook and cool no more than three potentially hazardous\nfoods.</span></p><p style='margin-left:.5in;'><b><u><span style='font-family:"Calibri","sans-serif";'>Inspected four times per year</span></u></b></p>\n\n<p style='margin-left:.5in;'><b><span style='font-size:12.0pt;'>Risk Category IV </span></b><span style='font-size:12.0pt;'>applies to\nfood service establishments that cook and cool an unlimited number of\npotentially hazardous foods. This category also includes those facilities using\nspecialized processes or serving a highly susceptible population.</span></p><span style='color:black;'><span><br /></span></span>\n\n<table border='0' cellpadding='0' cellspacing='0' style='width:513.0pt; border-collapse:collapse; margin-left:6.75pt; margin-right:6.75pt;' width='684'>\n <tbody><tr style='height:30.0pt;'>\n <td style='width:1.75in; padding:0in 5.4pt 0in 5.4pt; height:30.0pt;' valign='bottom' width='168'>\n <p style='margin-bottom:0in; margin-bottom:.0001pt;'><b><span style='color:black;'> </span></b></p>\n \n \n <p style='margin-bottom:0in; margin-bottom:.0001pt;'><b><span style='color:black;'>Field</span></b></p>\n </td>\n <td style='width:387.0pt; padding:0in 5.4pt 0in 5.4pt; height:30.0pt;' valign='bottom' width='516'>\n <p style='margin-bottom:0in; margin-bottom:.0001pt;'><b><span style='color:black;'>Description</span></b></p>\n </td>\n </tr>\n <tr style='height:15.0pt;'>\n <td style='width:1.75in; padding:0in 5.4pt 0in 5.4pt; height:15.0pt;' valign='top' width='168'>\n <p style='margin-bottom:0in; margin-bottom:.0001pt;'><span style='color:black;'>HSISID</span></p>\n </td>\n <td style='width:387.0pt; padding:0in 5.4pt 0in 5.4pt; height:15.0pt;' valign='top' width='516'>\n <p style='margin-bottom:0in; margin-bottom:.0001pt;'><span style='color:black;'>State code identifying the\n restaurant (also the primary key to identify the restaurant)</span></p>\n </td>\n </tr>\n <tr style='height:15.0pt;'>\n <td style='width:1.75in; padding:0in 5.4pt 0in 5.4pt; height:15.0pt;' valign='top' width='168'>\n <p style='margin-bottom:0in; margin-bottom:.0001pt;'><span style='color:black;'>Score</span></p>\n </td>\n <td style='width:387.0pt; padding:0in 5.4pt 0in 5.4pt; height:15.0pt;' valign='top' width='516'>\n <p style='margin-bottom:0in; margin-bottom:.0001pt;'><span style='color:black;'>Final score for this inspection</span></p>\n </td>\n </tr>\n <tr style='height:15.0pt;'>\n <td style='width:1.75in; padding:0in 5.4pt 0in 5.4pt; height:15.0pt;' valign='top' width='168'>\n <p style='margin-bottom:0in; margin-bottom:.0001pt;'><span style='color:black;'>Date</span></p>\n </td>\n <td style='width:387.0pt; padding:0in 5.4pt 0in 5.4pt; height:15.0pt;' valign='top' width='516'>\n <p style='margin-bottom:0in; margin-bottom:.0001pt;'><span style='color:black;'>Date of inspection</span></p>\n </td>\n </tr>\n <tr style='height:15.0pt;'>\n <td style='width:1.75in; padding:0in 5.4pt 0in 5.4pt; height:15.0pt;' valign='top' width='168'>\n <p style='margin-bottom:0in; margin-bottom:.0001pt;'><span style='color:black;'>Description</span></p>\n </td>\n <td style='width:387.0pt; padding:0in 5.4pt 0in 5.4pt; height:15.0pt;' valign='top' width='516'>\n <p style='margin-bottom:0in; margin-bottom:.0001pt;'><span style='color:black;'>General comments not that may or\n may not be tied to a inspection question</span></p>\n </td>\n </tr>\n <tr style='height:15.0pt;'>\n <td style='width:1.75in; padding:0in 5.4pt 0in 5.4pt; height:15.0pt;' valign='top' width='168'>\n <p style='margin-bottom:0in; margin-bottom:.0001pt;'><span style='color:black;'>Type</span></p>\n </td>\n <td style='width:387.0pt; padding:0in 5.4pt 0in 5.4pt; height:15.0pt;' valign='top' width='516'>\n <p style='margin-bottom:0in; margin-bottom:.0001pt;'><span style='color:black;'>Type of inspection: Inspection, Re-inspection,\n Visit</span></p>\n </td>\n </tr>\n \n <tr style='height:15.0pt;'>\n <td style='width:1.75in; padding:0in 5.4pt 0in 5.4pt; height:15.0pt;' valign='top' width='168'>\n <p style='margin-bottom:0in; margin-bottom:.0001pt;'><span style='color:black;'>PermitID</span></p>\n </td>\n <td style='width:387.0pt; padding:0in 5.4pt 0in 5.4pt; height:15.0pt;' valign='top' width='516'>\n <p style='margin-bottom:0in; margin-bottom:.0001pt;'><span style='color:black;'>Deprecated. 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No Noise Removal or Despiking has been done, so Caution must be used in interpreting isolated large Increases or Decreases in the measured Parameters.", + "fn": "WakeCountyGovernment", + "hasEmail": "mailto:gisapps@wake.gov" + }, + "description": "<div>The Wake County health department inspects food service facilities throughout Wake County. The department permits and inspects these facilities, and responds to citizen complaints. In the event of disease outbreak, the department investigates to determine the source of the infection, and prevent further illness.</div><p>This dataset captures the restaurants that are inspected.<span> </span>The data set is geocoded based on address with approximately 85% of the locations having a valid geo-location.<span> </span></p><p>You can find out additional information about our restaurant inspections on our website:<span> </span><a target='_blank' href='https://www.wake.gov/departments-government/environmental-health-safety' rel='nofollow ugc noopener noreferrer'>Food Safety and Sanitation</a></p><p>This table captures all Wake County sanitation inspections from September 20, 2012 to Present.</p><p> </p><p>This table is part of a set of data that combined will give you a picture of all restaurant inspections.<span> </span>Those three tables are:</p><p style='margin-bottom:.0001pt; text-indent:-.25in;'><span style='color:black;'><span>1.</span><span style='font:7.0pt "Times New Roman";'> </span><strong>Restaurants: </strong>This table captures all active facilities where Wake County performs sanitations inspections.<span> </span>Facilities that are closed are removed from all three files in this dataset.<span> </span>Per NC State regulations, facilities that have a change in ownership are considered closed and the restaurant re-opens under a new permit, even if there is not a change in the name of the restaurant.</span></p><p style='margin-bottom:.0001pt; text-indent:-.25in;'><span style='color:black;'><span>2.</span><span style='font:7.0pt "Times New Roman";'> </span><strong>Food Inspections: </strong>This table captures all Wake County performs sanitations inspections at active restaurants since September 20, 2012</span></p><p style='margin-bottom:.0001pt; text-indent:-.25in;'><span style='color:black;'><span>3.</span><span style='font:7.0pt "Times New Roman";'> </span></span><span style='color:rgb(76,76,76);'><strong>Food Inspection </strong></span><span style='color:black;'><strong>Violations: </strong>This table captures all violations identified during specific Wake County sanitations inspections at active restaurants since September 20, 2012.<span> </span>It reports the results in code violations and according to CDC Risk Factors.<span> </span></span>You can find additional information about the CDC Risk Factors on the FDA website: <a target='_blank' href='https://www.fda.gov/food/retail-food-protection/retail-food-risk-factor-study' rel='nofollow ugc noopener noreferrer'><span style='color:blue; font-family:"Helv","sans-serif"; font-size:10.0pt;'><span style='text-decoration:none;'>Retail Risk Factor Study</span></span></a></p><p> </p><p>The tables can be connected through the <span style='color:black;'>HSISID field.<span> </span></span></p><p style='text-indent:-.25in;'> The frequency of facility inspections fall under the following rules:</p><p style='margin-left:.5in;'><span style='font-family:"Calibri","sans-serif";'><strong><u>Inspected once per year:</u></strong></span></p><p style='margin-left:.5in;'><span style='font-family:"Calibri","sans-serif";'><strong>Risk Category I </strong>applies to food service establishments that prepare only non-potentially hazardous foods.</span></p><p style='margin-left:.5in;'><span style='font-family:"Calibri","sans-serif";'><strong><u>Inspected twice per year:</u></strong></span></p><p style='margin-left:.5in;'><span style='font-family:"Calibri","sans-serif";'><strong>Risk Category II </strong>applies to food service establishments that cook and cool no more than two potentially hazardous foods. 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In the event of disease outbreak, the department investigates to determine the source of the infection, and prevent further illness.</div><p>This dataset captures the restaurants that are inspected.<span> </span>The data set is geocoded based on address with approximately 85% of the locations having a valid geo-location.<span> </span></p><p>You can find out additional information about our restaurant inspections on our website:<span> </span><a target='_blank' href='https://www.wake.gov/departments-government/environmental-health-safety' rel='nofollow ugc noopener noreferrer'>Food Safety and Sanitation</a></p><p>This table captures all Wake County sanitation inspections from September 20, 2012 to Present.</p><p> </p><p>This table is part of a set of data that combined will give you a picture of all restaurant inspections.<span> </span>Those three tables are:</p><p style='margin-bottom:.0001pt; text-indent:-.25in;'><span style='color:black;'><span>1.</span><span style='font:7.0pt "Times New Roman";'> </span><strong>Restaurants: </strong>This table captures all active facilities where Wake County performs sanitations inspections.<span> </span>Facilities that are closed are removed from all three files in this dataset.<span> </span>Per NC State regulations, facilities that have a change in ownership are considered closed and the restaurant re-opens under a new permit, even if there is not a change in the name of the restaurant.</span></p><p style='margin-bottom:.0001pt; text-indent:-.25in;'><span style='color:black;'><span>2.</span><span style='font:7.0pt "Times New Roman";'> </span><strong>Food Inspections: </strong>This table captures all Wake County performs sanitations inspections at active restaurants since September 20, 2012</span></p><p style='margin-bottom:.0001pt; text-indent:-.25in;'><span style='color:black;'><span>3.</span><span style='font:7.0pt "Times New Roman";'> </span></span><span style='color:rgb(76,76,76);'><strong>Food Inspection </strong></span><span style='color:black;'><strong>Violations: </strong>This table captures all violations identified during specific Wake County sanitations inspections at active restaurants since September 20, 2012.<span> </span>It reports the results in code violations and according to CDC Risk Factors.<span> </span></span>You can find additional information about the CDC Risk Factors on the FDA website: <a target='_blank' href='https://www.fda.gov/food/retail-food-protection/retail-food-risk-factor-study' rel='nofollow ugc noopener noreferrer'><span style='color:blue; font-family:"Helv","sans-serif"; font-size:10.0pt;'><span style='text-decoration:none;'>Retail Risk Factor Study</span></span></a></p><p> </p><p>The tables can be connected through the <span style='color:black;'>HSISID field.<span> </span></span></p><p style='text-indent:-.25in;'> The frequency of facility inspections fall under the following rules:</p><p style='margin-left:.5in;'><span style='font-family:"Calibri","sans-serif";'><strong><u>Inspected once per year:</u></strong></span></p><p style='margin-left:.5in;'><span style='font-family:"Calibri","sans-serif";'><strong>Risk Category I </strong>applies to food service establishments that prepare only non-potentially hazardous foods.</span></p><p style='margin-left:.5in;'><span style='font-family:"Calibri","sans-serif";'><strong><u>Inspected twice per year:</u></strong></span></p><p style='margin-left:.5in;'><span style='font-family:"Calibri","sans-serif";'><strong>Risk Category II </strong>applies to food service establishments that cook and cool no more than two potentially hazardous foods. 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The Start Time for H13a is the Time given as the Start Time for the Line, but (to sufficient accuracy) its Accumulation Period is half the Period given under \"Coverage\". Again, to sufficient accuracy, the Start Time for H13b is the Time given plus half the Accumulation Period, and the Accumulation Period for H13b is half the Period given under \"Coverage\". Each Line contains Data for one single Readout of the Rates H10-H12, H13a, H13b, and H14-H27. All Readouts where at least one of the Rates has a Non-fill Value are included. Where Fill does occur it is indicated by -1. Since the Accumulation Period for each Readout is forced to include an Integral Number of Spacecraft Spins in order to produce pure Spin-Averaged Measurements, the Lengths of the Accumulation Periods vary in a Cyclic Manner as the Period of the Telemetry Cycle beats with the Spacecraft Spin Period. At the most common Science Telemetry Rate, 2048 bps, each Rate in this File is Readout on average once every 128 s, except for H13 which is Readout on average twice in every 128 s. At 2048 bps, the Cycle of Accumulation Periods is 132, 132, 120, 132, 132,, 120, 132, etc., seconds. No Noise Removal or Despiking has been done, so Caution must be used in interpreting isolated large Increases or Decreases in the Counting Rates.", + "fn": "WakeCountyGovernment", + "hasEmail": "mailto:gisapps@wake.gov" + }, + "description": "<p>The Wake County health department inspects food service facilities throughout Wake County. The department permits and inspects these facilities, and responds to citizen complaints. In the event of disease outbreak, the department investigates to determine the source of the infection, and prevent further illness.</p><p>This dataset captures the restaurants that are inspected.<span> </span>The data set is geocoded based on address with approximately 85% of the locations having a valid geo-location.<span> </span></p><p>You can find out additional information about our restaurant inspections on our website:<span> </span><a target='_blank' href='https://www.wake.gov/departments-government/environmental-health-safety' rel='nofollow ugc noopener noreferrer'>Food Safety and Sanitation</a></p><p>This table captures all Wake County sanitation inspections from September 20, 2012 to Present.</p><p> </p><p>This table is part of a set of data that combined will give you a picture of all restaurant inspections.<span> </span>Those three tables are:</p><p style='margin-bottom:.0001pt; text-indent:-.25in;'><span style='color:black;'><span>1.</span><span style='font:7.0pt "Times New Roman";'> </span><strong>Restaurants: </strong>This table captures all active facilities where Wake County performs sanitations inspections.<span> </span>Facilities that are closed are removed from all three files in this dataset.<span> </span>Per NC State regulations, facilities that have a change in ownership are considered closed and the restaurant re-opens under a new permit, even if there is not a change in the name of the restaurant.</span></p><p style='margin-bottom:.0001pt; text-indent:-.25in;'><span style='color:black;'><span>2.</span><span style='font:7.0pt "Times New Roman";'> </span><strong>Food Inspections: </strong>This table captures all Wake County performs sanitations inspections at active restaurants since September 20, 2012</span></p><p style='margin-bottom:.0001pt; text-indent:-.25in;'><span style='color:black;'><span>3.</span><span style='font:7.0pt "Times New Roman";'> </span></span><span style='color:rgb(76,76,76);'><strong>Food Inspection </strong></span><span style='color:black;'><strong>Violations: </strong>This table captures all violations identified during specific Wake County sanitations inspections at active restaurants since September 20, 2012.<span> </span>It reports the results in code violations and according to CDC Risk Factors.<span> </span></span>You can find additional information about the CDC Risk Factors on the FDA website: <a target='_blank' href='https://www.fda.gov/food/retail-food-protection/retail-food-risk-factor-study' rel='nofollow ugc noopener noreferrer'><span style='color:blue; font-family:"Helv","sans-serif"; font-size:10.0pt;'><span style='text-decoration:none;'>Retail Risk Factor Study</span></span></a></p><p> </p><p>The tables can be connected through the <span style='color:black;'>HSISID field.<span> </span></span></p><p style='text-indent:-.25in;'>T The frequency of facility inspections fall under the following rules:</p><p style='margin-left:.5in;'><span style='font-family:"Calibri","sans-serif";'><strong><u>Inspected once per year:</u></strong></span></p><p style='margin-left:.5in;'><span style='font-family:"Calibri","sans-serif";'><strong>Risk Category I </strong>applies to food service establishments that prepare only non-potentially hazardous foods.</span></p><p style='margin-left:.5in;'><span style='font-family:"Calibri","sans-serif";'><strong><u>Inspected twice per year:</u></strong></span></p><p style='margin-left:.5in;'><span style='font-family:"Calibri","sans-serif";'><strong>Risk Category II </strong>applies to food service establishments that cook and cool no more than two potentially hazardous foods. Potentially hazardous raw ingredients shall be received in a ready-to-cook form.</span></p><p style='margin-left:.5in;'><span style='font-family:"Calibri","sans-serif";'><strong><u>Inspected three times per year</u></strong></span></p><p style='margin-left:.5in;'><span style='font-family:"Calibri","sans-serif";'><strong>Risk Category III </strong>applies to food service establishments that cook and cool no more than three potentially hazardous foods.</span></p><p style='margin-left:.5in;'><span style='font-family:"Calibri","sans-serif";'><strong><u>Inspected four times per year</u></strong></span></p><p style='margin-left:.5in;'><span style='font-size:12.0pt;'><strong>Risk Category IV </strong>applies to food service establishments that cook and cool an unlimited number of potentially hazardous foods. This category also includes those facilities using specialized processes or serving a highly susceptible population.</span></p><p style='margin-left:.5in;'> </p><p style='margin-left:.5in;'><span style='font-size:12.0pt;'><strong>Field Descriptions</strong> are available </span><a target='_blank' href='https://maps.wake.gov/metadata/RestaurantsFieldDefinitions.pdf' rel='nofollow ugc noopener noreferrer'><span style='font-size:12.0pt;'>here</span></a>.</p><p style='margin-bottom:.0001pt; text-indent:-.25in;'> </p>", "distribution": [ { "@type": "dcat:Distribution", - "downloadURL": "http://ufa.esac.esa.int/ufa-sl-server/data-action?PROTOCOL=HTTP&PRODUCT_TYPE=ALL&FILE_NAME=ReadMeHETFullRes.doc&FILE_PATH=%2Fufa%2FHiRes%2FCOSPIN%2FHET", - "format": "BIN", - "mediaType": "application/octet-stream" - }, - { - "@type": "dcat:Distribution", - "downloadURL": "http://ufa.esac.esa.int/ufa-sl-server/data-action?PROTOCOL=HTTP&PRODUCT_TYPE=ALL&FILE_NAME=het_usernotes.pdf&FILE_PATH=%2Fufa%2FHiRes%2Fdoc%2Fcospin", - "format": "BIN", - "mediaType": "application/octet-stream" - }, - { - "@type": "dcat:Distribution", - "downloadURL": "http://ufa.esac.esa.int/ufa/#data", - "format": "BIN", - "mediaType": "application/octet-stream" - }, - { - "@type": "dcat:Distribution", - "downloadURL": "http://ufa.esac.esa.int/ufa/#instruments", - "format": "BIN", - "mediaType": "application/octet-stream" - }, - { - "@type": "dcat:Distribution", - "downloadURL": "https://helio.data.nasa.gov/dataset/Ulysses_COSPIN_HET_Rates_Omni2_PT128S", - "format": "BIN", - "mediaType": "application/octet-stream" - }, - { - "@type": "dcat:Distribution", - "downloadURL": "https://hpde.io/NASA/NumericalData/Ulysses/COSPIN/HET/Rates/Omni2/PT128S", - "format": "BIN", - "mediaType": "application/octet-stream" + "accessURL": "https://data-wake.opendata.arcgis.com/api/download/v1/items/124c2187da8c41c59bde04fa67eb2872/csv?layers=0", + "format": "CSV", + "mediaType": "text/csv", + "title": "CSV" + }, + { + "@type": "dcat:Distribution", + "accessURL": "https://data-wake.opendata.arcgis.com/api/download/v1/items/124c2187da8c41c59bde04fa67eb2872/geojson?layers=0", + "format": "GeoJSON", + "mediaType": "application/vnd.geo+json", + "title": "GeoJSON" + }, + { + "@type": "dcat:Distribution", + "accessURL": "https://data-wake.opendata.arcgis.com/api/download/v1/items/124c2187da8c41c59bde04fa67eb2872/kml?layers=0", + "format": "KML", + "mediaType": "application/vnd.google-earth.kml+xml", + "title": "KML" + }, + { + "@type": "dcat:Distribution", + "accessURL": "https://data-wake.opendata.arcgis.com/api/download/v1/items/124c2187da8c41c59bde04fa67eb2872/shapefile?layers=0", + "format": "ZIP", + "mediaType": "application/zip", + "title": "Shapefile" + }, + { + "@type": "dcat:Distribution", + "accessURL": "https://data-wake.opendata.arcgis.com/datasets/Wake::restaurants-in-wake-county", + "format": "Web Page", + "mediaType": "text/html", + "title": "ArcGIS Hub Dataset" + }, + { + "@type": "dcat:Distribution", + "accessURL": "https://maps.wake.gov/arcgis/rest/services/Inspections/RestaurantInspectionsOpenData/MapServer/0", + "format": "ArcGIS GeoServices REST API", + "mediaType": "application/json", + "title": "ArcGIS GeoService" } ], - "identifier": "https://doi.org/10.48322/78qg-8e67", - "keyword": [ - "energeticparticles" - ], - "landingPage": "https://doi.org/10.48322/78qg-8e67", - "license": "https://www.usa.gov/government-works", - "modified": "2026-09-28", - "programCode": [ - "026:000" - ], + "identifier": "https://www.arcgis.com/home/item.html?id=124c2187da8c41c59bde04fa67eb2872&sublayer=0", + "issued": "2016-08-12T18:16:04.000Z", + "keyword": [ + "Food Safety", + "Inspections", + "NC", + "North Carolina", + "Permit", + "Restaurants", + "Wake", + "Wake County" + ], + "landingPage": "https://data-wake.opendata.arcgis.com/datasets/Wake::restaurants-in-wake-county", + "license": "https://creativecommons.org/licenses/by/4.0", + "modified": "2026-10-07T15:59:39.505Z", "publisher": { - "@type": "org:Organization", - "name": "UlyssesFinalArchive" - }, - "theme": [ - "Heliophysics" - ], - "title": "Ulysses Cosmic Ray and Solar Particle Investigation (COSPIN) High Energy Telescope (HET) Full Resolution Heavy Ion Counts and Accumulation Times for Spin-Averaged Coincidence Counting Rates, OMNI2 H10-H27, 128 s Data" - }, - "description": "A Directory containing Daily FTP downloadable Files containing Readout-by-Readout Listings of the Counts accumulated in the H1-H27 Spin-Averaged Counting Rates. 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Potentially hazardous raw ingredients shall be received in a ready-to-cook form.</span></p><p style='margin-left:.5in;'><span style='font-family:"Calibri","sans-serif";'><strong><u>Inspected three times per year</u></strong></span></p><p style='margin-left:.5in;'><span style='font-family:"Calibri","sans-serif";'><strong>Risk Category III </strong>applies to food service establishments that cook and cool no more than three potentially hazardous foods.</span></p><p style='margin-left:.5in;'><span style='font-family:"Calibri","sans-serif";'><strong><u>Inspected four times per year</u></strong></span></p><p style='margin-left:.5in;'><span style='font-size:12.0pt;'><strong>Risk Category IV </strong>applies to food service establishments that cook and cool an unlimited number of potentially hazardous foods. 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