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The water surface elevations therein can be used to describe historical environmental conditions, contextualize contemporary conditions, project future conditions, conduct scientific research on aquatic and floodplain organisms and processes, assess existing and future without-project conditions as required for Upper Mississippi River Restoration Program restoration project, and many other applications. 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The water surface elevations therein can be used to describe historical environmental conditions, contextualize contemporary conditions, project future conditions, conduct scientific research on aquatic and floodplain organisms and processes, assess existing and future without-project conditions as required for Upper Mississippi River Restoration Program restoration project, and many other applications. 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Final models and simulation results were not provided because they result in large file sizes of about 50 Gb in total.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P9O954ZN","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.668d715ed34eb8d205624b2a.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_668d715ed34eb8d205624b2a","keyword":["Buhl","Gooding","Idaho","Land","Middle Snake","North America","Snake River","Twin Falls","USGS:668d715ed34eb8d205624b2a","United States","acoustic doppler current profiling","aerial photography","aquatic biology","aquatic vegetation","bathymetry","biota","ecology","elevation","environment","geoscientificInformation","geospatial analysis","habitat suitability indices","inlandWaters","lidar","location","mathematical modeling","modeling","nuisance species","stream discharge","stream-gage measurement","streamflow","weeds"],"modified":"2026-08-18T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-114.670959, 42.654635, -114.633665, 42.663409","theme":["geospatial"],"title":"Two-dimensional hydraulic model archive: Water quality, hydraulics, and aquatic plant growth in the middle Snake River, southern Idaho"},"description":"This is a child item (component) of the larger data release titled \u201cSupporting data: Water quality, hydraulics, and aquatic plant growth in the middle Snake River, southern Idaho\u201d. 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The attributes for each polygon shapefile describe the characteristics of all source datasets used to generate the topobathymetric dataset.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/4d9d021d-2a49-42a2-ba26-43c181706cd4","harvest_record_raw":"https://catalog.data.gov/harvest_record/4d9d021d-2a49-42a2-ba26-43c181706cd4/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_6a15bbc7b66b012f9f081d89","keyword":["3D Elevation Program","3DEP","Acoustic Sonar","Antelope Island State Park","Ash Meadows National Wildlife Refuge","Bear River Migratory Bird Refuge","Box Elder County","Burns Paiute Indian Colony","California","Carson Lake","Carson Lake Pasture","Carson Sink","Churchill County","DEM","David County","Eagle Lake","Fallon National Wildlife Refuge","Fallon Paiute-Shoshone Reservation","Fish Springs National Wildlife Refuge","Flood Inundation Modeling","Franklin Lake","Fremont\u2013Winema National Forest","Goose Lake","Harney County","Harney Lake","Honey Lake","Honey Lake Wildlife Area","Idaho","Inland Bathymetry","Inyo National Forest","Lake Abert","Lake County","Lassen County","Lassen National Forest","Light Detection and Ranging","Lower Chewaucan Marsh","Malheur Lake","Malheur National Wildlife Refuge","Millard County","Mineral County","Modoc National Forest","Mono County","Mono Lake","Mono Lake Tufa State Natural Reserve","Mud Lake","Nevada","Oregon","Pershing County","Pyramid Lake","Pyramid Lake Paiute Reservation","Reservoir Storage Capacity","Ruby Lake","Ruby Lake National Wildlife Refuge","SLEIWAAs","Saline Lakes Ecosystems Integrated Water Availability Assessment","Salt Lake County","Sevier Lake","Silver Lake","Stillwater National Wildlife Refuge","Summer Lake","Summer Lake Wildlife Area","Susanville Indian Rancheria","TBDEM","Tooele County","U.S. Geological Survey","USGS","USGS:6a15bbc7b66b012f9f081d89","Upper Chewaucan Marsh","Utah","Utah Water Science Center","Walker Lake","Walker River Reservation","Washoe County","Weber County","Winnemucca Lake","Wyoming","XL Ranch Rancheria","aquatic ecosystems","bathymetry","benthic ecosystems","biota","birds","climatologyMeteorologyAtmosphere","digital elevation models","dissolved solids","earth sciences","economy","ecosystem management","ecosystem monitoring","elevation","environment","environmental assessment","geography","geomorphology","geoscientificInformation","geospatial analysis","geospatial datasets","habitat distribution","hydrology","inlandWaters","lake elevation","lidar","limnology","natural resource assessment","salinity","salt budget","salt cycling","shorebird habitat","society","storage capacity","surface area","surface-water level","topobathymetric digital elevation model","topobathymetry","topography","volume","water budget","water depth","water quality","water resource management","water surface elevation","water use","watershed management","wetland ecosystems"],"last_harvested_date":"2026-08-20T00:48:13.485733","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"},"popularity":0,"publisher":"U.S. Geological Survey","slug":"spatial-metadata-in-topobathymetric-elevation-models-and-elevation-area-volume-relationshi","spatial_centroid":{"lat":39.148219999999995,"lon":-117.33627999999999},"spatial_shape":{"coordinates":[[[-120.966,36.2283],[-120.966,43.5281],[-111.8917,43.5281],[-111.8917,36.2283],[-120.966,36.2283]]],"type":"Polygon"},"theme":["geospatial"],"title":"Spatial Metadata, in Topobathymetric Elevation Models and Elevation-Area-Volume Relationships for Selected Lakes in Closed Basins of the Great Basin States","type":"dataset"},{"_score":6.695981,"_sort":[1787186541991,6.695981,5,"ecff340e-3458-4575-be26-e3f864fadaec"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"U.S. Geological Survey, Alaska Science Center","hasEmail":"mailto:gs-ak_asc_datamanagers@usgs.gov"},"description":"This dataset contains fatty acid (FA) data expressed as mass percent of total FA for bearded seals, ringed seals and walrus. This is one of many datasets used in Bromaghin et al. 2016 (https://doi.org/10.1111/2041-210X.12456). These supplemental data were used in computer simulations to compare the bias of several quantitative fatty acid signature analysis (QFASA) estimators and develop recommendations regarding estimator selection.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/F7PR7T2W","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.ASC31.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_ASC31","keyword":["Alaska","Animals/Vertebrates","Arctic","Bearded seal","Bears","Biological informatics","Biota","Carnivores","Chukchi Sea","Coastal ecosystems","Diet composition","Diet estimation","Diets","Environment","Erignathus barbatus","Fatty Acids","Mammals","Marine ecosystems","Marine mammals","Pelagic habitat","Pinniped","Polar bear","Predator-prey","Pusa hispida","QFASA","Quantitative fatty acid signature analysis","Ringed seal","Seals/Sea lions/Walruses","USGS:ASC31","Ursus maritimus","Wildlife"],"modified":"2024-11-30T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-173.0, 65.0, -155.0, 72.0","theme":["geospatial"],"title":"Assessing the Robustness of Quantitative Fatty Acid Signature Analysis to Assumption Violations (Supplementary Data)"},"description":"This dataset contains fatty acid (FA) data expressed as mass percent of total FA for bearded seals, ringed seals and walrus. This is one of many datasets used in Bromaghin et al. 2016 (https://doi.org/10.1111/2041-210X.12456). These supplemental data were used in computer simulations to compare the bias of several quantitative fatty acid signature analysis (QFASA) estimators and develop recommendations regarding estimator selection.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/23e130f3-54b4-457c-a618-2e1eed20bbb2","harvest_record_raw":"https://catalog.data.gov/harvest_record/23e130f3-54b4-457c-a618-2e1eed20bbb2/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_ASC31","keyword":["Alaska","Animals/Vertebrates","Arctic","Bearded seal","Bears","Biological informatics","Biota","Carnivores","Chukchi Sea","Coastal ecosystems","Diet composition","Diet estimation","Diets","Environment","Erignathus barbatus","Fatty Acids","Mammals","Marine ecosystems","Marine mammals","Pelagic habitat","Pinniped","Polar bear","Predator-prey","Pusa hispida","QFASA","Quantitative fatty acid signature analysis","Ringed seal","Seals/Sea lions/Walruses","USGS:ASC31","Ursus maritimus","Wildlife"],"last_harvested_date":"2026-08-20T00:42:21.991995","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"},"popularity":5,"publisher":"U.S. Geological Survey","slug":"assessing-the-robustness-of-quantitative-fatty-acid-signature-analysis-to-assumption-viola","spatial_centroid":{"lat":67.8,"lon":-165.8},"spatial_shape":{"coordinates":[[[-173.0,65.0],[-173.0,72.0],[-155.0,72.0],[-155.0,65.0],[-173.0,65.0]]],"type":"Polygon"},"theme":["geospatial"],"title":"Assessing the Robustness of Quantitative Fatty Acid Signature Analysis to Assumption Violations (Supplementary Data)","type":"dataset"},{"_score":6.8857727,"_sort":[1787186382075,6.8857727,0,"954c6e47-a280-4b9c-8818-314c467c197b"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Marc Pons","hasEmail":"mailto:info@ceg.group"},"description":"This single-band float32 GeoTIFF raster represents a spatially smoothed vulnerability\nindex for sagebrush (Artemisia spp.) ecosystems at the northern extent of the sagebrush\nbiome, spanning the US\u2013Canada border region from north-central Montana into\nsoutheastern Alberta and southwestern Saskatchewan, with smaller portions of Wyoming,\nNorth Dakota, and South Dakota (approximately 46.0\u00b0N to 51.1\u00b0N latitude, 102.0\u00b0W to\n113.3\u00b0W longitude). The area falls primarily within the Northwestern Glaciated Plains\nand Northwestern Great Plains ecoregions (EPA Level III / CEC ecoregion classification),\nwith its western edge reaching the Rocky Mountain Front and Canadian Rockies foothills.\nThis region is the northernmost range of the Greater Sage-Grouse (Centrocercus\nurophasianus), centered on the Milk River and Frenchman River basins, and is sometimes\nreferred to informally as the greater northern sagebrush biome. Vulnerability values\nare continuous and range from 1 (lowest vulnerability) to 8 (highest vulnerability),\nreflecting a composite assessment of exposure, sensitivity, and adaptive capacity of\nsagebrush ecosystems to stressors including climate change, invasive species (e.g.,\ncheatgrass, Bromus tectorum), wildfire, and land conversion. A focal mean filter with\na window size of 10 pixels was applied to the source vulnerability raster. At the\nnative 100 m (nominal, projected-CRS) cell resolution, this window corresponds to a\nnominal 1,000 m ground footprint \u2014 see Positional Accuracy below for a caveat on true\nground distance under this projection. This smoothing reduces local pixel-level noise\nand emphasizes landscape-scale vulnerability patterns. The raster is projected in\nWGS 84 / Pseudo-Mercator (EPSG:3857) \u2014 selected for compatibility with ArcGIS Online\npublishing \u2014 with a datum of WGS84 (not NAD83). Cells with no data are assigned IEEE 754\nNaN (float32).","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P14KPFAL","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.6a3ece3e1ba49b7c2e2634db.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_6a3ece3e1ba49b7c2e2634db","keyword":["Alberta","Artemisia","EPSG:3857","GeoTIFF","Greater Sage-Grouse","Montana","North Dakota","Northern Great Plains","Northern Rocky Mountains","Northwestern Glaciated Plains","Northwestern Great Plains","Saskatchewan","South Dakota","USGS:6a3ece3e1ba49b7c2e2634db","WGS84","Wyoming","biota","cheatgrass","climate change","conservation planning","environment","focal mean smoothing","geoscientificInformation","invasive species","raster","sagebrush","sagebrush steppe","shrubland","vulnerability index","wildfire"],"modified":"2026-08-17T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-113.3097, 45.9977, -101.9756, 51.1180","theme":["geospatial"],"title":"Greater Northern Sagebrush Vulnerability Map"},"description":"This single-band float32 GeoTIFF raster represents a spatially smoothed vulnerability\nindex for sagebrush (Artemisia spp.) ecosystems at the northern extent of the sagebrush\nbiome, spanning the US\u2013Canada border region from north-central Montana into\nsoutheastern Alberta and southwestern Saskatchewan, with smaller portions of Wyoming,\nNorth Dakota, and South Dakota (approximately 46.0\u00b0N to 51.1\u00b0N latitude, 102.0\u00b0W to\n113.3\u00b0W longitude). The area falls primarily within the Northwestern Glaciated Plains\nand Northwestern Great Plains ecoregions (EPA Level III / CEC ecoregion classification),\nwith its western edge reaching the Rocky Mountain Front and Canadian Rockies foothills.\nThis region is the northernmost range of the Greater Sage-Grouse (Centrocercus\nurophasianus), centered on the Milk River and Frenchman River basins, and is sometimes\nreferred to informally as the greater northern sagebrush biome. Vulnerability values\nare continuous and range from 1 (lowest vulnerability) to 8 (highest vulnerability),\nreflecting a composite assessment of exposure, sensitivity, and adaptive capacity of\nsagebrush ecosystems to stressors including climate change, invasive species (e.g.,\ncheatgrass, Bromus tectorum), wildfire, and land conversion. A focal mean filter with\na window size of 10 pixels was applied to the source vulnerability raster. At the\nnative 100 m (nominal, projected-CRS) cell resolution, this window corresponds to a\nnominal 1,000 m ground footprint \u2014 see Positional Accuracy below for a caveat on true\nground distance under this projection. This smoothing reduces local pixel-level noise\nand emphasizes landscape-scale vulnerability patterns. The raster is projected in\nWGS 84 / Pseudo-Mercator (EPSG:3857) \u2014 selected for compatibility with ArcGIS Online\npublishing \u2014 with a datum of WGS84 (not NAD83). Cells with no data are assigned IEEE 754\nNaN (float32).","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/860d182f-b7a2-4d91-9094-ed84f52e0c83","harvest_record_raw":"https://catalog.data.gov/harvest_record/860d182f-b7a2-4d91-9094-ed84f52e0c83/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_6a3ece3e1ba49b7c2e2634db","keyword":["Alberta","Artemisia","EPSG:3857","GeoTIFF","Greater Sage-Grouse","Montana","North Dakota","Northern Great Plains","Northern Rocky Mountains","Northwestern Glaciated Plains","Northwestern Great Plains","Saskatchewan","South Dakota","USGS:6a3ece3e1ba49b7c2e2634db","WGS84","Wyoming","biota","cheatgrass","climate change","conservation planning","environment","focal mean smoothing","geoscientificInformation","invasive species","raster","sagebrush","sagebrush steppe","shrubland","vulnerability index","wildfire"],"last_harvested_date":"2026-08-20T00:39:42.075012","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"},"popularity":0,"publisher":"U.S. Geological Survey","slug":"greater-northern-sagebrush-vulnerability-map","spatial_centroid":{"lat":48.045820000000006,"lon":-108.77606},"spatial_shape":{"coordinates":[[[-113.3097,45.9977],[-113.3097,51.118],[-101.9756,51.118],[-101.9756,45.9977],[-113.3097,45.9977]]],"type":"Polygon"},"theme":["geospatial"],"title":"Greater Northern Sagebrush Vulnerability Map","type":"dataset"},{"_score":2.3939304,"_sort":[1787186351761,2.3939304,0,"5a57a7f7-45a1-48bf-b782-053b9679c038"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Jonathan Casey Root","hasEmail":"mailto:jroot@usgs.gov"},"description":"Terminal and saline lakes across the western United States serve as critical hydrologic, ecologic, and geomorphic resources. This data release provides assimilated topobathymetric elevation models and elevation area volume (EAV) relationships for selected lakes within these terminal basins. The datasets integrate the best available topographic lidar and bathymetric information, including recent high resolution lidar digital elevation models (DEMs) and historical or modern bathymetric surveys, to produce continuous elevation surfaces for each lake. Bathymetric sources include interpolated DEMs derived from historical contour maps as well as more recent echosounder based or lidar supported lakebed surveys. All elevation data were transformed to the North American Vertical Datum of 1988 (NAVD88) and merged at the highest available spatial resolution for each lake domain.\nTopobathymetric rasters were generated in ArcGIS Pro (v. 3.5.5) using consistent horizontal projections within the Universal Transverse Mercator system and processed to ensure seamless topographic transitions between dry and submerged surfaces. In cases where bathymetric coverage did not overlap with lidar, elevation gaps were interpolated using hydrologically consistent void filling models to create continuous topobathymetry. Elevation area volume relationships were computed at 0.1 meter intervals across each modeled lake using the ESRI Storage Capacity tool, with hydrologically conditioned processing for lakes in which natural or manmade barriers form multiple basins that connect only at specific elevations. The uppermost elevation in each EAV table is equal to or above the highest recorded water-surface elevation observed in historical records. These EAV curves provide a quantitative basis for hydrologic modeling, water budget analyses, and ecological assessment within each closed basin.\nThis data release delivers standardized, high\u2011quality elevation datasets and EAV metrics for lakes including Eagle Lake, Goose Lake, Honey Lake, and Mono Lake in California, Carson Lake, Carson Sink, Franklin Lake, Pyramid Lake, Ruby Lake, Winnemucca Lake, and Walker Lake in Nevada, Lake Abert, Harney Lake, Malheur Lake, Mud Lake, Silver Lake, and Summer Lake in Oregon, and Sevier Lake in Utah. Together, these products support improved understanding of lake dynamics, ecosystem management, and hydrogeomorphic change across terminal lake systems of the western United States.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P147WRTT","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.6a107437b66b01c1459c95e0.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_6a107437b66b01c1459c95e0","keyword":["3D Elevation Program","3DEP","Acoustic Sonar","Antelope Island State Park","Ash Meadows National Wildlife Refuge","Bear River Migratory Bird Refuge","Box Elder County","Burns Paiute Indian Colony","California","Carson Lake","Carson Lake Pasture","Carson Sink","Churchill County","DEM","David County","Eagle Lake","Fallon National Wildlife Refuge","Fallon Paiute-Shoshone Reservation","Fish Springs National Wildlife Refuge","Flood Inundation Modeling","Franklin Lake","Fremont\u2013Winema National Forest","Goose Lake","Harney County","Harney Lake","Honey Lake","Honey Lake Wildlife Area","Idaho","Inland Bathymetry","Inyo National Forest","Lake Abert","Lake County","Lassen County","Lassen National Forest","Light Detection and Ranging","Lower Chewaucan Marsh","Malheur Lake","Malheur National Wildlife Refuge","Millard County","Mineral County","Modoc National Forest","Mono County","Mono Lake","Mono Lake Tufa State Natural Reserve","Mud Lake","Nevada","Oregon","Pershing County","Pyramid Lake","Pyramid Lake Paiute Reservation","Reservoir Storage Capacity","Ruby Lake","Ruby Lake National Wildlife Refuge","SLEIWAAs","Saline Lakes Ecosystems Integrated Water Availability Assessment","Salt Lake County","Sevier Lake","Silver Lake","Stillwater National Wildlife Refuge","Summer Lake","Summer Lake Wildlife Area","Susanville Indian Rancheria","TBDEM","Tooele County","U.S. Geological Survey","USGS","USGS:6a107437b66b01c1459c95e0","Upper Chewaucan Marsh","Utah","Utah Water Science Center","Walker Lake","Walker River Reservation","Washoe County","Weber County","Winnemucca Lake","Wyoming","XL Ranch Rancheria","aquatic ecosystems","bathymetry","benthic ecosystems","biota","birds","climatologyMeteorologyAtmosphere","digital elevation models","dissolved solids","earth sciences","economy","ecosystem management","ecosystem monitoring","elevation","environment","environmental assessment","geography","geomorphology","geoscientificInformation","geospatial analysis","geospatial datasets","habitat distribution","hydrology","inlandWaters","lake elevation","lidar","limnology","natural resource assessment","salinity","salt budget","salt cycling","shorebird habitat","society","storage capacity","surface area","surface-water level","topobathymetric digital elevation model","topobathymetry","topography","volume","water budget","water depth","water quality","water resource management","water surface elevation","water use","watershed management","wetland ecosystems"],"modified":"2026-08-17T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-120.9660, 36.2283, -111.8917, 43.5281","theme":["geospatial"],"title":"Topobathymetric Elevation Models and Elevation-Area-Volume Relationships for Selected Lakes in Closed Basins of the Great Basin States"},"description":"Terminal and saline lakes across the western United States serve as critical hydrologic, ecologic, and geomorphic resources. This data release provides assimilated topobathymetric elevation models and elevation area volume (EAV) relationships for selected lakes within these terminal basins. The datasets integrate the best available topographic lidar and bathymetric information, including recent high resolution lidar digital elevation models (DEMs) and historical or modern bathymetric surveys, to produce continuous elevation surfaces for each lake. Bathymetric sources include interpolated DEMs derived from historical contour maps as well as more recent echosounder based or lidar supported lakebed surveys. All elevation data were transformed to the North American Vertical Datum of 1988 (NAVD88) and merged at the highest available spatial resolution for each lake domain.\nTopobathymetric rasters were generated in ArcGIS Pro (v. 3.5.5) using consistent horizontal projections within the Universal Transverse Mercator system and processed to ensure seamless topographic transitions between dry and submerged surfaces. In cases where bathymetric coverage did not overlap with lidar, elevation gaps were interpolated using hydrologically consistent void filling models to create continuous topobathymetry. Elevation area volume relationships were computed at 0.1 meter intervals across each modeled lake using the ESRI Storage Capacity tool, with hydrologically conditioned processing for lakes in which natural or manmade barriers form multiple basins that connect only at specific elevations. The uppermost elevation in each EAV table is equal to or above the highest recorded water-surface elevation observed in historical records. These EAV curves provide a quantitative basis for hydrologic modeling, water budget analyses, and ecological assessment within each closed basin.\nThis data release delivers standardized, high\u2011quality elevation datasets and EAV metrics for lakes including Eagle Lake, Goose Lake, Honey Lake, and Mono Lake in California, Carson Lake, Carson Sink, Franklin Lake, Pyramid Lake, Ruby Lake, Winnemucca Lake, and Walker Lake in Nevada, Lake Abert, Harney Lake, Malheur Lake, Mud Lake, Silver Lake, and Summer Lake in Oregon, and Sevier Lake in Utah. 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Results from these analyses demonstrated that, in many instances, drinking water is an exposure pathway for multiple contaminants of concern (exposures greater than the federal and state drinking water health-based guidelines) in private, public, and bottled water sources. In addition to targeted chemical analyses, in vitro bioactivity analyses were performed to help characterize the potential biological effects from multiple contaminants.\nFrom 2016-2020, 265 water-quality samples, including 21 quality-assurance field blanks, which had previously been extracted from 1-liter samples were sent to Attagene, Inc., Morrisville, North Carolina for in vitro bioactivity screening. These extracts were analyzed for 48 biological endpoints using the cis-factorial assay described in Romanov and others (2008). Detailed method information and further analysis can be found in the associated report Bradley and others (2026).\nReferences--\nBradley, P.M., Romanok, K.M., Smalling, K.L., Gordon, S.E., Huffman, B.J., Friedman, K.P., Villeneuve, D.L., Blackwell, B.R., Fitzpatrick, S.C., Focazio, M.J., Medlock-Kakaley, E., Meppelink, S.M., Navas-Acien, A., Nigra, A.E., and Schreiner, M.L., 2025, Private, public, and bottled drinking water: Shared contaminant-mixture exposures and effects challenge: Environmental International, v. 195, 18 p., accessed on April 29, 2020 2026, at https://doi.org/10.1016/j.envint.2024.109220.\nRomanov, S., Medvedev, A., Gambarian, M., Poltoratskaya, N., Moeser, M., Medvedeva, L., Gambarian, M., Diatchenko, L., and Makarov, S., 2008, Homogeneous reporter system enables quantitative functional assessment of multiple transcription factors: Nature Methods, v. 5, p. 253-60, accessed on April 28, 2026 at https://doi.org/10.1038/nmeth.1186.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P13HST8C","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.69f2398cb66b010e8bec5c39.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_69f2398cb66b010e8bec5c39","keyword":["Attagene","USGS:69f2398cb66b010e8bec5c39","biota","bottled water","cis-Factorial endpoints","dissolved contaminants","drinking water","environment","environmental health (human)","geoscientificInformation","health","in vitro bioassay","inlandWaters","private wells","public supply","tapwater"],"modified":"2026-08-17T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-126.3867, 17.4764, -64.6875, 49.3824","theme":["geospatial"],"title":"In vitro bioactivity results analyzed in private, public, and bottled drinking-water samples, 2016-20."},"description":"Beginning in 2016, the U.S. Geological Survey, Environmental Health Program, Drinking Water and Wastewater Infrastructure Integrated Science Team, in collaboration with other federal, non-governmental and Tribal partners, began collecting and analyzing tapwater samples from across the Nation for a large suite of inorganic, organic, and biological contaminants (Bradley and others, 2025). Results from these analyses demonstrated that, in many instances, drinking water is an exposure pathway for multiple contaminants of concern (exposures greater than the federal and state drinking water health-based guidelines) in private, public, and bottled water sources. In addition to targeted chemical analyses, in vitro bioactivity analyses were performed to help characterize the potential biological effects from multiple contaminants.\nFrom 2016-2020, 265 water-quality samples, including 21 quality-assurance field blanks, which had previously been extracted from 1-liter samples were sent to Attagene, Inc., Morrisville, North Carolina for in vitro bioactivity screening. These extracts were analyzed for 48 biological endpoints using the cis-factorial assay described in Romanov and others (2008). Detailed method information and further analysis can be found in the associated report Bradley and others (2026).\nReferences--\nBradley, P.M., Romanok, K.M., Smalling, K.L., Gordon, S.E., Huffman, B.J., Friedman, K.P., Villeneuve, D.L., Blackwell, B.R., Fitzpatrick, S.C., Focazio, M.J., Medlock-Kakaley, E., Meppelink, S.M., Navas-Acien, A., Nigra, A.E., and Schreiner, M.L., 2025, Private, public, and bottled drinking water: Shared contaminant-mixture exposures and effects challenge: Environmental International, v. 195, 18 p., accessed on April 29, 2020 2026, at https://doi.org/10.1016/j.envint.2024.109220.\nRomanov, S., Medvedev, A., Gambarian, M., Poltoratskaya, N., Moeser, M., Medvedeva, L., Gambarian, M., Diatchenko, L., and Makarov, S., 2008, Homogeneous reporter system enables quantitative functional assessment of multiple transcription factors: Nature Methods, v. 5, p. 253-60, accessed on April 28, 2026 at https://doi.org/10.1038/nmeth.1186.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/9cb7b4f2-47e6-4bf6-aeaa-eaffadd54825","harvest_record_raw":"https://catalog.data.gov/harvest_record/9cb7b4f2-47e6-4bf6-aeaa-eaffadd54825/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_69f2398cb66b010e8bec5c39","keyword":["Attagene","USGS:69f2398cb66b010e8bec5c39","biota","bottled water","cis-Factorial endpoints","dissolved contaminants","drinking water","environment","environmental health (human)","geoscientificInformation","health","in vitro bioassay","inlandWaters","private wells","public supply","tapwater"],"last_harvested_date":"2026-08-20T00:35:34.524528","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"},"popularity":0,"publisher":"U.S. Geological Survey","slug":"in-vitro-bioactivity-results-analyzed-in-private-public-and-bottled-drinking-water-2016-20","spatial_centroid":{"lat":30.238799999999998,"lon":-101.70702},"spatial_shape":{"coordinates":[[[-126.3867,17.4764],[-126.3867,49.3824],[-64.6875,49.3824],[-64.6875,17.4764],[-126.3867,17.4764]]],"type":"Polygon"},"theme":["geospatial"],"title":"In vitro bioactivity results analyzed in private, public, and bottled drinking-water samples, 2016-20.","type":"dataset"},{"_score":2.4142075,"_sort":[1787186000579,2.4142075,0,"7d3cc5ec-c983-4eb2-bb28-ffaef006eec4"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Jonathan Casey Root","hasEmail":"mailto:jroot@usgs.gov"},"description":"Terminal and saline lakes across the western United States serve as critical hydrologic, ecologic, and geomorphic resources. 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All elevation data were transformed to the North American Vertical Datum of 1988 (NAVD88) and merged at the highest available spatial resolution for each lake domain.\nTopobathymetric rasters were generated in ArcGIS Pro (v. 3.5.5) using consistent horizontal projections within the Universal Transverse Mercator system and processed to ensure seamless topographic transitions between dry and submerged surfaces. In cases where bathymetric coverage did not overlap with lidar, elevation gaps were interpolated using hydrologically consistent void filling models to create continuous topobathymetry. Elevation area volume relationships were computed at 0.1 meter intervals across each modeled lake using the ESRI Storage Capacity tool, with hydrologically conditioned processing for lakes in which natural or manmade barriers form multiple basins that connect only at specific elevations. The uppermost elevation in each EAV table is equal to or above the highest recorded water-surface elevation observed in historical records. These EAV curves provide a quantitative basis for hydrologic modeling, water budget analyses, and ecological assessment within each closed basin.\nThis data release delivers standardized, high\u2011quality elevation datasets and EAV metrics for lakes including Eagle Lake, Goose Lake, Honey Lake, and Mono Lake in California, Carson Lake, Carson Sink, Franklin Lake, Pyramid Lake, Ruby Lake, Winnemucca Lake, and Walker Lake in Nevada, Lake Abert, Harney Lake, Malheur Lake, Mud Lake, Silver Lake, and Summer Lake in Oregon, and Sevier Lake in Utah. Together, these products support improved understanding of lake dynamics, ecosystem management, and hydrogeomorphic change across terminal lake systems of the western United States.\nThis section of the data release includes tables in the format of comma-separated value (CSV) files with elevation-area-volume relationships for selected lakes in closed basins of the Great Basin States. 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The uppermost elevation in each EAV table is equal to or above the highest recorded water-surface elevation observed in historical records. These EAV curves provide a quantitative basis for hydrologic modeling, water budget analyses, and ecological assessment within each closed basin.\nThis data release delivers standardized, high\u2011quality elevation datasets and EAV metrics for lakes including Eagle Lake, Goose Lake, Honey Lake, and Mono Lake in California, Carson Lake, Carson Sink, Franklin Lake, Pyramid Lake, Ruby Lake, Winnemucca Lake, and Walker Lake in Nevada, Lake Abert, Harney Lake, Malheur Lake, Mud Lake, Silver Lake, and Summer Lake in Oregon, and Sevier Lake in Utah. 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These data are from a replicated BACI (before-after-control-impact) designed study, at two marshes with differing hydrology and geomorphology. Data were collected using HOBO Water Level Data Loggers (U20L-04) deployed below the marsh surface between May and October (full duration of deployment varies by year). Data were collected every 15-minutes and filtered to generate a minimum daily water level. 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This analysis involved several steps. First, time-series climate data were compiled and plotted to identify drought periods. Similarly, time-series data representing insect outbreaks were compiled and plotted to identify trends in insect mortality. The study area was classified into forest canopy types using existing modeled estimates of tree basal area by tree species. Using remotely-sensed Normalized Difference Moisture Index (NDMI) from the Landsat archive, NDMI anomalies from reference conditions were calculated in 2001 and 2009. Based on these anomalies, and using the forest classification map, refugia from drought (in 2001) and combined drought-MPB effects (in 2009) were identified as NDMI anomalies greater than the 90\\u003Csup\\u003Eth\\u003C/sup\\u003E-percentile value within each forest type. Once refugia had been identified, landscape variables (topographic, soil, and forest stand characteristics) were compiled and used to model the landscape controls on refugia locations using Boosted Regression Tree (BRT) modeling, a machine-learning algorithm. For detailed descriptions of data-release components, please consult the appropriate metadata documents that accompany the processing scripts and data products.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/F74Q7SWX","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.59637fdbe4b0d1f9f059d824.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_59637fdbe4b0d1f9f059d824","keyword":["USGS:59637fdbe4b0d1f9f059d824","biota","elevation","environment","geoscientificInformation"],"modified":"2026-08-17T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-120.908504664726, 42.46096497075, -120.768520709553, 42.5920986015813","theme":["geospatial"],"title":"Analysis of remotely-sensed vegetation conditions during droughts and a mountain pine beetle outbreak, Gearhart Mountain Wilderness, Oregon"},"description":"This data release includes data-processing scripts, data products, and associated metadata for a remote-sensing based approach to characterize vegetation conditions within a dry, mixed conifer forest study area in southern Oregon in 2001 (a single year drought without any widespread insect mortality) and 2009 (during a multi-year drought that coincided with a severe outbreak of mountain pine beetle; MPB). This analysis involved several steps. First, time-series climate data were compiled and plotted to identify drought periods. Similarly, time-series data representing insect outbreaks were compiled and plotted to identify trends in insect mortality. The study area was classified into forest canopy types using existing modeled estimates of tree basal area by tree species. Using remotely-sensed Normalized Difference Moisture Index (NDMI) from the Landsat archive, NDMI anomalies from reference conditions were calculated in 2001 and 2009. Based on these anomalies, and using the forest classification map, refugia from drought (in 2001) and combined drought-MPB effects (in 2009) were identified as NDMI anomalies greater than the 90\\u003Csup\\u003Eth\\u003C/sup\\u003E-percentile value within each forest type. Once refugia had been identified, landscape variables (topographic, soil, and forest stand characteristics) were compiled and used to model the landscape controls on refugia locations using Boosted Regression Tree (BRT) modeling, a machine-learning algorithm. 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All elevation data were transformed to the North American Vertical Datum of 1988 (NAVD88) and merged at the highest available spatial resolution for each lake domain.\nTopobathymetric rasters were generated in ArcGIS Pro (v. 3.5.5) using consistent horizontal projections within the Universal Transverse Mercator system and processed to ensure seamless topographic transitions between dry and submerged surfaces. In cases where bathymetric coverage did not overlap with lidar, elevation gaps were interpolated using hydrologically consistent void filling models to create continuous topobathymetry. Elevation area volume relationships were computed at 0.1 meter intervals across each modeled lake using the ESRI Storage Capacity tool, with hydrologically conditioned processing for lakes in which natural or manmade barriers form multiple basins that connect only at specific elevations. The uppermost elevation in each EAV table is equal to or above the highest recorded water-surface elevation observed in historical records. These EAV curves provide a quantitative basis for hydrologic modeling, water budget analyses, and ecological assessment within each closed basin.\nThis data release delivers standardized, high\u2011quality elevation datasets and EAV metrics for lakes including Eagle Lake, Goose Lake, Honey Lake, and Mono Lake in California, Carson Lake, Carson Sink, Franklin Lake, Pyramid Lake, Ruby Lake, Winnemucca Lake, and Walker Lake in Nevada, Lake Abert, Harney Lake, Malheur Lake, Mud Lake, Silver Lake, and Summer Lake in Oregon, and Sevier Lake in Utah. Together, these products support improved understanding of lake dynamics, ecosystem management, and hydrogeomorphic change across terminal lake systems of the western United States.\nThis section of the data releases includes high-resolution topobathymetric elevation data for selected lakes in closed basins of the Great Basin States. 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All elevation data were transformed to the North American Vertical Datum of 1988 (NAVD88) and merged at the highest available spatial resolution for each lake domain.\nTopobathymetric rasters were generated in ArcGIS Pro (v. 3.5.5) using consistent horizontal projections within the Universal Transverse Mercator system and processed to ensure seamless topographic transitions between dry and submerged surfaces. In cases where bathymetric coverage did not overlap with lidar, elevation gaps were interpolated using hydrologically consistent void filling models to create continuous topobathymetry. Elevation area volume relationships were computed at 0.1 meter intervals across each modeled lake using the ESRI Storage Capacity tool, with hydrologically conditioned processing for lakes in which natural or manmade barriers form multiple basins that connect only at specific elevations. 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We compared them against mice living in standard conditions (Vivarium Ground Control) and mice living in an environment matched to ISS conditions (Habitat Ground Control). 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Non-coding RNAs like miRNAs are key to regulating this landscape. We thus analyzed 686 small RNA samples of mice from 13 solid organs at 3 and 8 months of age, after at least 3 weeks on the ISS and compared them to earth-bound controls. We observed significant spaceflight effects in systemic tissue remodeling pathways along the Fat-Liver-Pancreas axis and in heart, brain, spleen and thymus. The MIR-17/92 and MIR-1/133 families drive distinct molecular changes through specific gene targeting. Age-dependent changes, smaller in magnitude compared to age-independent changes, primarily involved tissue remodeling through MIR-8, MIR-154 and MIR-15 families in MAT, pancreas, and diaphragm. Our findings provide evidence on how spaceflight regulates mammalian gene expression in preparation for interplanetary spaceflight. We sequenced 686 samples across 13 organs of young (3 months) and middle-aged (8 months) mice that were sent to the ISS (Flight). We compared them against mice living in standard conditions (Vivarium Ground Control) and mice living in an environment matched to ISS conditions (Habitat Ground Control). We euthanized mice at two time-points (matching timelines for controls and flight mice), one before returning to earth (TERM) and one after (LAR) in order to distinguish spaceflight-induced effects from the reentry-induced stress.","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/f95ce988-ba95-443b-bb71-17ea1261ebf4","harvest_record_raw":"https://catalog.data.gov/harvest_record/f95ce988-ba95-443b-bb71-17ea1261ebf4/raw","has_download":true,"has_spatial":false,"identifier":"10.26030/bnfb-5953","keyword":["biological-and-physical-sciences","genelab","nasa"],"last_harvested_date":"2026-08-19T00:47:39.869294","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"},"popularity":0,"publisher":"Open Science Data Repository","slug":"micrornas-shape-mouse-age-independent-tissue-adaptation-to-spaceflight-via-ecm-and-develop-5a902","spatial_centroid":null,"spatial_shape":null,"theme":["Biological and Physical Sciences"],"title":"MicroRNAs shape mouse age-independent tissue adaptation to spaceflight via ECM and developmental pathways - Pancreas data","type":"dataset"},{"_score":14.9703045,"_sort":[1787100454737,14.9703045,2,"f540ded7-c45d-4af2-b606-89069f27ff50"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Open Science Data Repository Help Desk","hasEmail":"mailto:arc-dl-osdr-help@mail.nasa.gov"},"description":"Translating fundamental biological discoveries from NASA Space Biology program into health risk from space flights has been an ongoing challenge. We propose to use NASA GeneLab database to gain new knowledge on potential systemic responses to space. Unbiased systems biology analysis of transcriptomic data from seven different rodent datasets reveals for the first time the existence of potential 'master regulators' coordinating a systemic response to microgravity and/or space radiation with TGF-\u03b21 being the most common regulator. We hypothesized the space environment leads to the release of biomolecules circulating inside the blood stream. Through datamining we identified 13 candidate microRNAs (miRNA) which are common in all studies and directly interact with TGF-\u03b21 that can be potential circulating factors impacting space biology. This study exemplifies the utility of the GeneLab data repository to aid in the process of performing novel hypothesis-based research.","distribution":[{"@type":"dcat:Distribution","downloadURL":"http://purl.bioontology.org/ontology/NCBITAXON/10116","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://lsda.jsc.nasa.gov/Experiment/exper/30","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://osdr.nasa.gov/bio/repo/data/missions/STS-40","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://osdr.nasa.gov/bio/repo/data/studies/OSD-422","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.26030/jq04-0n51","keyword":["biological-and-physical-sciences","genelab","nasa"],"license":"https://www.usa.gov/government-works","modified":"2026-08-10","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"Open Science Data Repository"},"theme":["Biological and Physical Sciences"],"title":"Rodent Research-1 (RR1) NASA Validation Flight: Mouse liver transcriptomic, proteomic, epigenomic and histology data"},"description":"Translating fundamental biological discoveries from NASA Space Biology program into health risk from space flights has been an ongoing challenge. We propose to use NASA GeneLab database to gain new knowledge on potential systemic responses to space. Unbiased systems biology analysis of transcriptomic data from seven different rodent datasets reveals for the first time the existence of potential 'master regulators' coordinating a systemic response to microgravity and/or space radiation with TGF-\u03b21 being the most common regulator. We hypothesized the space environment leads to the release of biomolecules circulating inside the blood stream. Through datamining we identified 13 candidate microRNAs (miRNA) which are common in all studies and directly interact with TGF-\u03b21 that can be potential circulating factors impacting space biology. This study exemplifies the utility of the GeneLab data repository to aid in the process of performing novel hypothesis-based research.","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/01123c39-0983-4dd0-a053-e5c88fce877e","harvest_record_raw":"https://catalog.data.gov/harvest_record/01123c39-0983-4dd0-a053-e5c88fce877e/raw","has_download":true,"has_spatial":false,"identifier":"10.26030/jq04-0n51","keyword":["biological-and-physical-sciences","genelab","nasa"],"last_harvested_date":"2026-08-19T00:47:34.737955","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"},"popularity":2,"publisher":"Open Science Data Repository","slug":"rodent-research-1-rr1-nasa-validation-flight-mouse-liver-transcriptomic-proteomic-epigenom","spatial_centroid":null,"spatial_shape":null,"theme":["Biological and Physical Sciences"],"title":"Rodent Research-1 (RR1) NASA Validation Flight: Mouse liver transcriptomic, proteomic, epigenomic and histology data","type":"dataset"},{"_score":14.160965,"_sort":[1787100443301,14.160965,4,"61da5e7b-f47a-469e-8a2f-575ff8764053"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Open Science Data Repository Help Desk","hasEmail":"mailto:arc-dl-osdr-help@mail.nasa.gov"},"description":"Suborbital spaceflights now enable human-tended research investigating short-term gravitational effects in biological systems, eliminating the need for complex automation. Here, we discuss a method utilizing KSC Fixation Tubes (KFTs) to both carry biology to suborbital space as well as fix that biology at certain stages of flight. Plants on support media were inserted into the sample side of KFTs preloaded with RNAlater in the fixation chamber. The KFTs were activated at various stages of a simulated flight to fix the plants. RNA-seq analysis conducted on tissue samples housed in KFTs, showed that plants behaved consistently in KFTs when compared to petri-plates. Over the time course, roots adjusted to hypoxia and leaves adjusted to changes in photosynthesis. These responses were due in part to the environment imposed by the encased triple containment of the KFTs, which is a requirement for flight in human spacecraft. While plants exhibited expected reproducible transcriptomic alteration over time in the KFTs, responses to clinorotation during the simulated flight suggest that transcriptomic responses to suborbital spaceflight can be examined using this approach.","distribution":[{"@type":"dcat:Distribution","downloadURL":"http://purl.bioontology.org/ontology/NCBITAXON/162425","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://lsda.jsc.nasa.gov/Experiment/exper/13671#data","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://lsda.jsc.nasa.gov/Mission/miss/1391","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://osdr.nasa.gov/bio/repo/data/studies/OSD-233","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.ncbi.nlm.nih.gov/bioproject/PRJNA486827","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.26030/3he5-md28","keyword":["biological-and-physical-sciences","genelab","nasa"],"license":"https://www.usa.gov/government-works","modified":"2026-08-10","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"Open Science Data Repository"},"theme":["Biological and Physical Sciences"],"title":"Utilizing the KSC Fixation Tube to Conduct Human-Tended Plant Biology Experiments on a Suborbital Spaceflight"},"description":"Suborbital spaceflights now enable human-tended research investigating short-term gravitational effects in biological systems, eliminating the need for complex automation. Here, we discuss a method utilizing KSC Fixation Tubes (KFTs) to both carry biology to suborbital space as well as fix that biology at certain stages of flight. Plants on support media were inserted into the sample side of KFTs preloaded with RNAlater in the fixation chamber. The KFTs were activated at various stages of a simulated flight to fix the plants. RNA-seq analysis conducted on tissue samples housed in KFTs, showed that plants behaved consistently in KFTs when compared to petri-plates. Over the time course, roots adjusted to hypoxia and leaves adjusted to changes in photosynthesis. These responses were due in part to the environment imposed by the encased triple containment of the KFTs, which is a requirement for flight in human spacecraft. While plants exhibited expected reproducible transcriptomic alteration over time in the KFTs, responses to clinorotation during the simulated flight suggest that transcriptomic responses to suborbital spaceflight can be examined using this approach.","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/7f0f1e66-d301-49a6-9084-8f874376004d","harvest_record_raw":"https://catalog.data.gov/harvest_record/7f0f1e66-d301-49a6-9084-8f874376004d/raw","has_download":true,"has_spatial":false,"identifier":"10.26030/3he5-md28","keyword":["biological-and-physical-sciences","genelab","nasa"],"last_harvested_date":"2026-08-19T00:47:23.301196","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"},"popularity":4,"publisher":"Open Science Data Repository","slug":"utilizing-the-ksc-fixation-tube-to-conduct-human-tended-plant-biology-experiments-on-a-sub","spatial_centroid":null,"spatial_shape":null,"theme":["Biological and Physical Sciences"],"title":"Utilizing the KSC Fixation Tube to Conduct Human-Tended Plant Biology Experiments on a Suborbital Spaceflight","type":"dataset"},{"_score":8.4127865,"_sort":[1787100438120,8.4127865,4,"50f50334-586e-4572-826a-42f520d9b2a0"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Open Science Data Repository Help Desk","hasEmail":"mailto:arc-dl-osdr-help@mail.nasa.gov"},"description":"The wild type WS plants and the Sku5 mutant plants in the WS background were germinated on ISS or on the ground and the gene expression profiles in roots at 4 days or 8 days were established. The Sku5 gene (AT4G12420) codes for a multi-copper oxidase-like protein SKU5 protein that is involved in directed root tip growth. The Sku5 protein is glycosylated, GPI-anchored and localizes to the plasma membrane and the cell wall. The Sku5 gene is expressed most strongly in expanding tissues. The development of WS and Sku5 plants on orbit differs from that on the ground as demonstrated by the comparison of the gene expression profiles between 4 days old to 8 days old plant in the two environments. However the development of Sku5 mutant plants also differs from WS at either age and in either environment, suggesting the role of the genetic background in these developmental decisions. The 4 days old Sku5 roots in orbit engaged substantially more genes than the 4 days old WS roots in orbit but also more than the 4 days old Sku5 roots on the ground. Overall the 4 days old roots differentially expressed more genes in spaceflight relative to ground than the 8 days old roots of either genotype. Finally, the 4 days old Sku5 roots in orbit differ in 862 genes from the 8 days Sku5 roots in orbit while on the ground there is merely half of the number of genes differentially expressed between the 4 days and 8 days developmental stages of the Sku5 roots. APEX03-2 (Advanced Plant Experiment 03-2) also identified as TAGES-Isa (Transgenic Arabidopsis Gene Expression System\u2014Intracellular Signaling Architecture) was launched on SpaceX mission CRS-5 on 10 January 2015. Dry, sterilized Arabidopsis seeds were planted aseptically on the surface of 10-cm2 solid media plates and remained dormant until removed from cold stowage and exposed to light at the initiation of the experiment on the ISS (International Space Station). The plates were grown in the Vegetable Production System (VPS/Veggie) hardware on the Columbus Module of the ISS with the overhead LED lighting of the VPS. At four or for the second experimental set at eight days, seedlings were harvested by an astronaut into KFT (Kennedy Fixation Tube) containing RNAlater solutions. Upon return to Earth, the harvested material was used to compare the transcriptomes of each genotype and each age using RNAseq technology. The patterns of gene expression was compared between treatments (spaceflight versus ground control) within each genotype of same age or between two ages within same genotype and within same treatment. For 4 day old roots 5-8 roots were combined to serve as one biological replica. For 8 day old roots 2-3 roots were used to form one biological replica. In each case the four biological replicas were used for the transcriptomic analysis.","distribution":[{"@type":"dcat:Distribution","downloadURL":"http://purl.bioontology.org/ontology/NCBITAXON/3702","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://osdr.nasa.gov/bio/repo/data/missions/SpaceX-5","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://osdr.nasa.gov/bio/repo/data/studies/OSD-281","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE95620","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.26030/j07k-nm86","keyword":["biological-and-physical-sciences","genelab","nasa"],"license":"https://www.usa.gov/government-works","modified":"2026-08-10","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"Open Science Data Repository"},"theme":["Biological and Physical Sciences"],"title":"During development, the Sku5 mutant roots engage different genes than wild type WS roots, either on the ground or in spaceflight."},"description":"The wild type WS plants and the Sku5 mutant plants in the WS background were germinated on ISS or on the ground and the gene expression profiles in roots at 4 days or 8 days were established. The Sku5 gene (AT4G12420) codes for a multi-copper oxidase-like protein SKU5 protein that is involved in directed root tip growth. The Sku5 protein is glycosylated, GPI-anchored and localizes to the plasma membrane and the cell wall. The Sku5 gene is expressed most strongly in expanding tissues. The development of WS and Sku5 plants on orbit differs from that on the ground as demonstrated by the comparison of the gene expression profiles between 4 days old to 8 days old plant in the two environments. However the development of Sku5 mutant plants also differs from WS at either age and in either environment, suggesting the role of the genetic background in these developmental decisions. The 4 days old Sku5 roots in orbit engaged substantially more genes than the 4 days old WS roots in orbit but also more than the 4 days old Sku5 roots on the ground. Overall the 4 days old roots differentially expressed more genes in spaceflight relative to ground than the 8 days old roots of either genotype. Finally, the 4 days old Sku5 roots in orbit differ in 862 genes from the 8 days Sku5 roots in orbit while on the ground there is merely half of the number of genes differentially expressed between the 4 days and 8 days developmental stages of the Sku5 roots. APEX03-2 (Advanced Plant Experiment 03-2) also identified as TAGES-Isa (Transgenic Arabidopsis Gene Expression System\u2014Intracellular Signaling Architecture) was launched on SpaceX mission CRS-5 on 10 January 2015. Dry, sterilized Arabidopsis seeds were planted aseptically on the surface of 10-cm2 solid media plates and remained dormant until removed from cold stowage and exposed to light at the initiation of the experiment on the ISS (International Space Station). The plates were grown in the Vegetable Production System (VPS/Veggie) hardware on the Columbus Module of the ISS with the overhead LED lighting of the VPS. At four or for the second experimental set at eight days, seedlings were harvested by an astronaut into KFT (Kennedy Fixation Tube) containing RNAlater solutions. Upon return to Earth, the harvested material was used to compare the transcriptomes of each genotype and each age using RNAseq technology. The patterns of gene expression was compared between treatments (spaceflight versus ground control) within each genotype of same age or between two ages within same genotype and within same treatment. For 4 day old roots 5-8 roots were combined to serve as one biological replica. For 8 day old roots 2-3 roots were used to form one biological replica. In each case the four biological replicas were used for the transcriptomic analysis.","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/c63fe0f1-02bb-4fb6-8bff-2264a998be79","harvest_record_raw":"https://catalog.data.gov/harvest_record/c63fe0f1-02bb-4fb6-8bff-2264a998be79/raw","has_download":true,"has_spatial":false,"identifier":"10.26030/j07k-nm86","keyword":["biological-and-physical-sciences","genelab","nasa"],"last_harvested_date":"2026-08-19T00:47:18.120874","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"},"popularity":4,"publisher":"Open Science Data Repository","slug":"during-development-the-sku5-mutant-roots-engage-different-genes-than-wild-type-ws-roots-ei","spatial_centroid":null,"spatial_shape":null,"theme":["Biological and Physical Sciences"],"title":"During development, the Sku5 mutant roots engage different genes than wild type WS roots, either on the ground or in spaceflight.","type":"dataset"},{"_score":12.521318,"_sort":[1787100434304,12.521318,4,"4cb63daf-9b11-40a7-9298-9c048d419a67"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Open Science Data Repository Help Desk","hasEmail":"mailto:arc-dl-osdr-help@mail.nasa.gov"},"description":"Understanding the molecular mechanisms by which plants sense and adapt to changes in the space environment is essential for generating plants that are better adapted to withstand space flight, microgravity, and other adverse conditions encountered in space. The objective of our spaceflight experiment \u201cPlant Signaling in Microgravity\u201d (carried out on the International Space Station, ISS), was to compare transcript profiles of wild type and transgenic InsP 5-ptase plants with compromised InsP3 signaling. The transgenic Arabidopsis plants constitutively express the mammalian type I inositol polyphosphate 5-phosphatase (InsP 5-ptase), an enzyme that specifically hydrolyzes the lipid-derived second messenger inositol 1,4,5-trisphosphate (InsP3). These transgenic plants exhibit normal growth and morphology; however, their responses to environmental stimuli including gravity and drought are altered. Seedlings were grown for 5 days under continuous light in experimental containers placed in the European Modular Cultivation system (EMCS) onboard the ISS. The EMCS consists of two rotors within a controlled chamber, allowing for a \u201c1g\u201d control in space. After sample retrieval from the ISS, RNA was isolated from shoot and root tissue and subjected to RNA sequencing. Two-way comparisons of micro g versus \u201c1\u201dg have uncovered regulatory mechanisms that are both conserved and altered between the wild type and transgenic seedlings.","distribution":[{"@type":"dcat:Distribution","downloadURL":"http://purl.bioontology.org/ontology/NCBITAXON/3702","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://nlsp.nasa.gov/view/lsdapub/lsda_experiment/8bb8cb8a-d1ee-5806-bac3-a8c28d3e7fad","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://osdr.nasa.gov/bio/repo/data/missions/STS-135","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://osdr.nasa.gov/bio/repo/data/studies/OSD-223","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.26030/wdtz-v612","keyword":["biological-and-physical-sciences","genelab","nasa"],"license":"https://www.usa.gov/government-works","modified":"2026-08-10","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"Open Science Data Repository"},"theme":["Biological and Physical Sciences"],"title":"The effect of spaceflight on transgenic Arabidopsis plants with compromised signaling"},"description":"Understanding the molecular mechanisms by which plants sense and adapt to changes in the space environment is essential for generating plants that are better adapted to withstand space flight, microgravity, and other adverse conditions encountered in space. The objective of our spaceflight experiment \u201cPlant Signaling in Microgravity\u201d (carried out on the International Space Station, ISS), was to compare transcript profiles of wild type and transgenic InsP 5-ptase plants with compromised InsP3 signaling. The transgenic Arabidopsis plants constitutively express the mammalian type I inositol polyphosphate 5-phosphatase (InsP 5-ptase), an enzyme that specifically hydrolyzes the lipid-derived second messenger inositol 1,4,5-trisphosphate (InsP3). These transgenic plants exhibit normal growth and morphology; however, their responses to environmental stimuli including gravity and drought are altered. Seedlings were grown for 5 days under continuous light in experimental containers placed in the European Modular Cultivation system (EMCS) onboard the ISS. The EMCS consists of two rotors within a controlled chamber, allowing for a \u201c1g\u201d control in space. After sample retrieval from the ISS, RNA was isolated from shoot and root tissue and subjected to RNA sequencing. Two-way comparisons of micro g versus \u201c1\u201dg have uncovered regulatory mechanisms that are both conserved and altered between the wild type and transgenic seedlings.","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/1275db7a-ffa4-4f6f-bdbc-058647abf37d","harvest_record_raw":"https://catalog.data.gov/harvest_record/1275db7a-ffa4-4f6f-bdbc-058647abf37d/raw","has_download":true,"has_spatial":false,"identifier":"10.26030/wdtz-v612","keyword":["biological-and-physical-sciences","genelab","nasa"],"last_harvested_date":"2026-08-19T00:47:14.304968","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"},"popularity":4,"publisher":"Open Science Data Repository","slug":"the-effect-of-spaceflight-on-transgenic-arabidopsis-plants-with-compromised-signaling","spatial_centroid":null,"spatial_shape":null,"theme":["Biological and Physical Sciences"],"title":"The effect of spaceflight on transgenic Arabidopsis plants with compromised signaling","type":"dataset"},{"_score":9.134415,"_sort":[1787100425620,9.134415,3,"69b87a1a-7a9d-48d8-8533-dc545c92e4f5"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["026:00"],"contactPoint":{"@type":"vcard:Contact","fn":"Open Science Data Repository Help Desk","hasEmail":"mailto:arc-dl-osdr-help@mail.nasa.gov"},"description":"The environmental microbiome study was designed to decipher microbial diversity of the International Space Station surfaces in terms of spatial and temporal distributions using 16S and ITS iTag Illumina sequencing. We hypothesized that the microbial population of environmental surfaces changes in time due to astronauts' activity and might be location specific. The environmental samples were collected with the polyester wipes from eight different locations in the ISS during two consecutive sampling sessions (three months apart). The specific objective was to unveil the viable microbial diversity of each location during two separate sessions in terms of abundance and richness of the communities. The International Space Station (ISS) as a closed built environment has its own environmental microbiome which is shaped by microgravity, radiation, and limited human presence. The microbial diversity associated with ISS environmental surfaces was investigated during this study. Polyester wipes and contact slides were used for sampling of eight various surface locations on the ISS at different time periods. The samples were retrieved and analyzed immediately upon the return to the Earth (via Soyuz TMA-14M or Dragon capsule from SpaceX). After surface sample collection, contact slides containing nutrient media for the growth of bacteria and fungi were incubated at 25C. The polyester wipes were processed to measure microbial burden (R2A, Blood Agar, and Potato Dextrose Agar) and recover cultivable bacteria as well as fungi. Subsequently, viable microbial burden was assessed using Adenosine Triphosphate (ATP) assay, and quantitative polymerase chain reaction (PCR) methods after propidium monoazide (PMA) treatment. The 16S-tag and metagenome analyses were used to elucidate viable microbial diversity. The cultivable bacterial population yield from the polyester wipes was very high (5 to 7-logs) when compared with the contact slides (102 to 103 CFU/m2). The PMA-qPCR analysis showed considerable variation of viable bacterial population (105 to 109 16S rDNA gene copies/m2) among locations sampled. Unlike contact slides, polyester wipes cover much larger sample surface (~1 m2) and produce much more reliable results of the microbial diversity of the ISS covering both cultivable and non-cultivable species. The cultivable, total, and viable microbial diversity was determined utilizing state-of-the art molecular techniques. The implementation of the PMA assay before DNA extraction allowed distinguishing viable microorganisms, which is crucial for determining their role to the crew health, the ISS maintenance and the general knowledge of the closed environmentally controlled built systems.","distribution":[{"@type":"dcat:Distribution","downloadURL":"http://purl.bioontology.org/ontology/NCBITAXON/13613","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://nlsp.nasa.gov/view/lsdapub/lsda_experiment/c4df82ca-6b22-5b77-9515-722c0ac999c3","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://osdr.nasa.gov/bio/repo/data/missions/SpaceX-5","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://osdr.nasa.gov/bio/repo/data/missions/SpaceX-6","format":"BIN","mediaType":"application/octet-stream"},{"@type":"dcat:Distribution","downloadURL":"https://osdr.nasa.gov/bio/repo/data/studies/OSD-65","format":"BIN","mediaType":"application/octet-stream"}],"identifier":"10.26030/k2s7-ke78","keyword":["biological-and-physical-sciences","genelab","nasa"],"license":"https://www.usa.gov/government-works","modified":"2026-08-10","programCode":["026:000"],"publisher":{"@type":"org:Organization","name":"Open Science Data Repository"},"theme":["Biological and Physical Sciences"],"title":"Microbial Observatory (ISS-MO): Microbial diversity"},"description":"The environmental microbiome study was designed to decipher microbial diversity of the International Space Station surfaces in terms of spatial and temporal distributions using 16S and ITS iTag Illumina sequencing. We hypothesized that the microbial population of environmental surfaces changes in time due to astronauts' activity and might be location specific. The environmental samples were collected with the polyester wipes from eight different locations in the ISS during two consecutive sampling sessions (three months apart). The specific objective was to unveil the viable microbial diversity of each location during two separate sessions in terms of abundance and richness of the communities. The International Space Station (ISS) as a closed built environment has its own environmental microbiome which is shaped by microgravity, radiation, and limited human presence. The microbial diversity associated with ISS environmental surfaces was investigated during this study. Polyester wipes and contact slides were used for sampling of eight various surface locations on the ISS at different time periods. 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Geographic coordinates are obtained from an onboard Global Positioning System, GPS, unit. Magnetic coordinates are derived by using the International Radiation Belt Environment Modeling, IRBEM, FORTRAN library.\n\nThe BARREL Mission was a multiple-balloon investigation designed to study electron losses from Earth's Radiation Belts. Selected as a NASA Living with a Star Mission of Opportunity, BARREL was designed to augment the Radiation Belt Storm Probes, RBSP, mission by providing measurements of the spatial and temporal variations of electron precipitation from the radiation belts. The RBSP mission has since been renamed the Van Allen Probes mission. Each BARREL balloon carried an X-ray spectrometer to measure the bremsstrahlung X-rays produced by precipitating relativistic electrons as they collide with neutrals in the atmosphere, and a DC magnetometer to measure ULF-timescale variations of the magnetic field. BARREL observations collected near latitudes close to either the antarctic and arctic circles at stratospheric altitudes at about 30 km. The BARREL instrumentation provided the first balloon measurements of relativistic electron precipitation while comprehensive in situ measurements of both plasma waves and energetic particles were available. Also, the BARREL data has been used to characterize the spatial scale of precipitation at relativistic energies.\n\nThe initial pair of balloon campaigns that were conducted initially during the Austral summer months of January and February of 2013 and 2014 with launches from two stations located in Antarctica: the British base located at Halley Bay on the Brunt Ice Shelf and the South African SANAE IV base (SANAE stand for South African National Antarctic Expedition) located in Vesleskarvet, Queen Maud Land. For the 2013 and 2014 the balloon campaigns, the launch plan was designed to maintain an array with about five payloads spread across about six hours of magnetic local time, MLT, in the region that magnetically maps to the radiation belts. Thus, the BARREL balloon constellation constituted an evolving and slowly moving array able to study relativistic electron precipitation from the radiation belts.\n\nLater campaigns were undertaken in 2015 and 2016 from the Esrange Space Center located in Kiruna, Sweden. The 2015 and 2016 campaigns were undertaken in coordination with the Van Allen Probes mission, the European Incoherent Scatter Scientific Association, EISCAT, incoherent scatter radar system, and other ground and space based instruments. Seven balloon launches occurred during the August 2015 BARREL campaign. A total of eight flights occurred during August 2016.\n\nSumming over the four BARREL campaigns, over 50 small, approximately 20 kg, stratospheric balloons were successively launched. The website creeated and hosted by A.J. Halford (see Information URL below) reports that: \"By the end of the campaigns, there were over 90 researchers coordinating on a daily basis with the BARREL team working on 7 different satellite missions, 1 other balloon mission, and way too many ground based instruments to count.\" Although the BARREL mission launched only balloons during the years from 2013 to 2016, research using data collected on these flights is ongoing, so stay tuned for updates! All data and analysis software are freely available to the scientific community.\n\nThe information listed above in this resource description was compiled by referencing several BARREL related resources including primarily the Millan et al. 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This will help you ensure that your science results are valid.\n\n* Users should always use the highest version numbers of data and analysis tools. Browse/quick-look plots are not intended for science analysis or publication and should not be used for those purposes without consent of the principal investigator, PI.\n* Users should notify the BARREL PI of the data use and investigation objectives. This will ensure that you are using the data appropriately and have the most recent version of the data or analysis routines. Additionally, if a BARREL team member is already working on a similar or related topic, they may be able to contribute intellectually.\n* If BARREL team members are not part of the author list, then users should Credit/Acknowledge the BARREL team as follows: We acknowledge the BARREL team (PI: Robyn Millan) for use of BARREL data.\n* Users are also requested to provide the PI with a copy of each manuscript that uses BARREL data upon submission of that manuscript for consideration of publication. 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For the 2013 and 2014 the balloon campaigns, the launch plan was designed to maintain an array with about five payloads spread across about six hours of magnetic local time, MLT, in the region that magnetically maps to the radiation belts. Thus, the BARREL balloon constellation constituted an evolving and slowly moving array able to study relativistic electron precipitation from the radiation belts.\n\nLater campaigns were undertaken in 2015 and 2016 from the Esrange Space Center located in Kiruna, Sweden. The 2015 and 2016 campaigns were undertaken in coordination with the Van Allen Probes mission, the European Incoherent Scatter Scientific Association, EISCAT, incoherent scatter radar system, and other ground and space based instruments. Seven balloon launches occurred during the August 2015 BARREL campaign. A total of eight flights occurred during August 2016.\n\nSumming over the four BARREL campaigns, over 50 small, approximately 20 kg, stratospheric balloons were successively launched. The website creeated and hosted by A.J. Halford (see Information URL below) reports that: \"By the end of the campaigns, there were over 90 researchers coordinating on a daily basis with the BARREL team working on 7 different satellite missions, 1 other balloon mission, and way too many ground based instruments to count.\" Although the BARREL mission launched only balloons during the years from 2013 to 2016, research using data collected on these flights is ongoing, so stay tuned for updates! All data and analysis software are freely available to the scientific community.\n\nThe information listed above in this resource description was compiled by referencing several BARREL related resources including primarily the Millan et al. 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This will help you ensure that your science results are valid.\n\n* Users should always use the highest version numbers of data and analysis tools. Browse/quick-look plots are not intended for science analysis or publication and should not be used for those purposes without consent of the principal investigator, PI.\n* Users should notify the BARREL PI of the data use and investigation objectives. This will ensure that you are using the data appropriately and have the most recent version of the data or analysis routines. Additionally, if a BARREL team member is already working on a similar or related topic, they may be able to contribute intellectually.\n* If BARREL team members are not part of the author list, then users should Credit/Acknowledge the BARREL team as follows: We acknowledge the BARREL team (PI: Robyn Millan) for use of BARREL data.\n* Users are also requested to provide the PI with a copy of each manuscript that uses BARREL data upon submission of that manuscript for consideration of publication. 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For the 2013 and 2014 the balloon campaigns, the launch plan was designed to maintain an array with about five payloads spread across about six hours of magnetic local time, MLT, in the region that magnetically maps to the radiation belts. Thus, the BARREL balloon constellation constituted an evolving and slowly moving array able to study relativistic electron precipitation from the radiation belts.\n\nLater campaigns were undertaken in 2015 and 2016 from the Esrange Space Center located in Kiruna, Sweden. The 2015 and 2016 campaigns were undertaken in coordination with the Van Allen Probes mission, the European Incoherent Scatter Scientific Association, EISCAT, incoherent scatter radar system, and other ground and space based instruments. Seven balloon launches occurred during the August 2015 BARREL campaign. A total of eight flights occurred during August 2016.\n\nSumming over the four BARREL campaigns, over 50 small, approximately 20 kg, stratospheric balloons were successively launched. The website creeated and hosted by A.J. Halford (see Information URL below) reports that: \"By the end of the campaigns, there were over 90 researchers coordinating on a daily basis with the BARREL team working on 7 different satellite missions, 1 other balloon mission, and way too many ground based instruments to count.\" Although the BARREL mission launched only balloons during the years from 2013 to 2016, research using data collected on these flights is ongoing, so stay tuned for updates! All data and analysis software are freely available to the scientific community.\n\nThe information listed above in this resource description was compiled by referencing several BARREL related resources including primarily the Millan et al. (2013) Space Science Reviews publication, the BARREL at Dartmouth mission web site, and the website maintained by A.J. Halford.\n\nThe current release of all BARREL CDF data products are Version 10 files.\n\nBARREL will make all its scientific data products quickly and publicly available but all users are expected to read and follow the BARREL Data Usage Policy listed below.\n\nBARREL Data Usage Policy\n\nBARREL data products are made freely available to the public and every effort is made to ensure that these products are of the highest quality. However, there may occasionally be issues with either the instruments or data processing that affect the accuracy of data. When possible, a quality flag is included in higher level data products, and known issues are posted in the BARREL data repository. You are also strongly encouraged to follow the guidelines below if you are planning a publication or presentation in which BARREL data are used. 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