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22,922 results for “Collections as data”
Regional databases demonstrate macroecological patterns less clearly than systematically collected field data
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Data from: Comparative assessment of a novel fan box trap for collecting Anopheles farauti and culicine mosquitoes alive in tropical north Queensland, Australia
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Baltic Sea stable isotope ecology meta-data collection
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Cucumber core collection fruit morphological traits raw data (2019-2022)
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Data collected by fruit body– and DNA-based survey methods yield consistent species-to-species association networks in wood-inhabiting fungal communities
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Data and code from: Integrating genomics, collections, and community science to delimit species clarifies the taxonomy of a variable monitor lizard (<em>Varanus tristis</em>)
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Data from: Baboon travel progressions as a ‘social spandrel’ in collective animal behaviour
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Collection and ddRadSeq sequencing data for Sitophilus zeamais from Oaxaca and Chiapas, Mexico
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Wirewalker data collected during the 2020 Southern California red tide
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Data for: Re-collected after 55 years: a new species of Bembidion (Coleoptera, Carabidae) from California
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Protea repens whole transcriptome count data for control and drought treatment for 8 populations, climatic data for the 8 populations and phenotypic data collected, and data used for linear mixed models for climate gene expression/trait correlation testing
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University of Kansas Field Station: Cumulative field records of snake species collected by Dr. Henry S. Fitch 1948 - 2003, with a few additional records collected 2004 - 2016. Records contain capture locations, measurements, notes on reproduction, recapture, and growth data. This data package contains individual files for 14 species.
Dr. Henry S. Fitch began his pioneering research on the snake fauna of the Fitch Natural History Reservation and adjacent University of Kansas Field Station in 1948. Fitch remained an active researcher until the early 2000s. For nearly six decades he conducted extensive field work on snakes using capture/recapture techniques, and compiled other biological data as well (e.g., all snakes captured were weighed, measured, and marked with incomplete data collected on reproduction, stomach contents, and recaptures). This research resulted in scores of scientific publications on the ecology of the snakes. Henry S. Fitch died in 2009 and left as a legacy hand-written data sheets with approximately 60,000 capture records. George R. Pisani, a biologist at the University of Kansas and later at the Kansas Biological Survey, collaborated with Fitch on some ecological studies. Beginning about 2005, Pisani began the many-year process of converting the thousands of Fitch’s records of snake captures into an electronic database. This work was funded in part by the Kansas Dept. of Wildlife, Parks and Tourism Chickadee Checkoff Program.
Toolik Inlet Discharge Data collected in summer 2004, Arctic LTER, Toolik Research Station, Alaska.
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Water column dissolved (DSi) and biogenic (BSi) concentrations and fluxes collected from Sweeney (Right), West (Left) and Clubhead along with temperature, salinity, and flow data from 7/2010
Found at the landesea interface, these systems are silica replete with large stocks in plant biomass, sediments, and porewater, and therefore, have the potential to play a substantial role in the transformation and export of silica to coastal waters. In an effort to better understand this role, we measured the fluxes of dissolved (DSi) and biogenic (BSi) silica into and out of two tidal creeks in the PIE LTER salt marsh system. One of the creeks (Sweeney) has been fertilized from May to September for six years allowing us to examine the impacts of nutrient addition on silica dynamics within the marsh.
SGS-LTER Standard Met Data: 1971-2010 Manually Collected Soil Temperature Data in English Units on the Central Plains Experimental Range, Nunn, Colorado, USA 1971-2008, ARS Study Number 4
This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Digital Collections of Colorado (http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection. The objective of this study is to collect baseline meteorological data for the CPER. Datasets auto12_climdb and man11_climdb have been processed for quality and missing values. Additional information and referenced materials can be found: http://hdl.handle.net/10217/82446.
LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Andrews Forest LTER collected on 1982-12-13
This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Andrews Forest LTER, originally collected on 1982-12-13 (18:24:53.0540560Z) by Landsat 4, row 29, path 46. Cloud cover was 50 percent. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) software was originally developed by the National Aeronautics and Space Administration–Goddard Space Flight Center and the University of Maryland to produce top-of-atmosphere reflectance from Landsat Thematic Mapper and Enhanced Thematic Mapper Plus Level 1 digital numbers and to apply atmospheric corrections to generate a surface-reflectance product. The U.S. Geological Survey (USGS) has adopted the LEDAPS algorithm for producing the Landsat Surface Reflectance Climate Data Record. NASA Landsat Program, 2009, Landsat TM LT40460291982347XXX01, LPGS_12.0.2, USGS, Sioux Falls, 2012-06-10T15:25:20Z.
LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Andrews Forest LTER collected on 1984-07-03
This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Andrews Forest LTER, originally collected on 1984-07-03 (18:24:58.7720880Z) by Landsat 5, row 29, path 46. Cloud cover was 0.1 percent. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) software was originally developed by the National Aeronautics and Space Administration–Goddard Space Flight Center and the University of Maryland to produce top-of-atmosphere reflectance from Landsat Thematic Mapper and Enhanced Thematic Mapper Plus Level 1 digital numbers and to apply atmospheric corrections to generate a surface-reflectance product. The U.S. Geological Survey (USGS) has adopted the LEDAPS algorithm for producing the Landsat Surface Reflectance Climate Data Record. NASA Landsat Program, 2009, Landsat TM LT50460291984185PAC00, LPGS_12.0.2, USGS, Sioux Falls, 2012-05-18T19:30:38Z.
LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Andrews Forest LTER collected on 1994-03-25
This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Andrews Forest LTER, originally collected on 1994-03-25 (18:16:54.8730190Z) by Landsat 5, row 29, path 46. Cloud cover was 0 percent. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) software was originally developed by the National Aeronautics and Space Administration–Goddard Space Flight Center and the University of Maryland to produce top-of-atmosphere reflectance from Landsat Thematic Mapper and Enhanced Thematic Mapper Plus Level 1 digital numbers and to apply atmospheric corrections to generate a surface-reflectance product. The U.S. Geological Survey (USGS) has adopted the LEDAPS algorithm for producing the Landsat Surface Reflectance Climate Data Record. NASA Landsat Program, 2009, Landsat TM LT50460291994084XXX02, LPGS_12.0.2, USGS, Sioux Falls, 2012-05-19T04:11:26Z.
LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Central Arizona - Phoenix LTER collected on 1992-04-30
This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Central Arizona - Phoenix LTER, originally collected on 1992-04-30 (17:21:15.6250190Z) by Landsat 5, row 36, path 36. Cloud cover was 30 percent. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) software was originally developed by the National Aeronautics and Space Administration–Goddard Space Flight Center and the University of Maryland to produce top-of-atmosphere reflectance from Landsat Thematic Mapper and Enhanced Thematic Mapper Plus Level 1 digital numbers and to apply atmospheric corrections to generate a surface-reflectance product. The U.S. Geological Survey (USGS) has adopted the LEDAPS algorithm for producing the Landsat Surface Reflectance Climate Data Record. NASA Landsat Program, 2009, Landsat TM LT50360361992121XXX02, LPGS_12.0.2, USGS, Sioux Falls, 2012-08-17T20:14:38Z.
LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Shortgrass Steppe collected on 1995-04-18
This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Shortgrass Steppe, originally collected on 1995-04-18 (16:46:05.7110690Z) by Landsat 5, row 032, path 033. Cloud cover was 10 percent. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) software was originally developed by the National Aeronautics and Space Administration–Goddard Space Flight Center and the University of Maryland to produce top-of-atmosphere reflectance from Landsat Thematic Mapper and Enhanced Thematic Mapper Plus Level 1 digital numbers and to apply atmospheric corrections to generate a surface-reflectance product. The U.S. Geological Survey (USGS) has adopted the LEDAPS algorithm for producing the Landsat Surface Reflectance Climate Data Record. NASA Landsat Program, 2009, Landsat TM LT50330321995108AAA01, LPGS_12.1.3, USGS, Sioux Falls, 2012-12-22T08:08:12Z.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.