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6,782 results for “project”
10m Digital Elevation Model From National Elevation Dataset, Niwot Ridge LTER Project Area, Colorado
The U.S. Geological Survey has developed a National Elevation Dataset (NED). The NED is a seamless mosaic of best-available elevation data. The 7.5-minute elevation data for the conterminous United States are the primary initial source data. In addition to the availability of complete 7.5-minute data, efficient processing methods were developed to filter production artifacts in the existing data, convert to the NAD83 datum, edge-match, and fill slivers of missing data at quadrangle seams. One of the effects of the NED processing steps is a much-improved base of elevation data for calculating slope and hydrologic derivatives. The specifications for the NED 1 arc second and 1/3 arc second data are: Geographic coordinate system Horizontal datum of NAD83, except for AK which is NAD27 Vertical datum of NAVD88, except for AK which is NAVD29 Z units of meters NOTE: This EML metadata file does not contain important geospatial data processing information. Before using any NWT LTER geospatial data read the arcgis metadata XML file in either ISO or FGDC compliant format, using ArcGIS software (ArcCatalog > description), or by viewing the .xml file provided with the geospatial dataset.
10m Digital Elevation Model Shaded Relief From National Elevation Dataset, Niwot Ridge LTER Project Area, Colorado
The U.S. Geological Survey has developed a National Elevation Dataset (NED). The NED is a seamless mosaic of best-available elevation data. The 7.5-minute elevation data for the conterminous United States are the primary initial source data. In addition to the availability of complete 7.5-minute data, efficient processing methods were developed to filter production artifacts in the existing data, convert to the NAD83 datum, edge-match, and fill slivers of missing data at quadrangle seams. One of the effects of the NED processing steps is a much-improved base of elevation data for calculating slope and hydrologic derivatives. The specifications for the NED 1 arc second and 1/3 arc second data are: Geographic coordinate system Horizontal datum of NAD83, except for AK which is NAD27 Vertical datum of NAVD88, except for AK which is NAVD29 Z units of meters NOTE: This EML metadata file does not contain important geospatial data processing information. Before using any NWT LTER geospatial data read the arcgis metadata XML file in either ISO or FGDC compliant format, using ArcGIS software (ArcCatalog > description), or by viewing the .xml file provided with the geospatial dataset.
30m Digital Elevation Model From National Elevation Dataset, Niwot Ridge LTER Project Area, Colorado
The U.S. Geological Survey has developed a National Elevation Dataset (NED). The NED is a seamless mosaic of best-available elevation data. The 7.5-minute elevation data for the conterminous United States are the primary initial source data. In addition to the availability of complete 7.5-minute data, efficient processing methods were developed to filter production artifacts in the existing data, convert to the NAD83 datum, edge-match, and fill slivers of missing data at quadrangle seams. One of the effects of the NED processing steps is a much-improved base of elevation data for calculating slope and hydrologic derivatives. The specifications for the NED 1 arc second and 1/3 arc second data are: Geographic coordinate system Horizontal datum of NAD83, except for AK which is NAD27 Vertical datum of NAVD88, except for AK which is NAVD29 Z units of meters NOTE: This EML metadata file does not contain important geospatial data processing information. Before using any NWT LTER geospatial data read the arcgis metadata XML file in either ISO or FGDC compliant format, using ArcGIS software (ArcCatalog > description), or by viewing the .xml file provided with the geospatial dataset.
30m Digital Elevation Model Shaded Relief From National Elevation Dataset, Niwot Ridge LTER Project Area, Colorado
The U.S. Geological Survey has developed a National Elevation Dataset (NED). The NED is a seamless mosaic of best-available elevation data. The 7.5-minute elevation data for the conterminous United States are the primary initial source data. In addition to the availability of complete 7.5-minute data, efficient processing methods were developed to filter production artifacts in the existing data, convert to the NAD83 datum, edge-match, and fill slivers of missing data at quadrangle seams. One of the effects of the NED processing steps is a much-improved base of elevation data for calculating slope and hydrologic derivatives. The specifications for the NED 1 arc second and 1/3 arc second data are: Geographic coordinate system Horizontal datum of NAD83, except for AK which is NAD27 Vertical datum of NAVD88, except for AK which is NAVD29 Z units of meters. NOTE: This EML metadata file does not contain important geospatial data processing information. Before using any NWT LTER geospatial data read the arcgis metadata XML file in either ISO or FGDC compliant format, using ArcGIS software (ArcCatalog > description), or by viewing the .xml file provided with the geospatial dataset.
Snow-Off Digital Terrain Model (DTM) shaded relief from 2010 LiDAR Niwot Ridge LTER Project Area, Colorado
Citation: Anderson, S.P., Qinghua, G., and Parrish, E.G., 2012, Snow-on and snow-off LiDAR point cloud data and digital elevation models for study of topography, snow, ecosystems, and environmental change at Boulder Creek Critical Zone Observatory, Colorado: Boulder Creek CZO, INSTAAR, University of Colorado at Boulder, digital media. This 1m Digital Terrain Model (DTM) shaded relief is a snow-off DTM derived from bare-ground Light Detection and Ranging (LiDAR) point cloud data from August 2010 for the Boulder Creek Critical Zone Observatory (CZO), near Boulder Colorado. This dataset is better suited for derived layers such as slope angle, aspect, and contours. The DTM was created from 1,375 LiDAR point cloud tiles subsampled from 10 points/m2 to 1-meter postings, acquired by the National Center for Airborne Laser Mapping (NCALM) project. This data was collected in collaboration between the Boulder Creek CZO and NCALM, both funded by the National Science Foundation (NSF). The DTM has the functionality of a map layer for use in Geographic Information Systems (GIS) or remote sensing software. Total area imaged is 598.92 km^2. The LiDAR point cloud data was acquired with an Optech Gemini Airborne Laser Terrain Mapper (ALTM) and mounted in a Piper Twin PA-31 Chieftain with Inertial Measurement Unit (IMU) at a flying height of 600 m. Data from four GPS (Global Positioning System) ground stations were used for aircraft trajectory determination. The continuous DTM surface was created by mosaicing and then kriging 0.5 x 1 km LiDAR point cloud LAS-formated tiles using Golden Software's Surfer 8 Kriging algorithm. Horizontal accuracy is at least, but usually better than, 11 cm RMSE at 1 sigma and vertical accuracy is 5-30 cm RMSE at 1 sigma. The layer is available in IMAGINE format approx. 4 GB of data. It has a UTM zone 13 projection, with a NAD83 horizonal datum and a NAVD88 vertical datum, with FGDC-compliant metadata. A shaded relief model was also generated. A similar la
1:10,000 Soils, Niwot Ridge LTER Project Area, Colorado
Soils data digitized from 1:10,000 soils maps for most of length of Niwot Ridge. Source maps and soil classifications taken from Scott Burns' doctoral dissertation (Burns 1980). NOTE: This EML metadata file does not contain important geospatial data processing information. Before using any NWT LTER geospatial data read the ArcGIS metadata XML file in either ISO or FGDC compliant format using ArcGIS software or by viewing the .xml file provided with the geospatial dataset.
US-Hungary Grassland Biodiversity (cross-site project): 4x4 m Sample Plot Data (1996-1997)
Plant cover estimates were collected from Bouteloua grasslands at 3 different LTER (SGS, SEV, JRN) sites in summer of 1996/1997. The purpose of the data collection was to compare species composition and diversity between LTER sites and sandy grassland sites in Hungary.
Gunnison's Prairie Dog Relocation Project: Vegetation Cover Data from the Sevilleta National Wildife Refuge, New Mexico (2005-2013)
Prairie dogs are keystone species that impact both animals and plants in grassland habitats. They are a food resource for secondary consumers such as badgers, foxes, and raptors. Also, the mounds that they construct are home to many arthropod and reptile species that otherwise might not survive in grasslands. Both Gunnison’s and black-tailed prairie dogs can increase the number of plant species in grasslands and landscape heterogeneity with their ecosystem engineering that creates disturbed patches on the landscape. Gunnison’s prairie dogs, which were native herbivores at the Sevilleta National Wildlife Refuge (NWR) before their populations disappeared, were reintroduced at the Sevilleta NWR in 1997, 2005, and 2008. In 1998, a Gunnison’s prairie dog colony naturally established along the northern border on the east side of the Refuge. The naturally occurring colony and the colony that was reintroduced in 1997 have since then severely declined or gone locally extinct. Still, with the removal of cattle from the Sevilleta in 1973, the reintroductions of Gunnison’s prairie dogs in 2005 and 2008 provides an interesting opportunity to study how a native keystone herbivore affects a grassland habitat without the pressures and competition from livestock.
SGS-LTER Long-Term Monitoring Project: Body weights of rodents captured during SGS-LTER live-trapping on the Central Plains Experimental Range, Nunn, Colorado, USA 1994 -2011, ARS Study Number 118
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. Additional information and referenced materials can be found: http://hdl.handle.net/10217/83452. Body size is a fundamental biological measurement that is known to be related to an organism's physiology, life-history and ecology. Estimates of body size are also widely used in comparative evolutionary and ecological studies, including food web and diet studies that require estimates of biomass. Beginning in 1994, small mammals are live-trapped twice each year on the three grassland and three shrubland trapping webs. Individuals are weighed (to nearest 0.5 g using a Pesola spring scale) when first captured during a given trapping session but not upon recapture during the same session. Weights are calculated by subtracting the weight of an empty capture (ziploc) bag from the weight of animal in the bag. Individuals are classified into age classes (adult, subadult, juvenile) in the field based on a combination of size and pelage characteristics. This dataset gives means, standard deviations, minimum and maximum values for body weight, in grams, of small mammals captured between September 1994 and September 2008. All sites and sampling periods were combined. Most individuals (~93%) were classified as new captures, although a few individuals that were captured multiple time
SGS-LTER CO2 Elevation Study: Plant nitrogen, carbon and carbohydrates from Open Top Chamber project on the Central Plains Experimental Range, Nunn, Colorado, USA 1997 - 2001
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. Additional information and referenced materials can be found: http://hdl.handle.net/10217/82454. Plant samples from ambient and elevated CO2 open-top chambers, and unchambered controls, were collected for nitrogen, carbon and carbohydrates analysis on many dates over a five year period. In general, under elevated CO2, nitrogen was decreased, carbon was increased and carbohydrates were increased. This research was conducted at the Central Plains Experimental Range, near Nunn, CO; lat.40degrees 40 minutes N; long. 104 degrees 45 minutes W in the shortgrass steppe region of NE Colorado, USA and as a collaboration between SGS-LTER and USDA-ARS researchers.
final project dataset
<p>This is all my dataset used in final project.</p>
Photographs of selected 'Skopje 2014' projects taken in April 2017, Skopje, North Macedonia
<p>Photographs of selected 'Skopje 2014' projects taken in April 2017, Skopje, North Macedonia.</p> <p>Author attribution necessary.</p> <p>This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.</p>
Archive of JPG image files of Herbarium specimens from Columbia used in the BRAVO project.
<p>Archive of JPG image files of Herbarium specimens used in the BRAVO project.</p> <p>The individual images of herbarium specimens will also be included in the Zenodo project (in time)</p> <p>The project will pull these files into the workbench <a href="http://bravo.rbge.info/">http://bravo.rbge.info/</a></p> <p>The metadata for these images is included in the Zenodo project.</p>
Are developers losing interest on my project? An initial study on unstar events on GitHub platform
<p>GitHub is the most popular social coding platform and the world's largest collection of open source software. In this platform, users can star repositories to manifest their interest or satisfaction with the hosted project. However, it is not possible to maintainers of these projects to know whether they are losing the interest of developers from this platform (i.e., developers are removing their stars). In this paper, we present an initial investigation on how often developers remove stars from GitHub projects and the impact on their popularity. Our results show that GitHub projects frequently lose stars, however these events do not have a major influence on their overall popularity since most of them gain more stars than lose stars. We also show that some programming languages retain the interest from developers for more time.</p>
Dataset and scripts for "Sentiment Analysis over Collaborative Relationships in Open Source Software Projects"
<p>Dataset and scripts for "Sentiment Analysis over Collaborative Relationships in Open Source Software Projects".</p> <p>README is included in the files</p>
Dataset and Code for "Mining and Predicting Micro-Process Patterns of Issue Resolution for Open Source Software Projects"
<p>Dataset and Code for "Mining and Predicting Micro-Process Patterns of Issue Resolution for Open Source Software Projects" with README included</p>
Dataset for TECHNICAL SOLUTIONS FOR INCREASING DER HOSTING CAPACITY IN DISTRIBUTION GRIDS IN THE CZECH REPUBLIC IN TERMS OF EUROPEAN PROJECT INTERFLEX
<p>Data set for TECHNICAL SOLUTIONS FOR INCREASING DER HOSTING CAPACITY IN DISTRIBUTION GRIDS IN THE CZECH REPUBLIC IN TERMS OF EUROPEAN PROJECT INTERFLEX</p>
Dataset for Technical Solutions for Increasing PV Penetration in Distribution Grids in the Czech Republic in Terms of Interflex project
<p>Dataset for Technical Solutions for Increasing PV Penetration in Distribution Grids in the Czech Republic in Terms of Interflex project</p>
Dataset for Increasing DER Hosting Capacity in LV Grids in the Czech Republic in Terms of European Project InterFlex
<p>Dataset for Increasing DER Hosting Capacity in LV Grids in the Czech Republic in Terms of European Project InterFlex</p>
Dataset for Vliv dobijeni elektromobilu na pomery v distribucni soustave from CK CIRED Tabor 2018 Analysis of Smart Technical Measures Impacts on DER and EV Hosting Capacity Increase in LV and MV Grids in the Czech Republic in Terms of European Project InterFlex from SEST2019 Analysis of Smart Technical Measures Impacts on DER and EV Hosting Capacity Increase in LV and MV Grids in the Czech Republic in Terms of European Project InterFlex from ISGT2019 Evropský projekt InterFlex from CK CIRED Tabor 2017
<p>Dataset for</p> <p>Vliv dobijeni elektromobilu na pomery v distribucni soustave from CK CIRED Tabor 2018</p> <p>Analysis of Smart Technical Measures Impacts on DER and EV Hosting Capacity Increase in LV and MV Grids in the Czech Republic in Terms of European Project InterFlex from SEST2019</p> <p>Analysis of Smart Technical Measures Impacts on DER and EV Hosting Capacity Increase in LV and MV Grids in the Czech Republic in Terms of European Project InterFlex from ISGT2019</p> <p>Evropský projekt InterFlex from CK CIRED Tabor 2017</p>
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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)
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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.