Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
10,699
datasets available to search
ShareScore release 0.9.0
Dataset results
10,699 results for “easting”
Soil moisture and snowdepth measurements in the Black Sand experiment for East Knoll, Audubon, Lefty, Soddie and Trough, 2018 - 2024.
The purpose of the Black Sand experiment is to measure treatment effects on date of snowmelt on Niwot Ridge. Five sites with paired plots (treatment and control) were implemented across Niwot as part of the extended summer research program in order to understand the effects of earlier snowmelt. This dataset contains measurements of snowdepth throughout the melt season, manual measurements of volumetric water content and temperature data as an indication of snowmelt timing.
GRIME AI Water Segmentation Model for the USGS Monitoring Site East Branch Brandywine Creek below Downingtown, PA, 2023-2024
Ground-based observations from fixed-mount cameras have the potential to fill an important role in environmental sensing, including direct measurement of water levels and qualitative observation of ecohydrological research sites. All of this is theoretically possible for anyone who can install a trail camera. Easy acquisition of ground-based imagery has resulted in millions of environmental images stored, some of which are public data, and many of which contain information that has yet to be used for scientific purposes. The goal of this project was to develop and document key image processing and machine learning workflows, primarily related to semi-automated image labeling, to increase the use and value of existing and emerging archives of imagery that is relevant to ecohydrological processes. This data package includes imagery, annotation files, water segmentation model and model performance plots, and model test results (overlay images and masks) for USGS Monitoring Site East Branch Brandywine Creek below Downingtown, PA. All imagery was acquired from the USGS Hydrologic Imagery Visualization and Information System (HIVIS; see https://apps.usgs.gov/hivis/camera/PA_East_Branch_Brandywine_Creek_below_Downingtown for this specific data set) and/or the National Imagery Management System (NIMS) API. Water segmentation models were created by tuning the open-source Segment Anything Model 2 (SAM2, https://github.com/facebookresearch/sam2) using images that were annotated by team members on this project. The models were trained on the "water" annotations, but annotation files may include additional labels, such as "snow", "sky", and "unknown". Image annotation was done in Computer Vision Annotation Tool (CVAT) and exported in COCO format (.json). All model training and testing was completed in GaugeCam Remote Image Manager Educational Artificial Intelligence (GRIME AI, https://gaugecam.org/) software (Version: Beta 16). Model performance plots were automatically generate
GRIME AI Water Segmentation Model for the USGS Monitoring Site at East River at County Trunk HWY ZZ near Greenleaf, WI, 2023-2024
Ground-based observations from fixed-mount cameras have the potential to fill an important role in environmental sensing, including direct measurement of water levels and qualitative observation of ecohydrological research sites. All of this is theoretically possible for anyone who can install a trail camera. Easy acquisition of ground-based imagery has resulted in millions of environmental images stored, some of which are public data, and many of which contain information that has yet to be used for scientific purposes. The goal of this project was to develop and document key image processing and machine learning workflows, primarily related to semi-automated image labeling, to increase the use and value of existing and emerging archives of imagery that is relevant to ecohydrological processes. This data package includes imagery, annotation files, water segmentation model and model performance plots, and model test results (overlay images and masks) for USGS Monitoring Site at East River at County Trunk HWY ZZ near Greenleaf, WI. All imagery was acquired from the USGS Hydrologic Imagery Visualization and Information System (HIVIS; see https://apps.usgs.gov/hivis/camera/WI_East_River_at_HWY_ZZ_near_Greenleaf for this specific data set) and/or the National Imagery Management System (NIMS) API. Water segmentation models were created by tuning the open-source Segment Anything Model 2 (SAM2, https://github.com/facebookresearch/sam2) using images that were annotated by team members on this project. The models were trained on the "water" annotations, but annotation files may include additional labels, such as "snow", "sky", and "unknown". Image annotation was done in Computer Vision Annotation Tool (CVAT) and exported in COCO format (.json). All model training and testing was completed in GaugeCam Remote Image Manager Educational Artificial Intelligence (GRIME AI, https://gaugecam.org/) software (Version: Beta 16). Model performance plots were automatically generated duri
Individual plant growth and reproduction in the black sand extended growing season experiment for East Knoll, Audubon, Lefty, and Trough sites, 2018 - 2020.
As a result of climate change, the Rocky Mountain Front Range is experiencing warmer summers and earlier snowmelt. Due to the importance of snow for regulating soil temperature, growing season length, and available moisture in alpine ecosystems, even small shifts in the snow-free period could have large impacts. The focus of the Black Sand Extended Growing Season Length Experiment is to examine how terrain-related differences in climate exposure influence the way alpine habitats respond to climate change via earlier snowmelt. To simulate how climate exposure may affect plant communities, NWT LTER researchers established 5 experimental sites, each containing a pair 10 x 40m rectangular plots. These sites include north and south facing aspects, subalpine and alpine tundra meadows and a range of hydrological conditions (e.g. dry meadows, moist meadows, wet meadows). We accelerated snowmelt in one plot at each site by adding chemically inert black sand, while keeping the second plot as an unmanipulated control; black sand was added to control plots after snow had naturally melted. We used open top warming chambers (OTCs) to increase summer temperature in three subplots within each of the 10 x 40 m plots. This dataset includes measurements of growth and reproduction for Geum plants as well as counts of buds and flowers were counted and recorded for each tagged study plant, within all snow and warming treatments at all sites except Soddie.
Plant phenology observations in the black sand extended growing season experiment for East Knoll, Audubon, Lefty, and Trough sites, 2018 - 2020.
As a result of climate change, the Rocky Mountain Front Range is experiencing warmer summers and earlier snowmelt. Due to the importance of snow for regulating soil temperature, growing season length, and available moisture in alpine ecosystems, even small shifts in the snow-free period could have large impacts. The focus of the Black Sand Extended Growing Season Length Experiment is to examine how terrain-related differences in climate exposure influence the way alpine habitats respond to climate change via earlier snowmelt. To simulate how climate exposure may affect plant communities, NWT LTER researchers established 5 experimental sites, each containing a pair 10 x 40m rectangular plots. These sites include north and south facing aspects, subalpine and alpine tundra meadows and a range of hydrological conditions (e.g. dry meadows, moist meadows, wet meadows). We accelerated snowmelt in one plot at each site by adding chemically inert black sand, while keeping the second plot as an unmanipulated control; black sand was added to control plots after snow had naturally melted. We used open top warming chambers (OTCs) to increase summer temperature in three subplots within each of the 10 x 40 m plots. This dataset includes measurements of plant species phenology within all snow and warming treatments at all sites except Soddie.
Map of the temples of Allat in the Near East
<p>This map presents the localisation spots of the temples of Allat, located only in the Near East. The map is a result of data collection and building the database in the NodeGoat software. This map is based also on the information from the epigraphical and archaeological sources.</p>
[Dataset] Stroke Caregiver Burden in East Coast Peninsular Malaysia, A Short-term Longitudinal Study
<p>Raw dataset for study entitled "INFORMAL CAREGIVERS BURDEN AMONG STROKE PATIENTS IN EAST-COAST MALAYSIA: A SHORT-TERM LONGITUDINAL STUDY"</p> <p>This study is part of study funded by Newton Ungku Omar Fund (2020-2021) under grant for “A Scalable Solution for Supporting Informal Stroke Caregivers in Malaysia: Systematic Development and Feasibility Study” Malaysian Ministry of Education (203.PPSP.678003) and Medical Research Council, United Kingdom (MR/T018968/1).</p> <p>Please note that this data is in raw csv form, imported from REDCap. due to REDCap system, the raw file need to be relabel and relevel to reflect the original score or response.</p> <p>Data dictionary provided for data relabel and relevel purpose.</p> <p>R script also available to convert the raw csv into dataset with appropriate label and level</p> <p> </p> <p> </p>
Plant recruitment and seed quality in the Black Sand extended growing season experiment for East Knoll, Audubon, Lefty, and Trough sites, 2018 - 2020.
As a result of climate change, the Rocky Mountain Front Range is experiencing warmer summers and earlier snowmelt. Due to the importance of snow for regulating soil temperature, growing season length, and available moisture in alpine ecosystems, even small shifts in the snow-free period could have large impacts. The focus of the Black Sand Extended Growing Season Length Experiment is to examine how terrain-related differences in climate exposure influence the way alpine habitats respond to climate change via earlier snowmelt. To simulate how climate exposure may affect plant communities, NWT LTER researchers established 5 experimental sites, each containing a pair 10 x 40m rectangular plots. These sites include north and south facing aspects, subalpine and alpine tundra meadows and a range of hydrological conditions (e.g. dry meadows, moist meadows, wet meadows). We accelerated snowmelt in one plot at each site by adding chemically inert black sand, while keeping the second plot as an unmanipulated control; black sand was added to control plots after snow had naturally melted. We used open top warming chambers (OTCs) to increase summer temperature in three subplots within each of the 10 x 40 m plots. This dataset includes measurements of plant recruitment and seed quality.
Monthly time series of rainfall, potential evapotranspiration and streamflow for 201 catchments in South-East Australia
<p>The data set contains data for 201 catchments located in South-Eastern Australia. The data was extracted from the datasets collated by Lerat, Thyer et al. (2020) including rainfall and potential-evapotranspiration data obtained from the Bureau of Meteorology Australian Water Outlook website (Frost, Ramchurn et al. 2016) and streamflow data obtained from the Bureau of Meteorology Water Data Online website (Bureau of Meteorology 2019). The data was collected over the period from 1980 to 2018, split into the two sub-periods 1980-1999 (Period 1) and 1999-2018 (Period 2).</p><p> </p><p>Bureau of Meteorology. (2019). "Water Data Online." from <a href="http://www.bom.gov.au/waterdata">http://www.bom.gov.au/waterdata</a>.</p><p>Frost, A. J., A. Ramchurn and A. Smith (2016). "The bureau's operational AWRA landscape (AWRA-L) Model." Bureau of Meteorology Technical Report.</p><p>Lerat, J., M. Thyer, D. McInerney, D. Kavetski, F. Woldemeskel, C. Pickett-Heaps, D. Shin and P. Feikema (2020). "A robust approach for calibrating a daily rainfall-runoff model to monthly streamflow data." Journal of Hydrology<strong>591</strong>: 125129.</p>
Cathedral (Cathédrale Notre-Dame). Interior. The nave. East to West.
<u>File Name</u>: PM_144121_F_Reims <br><u>Sublocation</u>: Cathédrale Notre-Dame <br><u>Location</u>: Reims <br><u>Province</u>: Grand Est, Marne <br><u>Country</u>: France <br><u>Header</u>: Intérieur de la nef, est-ouest <br><u>Description</u>: Cathedral (Cathédrale Notre-Dame). Interior. The nave. East to West. <br><u>Author</u>: Photo: Paul M.R. Maeyaert <br><u>Author Mail</u>: PMRMaeyaert@gmail.com <br><u>Copyright</u>: © Paul M.R. Maeyaert,pmrmaeyaert@gmail.com <br><u>Keywords</u>: Europe|France; Europe|France|Grand Est; Europe|France|Grand Est|Marne; Europe|France|Grand Est|Marne|Reims; Cultural heritage|Monuments|Cathedral; Cultural heritage|Monuments; Cultural heritage <br><u>Date of Generation</u>: 2022-04-28T13:03:37+02:00
Three-dimensional thermal structure of East Asian continental lithosphere
<p>This data set includes 3 supplement data files and 1 readme file for 3D thermal structure of East Asian continental lithosphere. </p>
NERD (NEAR EAST RADIOCARBON DATES)
<p>The archive <strong>NERD</strong> provides a collation of <strong>11,072</strong> radiocarbon dates from <strong>1027</strong> archaeological sites in the Near East from the Late Pleistocene until the Late Holocene (15 - 1.5 cal. kyr BP). These dates have been collected from existing online digital archives, and electronic and print original publications. This is an <strong>ongoing dataset</strong> that will be updated step by step with new published radiocarbon dates. A detailed description of the present dataset is available via the following data paper: <strong>Palmisano, A., Bevan, A., Lawrence, D., and Shennan, S., 2022.<a href="https://openarchaeologydata.metajnl.com/articles/10.5334/joad.90/"> The NERD Dataset: Near East Radiocarbon Dates between 15,000 and 1,500 cal. yr. BP</a></strong>. <em>Journal of Open Archaeology Data</em>, <em>10</em>(2), 1-9.</p> <p>List of versions:</p> <ul> <li><strong>6.0</strong> 23 September 2022 — Removal of 12 duplicates and addition of 2 new dates (update of the files 'References.txt', 'nerd.csv', and 'Readme.md') on the basis of a data assessment on Cyprus dates provided by <a href="https://classics.cornell.edu/sturt-manning">Sturt Manning</a>.</li> <li><strong>5.0 </strong>25 March 2022 — 54 new dates added (update of the files 'References.txt', 'nerd.csv', and 'Readme.md').</li> <li><strong>4.0 </strong>8 December 2021 — 380 new dates added (update of the files 'References.txt', 'nerd.csv', and 'Readme.md').</li> <li><strong>3.0 </strong>7 April 2021 — 10 new dates added (update of the files 'References.txt', 'nerd.csv', and 'Readme.md').</li> <li><strong>2.0.</strong> 7 April 2021 — 31 new dates added (update of the files 'References.txt', 'nerd.csv', and 'Readme.md').</li> <li><strong>1.0 </strong> 6 April 2021 — First public release of the dataset on Zenodo</li> </ul>
A high-resolution, multi-decadal, free-running, hydrodynamic simulation of the East Australia Current System using the Regional Ocean Modeling System (Version 3.0, 1994-2019)
<p>The data is from a Regional Ocean Modelling System free-running, hydrodynamic simulation of the East Australian Current System. The model has a horizontal resolution of 2.5-6 km in the cross-shore direction and 5 km in the alongshore direction, and 30 vertical s-levels. The model domain covers the southeastern Australia oceanic region from 25.1-41.5°S and 147.1-162.2°E, and the grid is orientated 20 degrees clockwise to be predominantly orientated alongshore. The time period covered is 02 Jan 1994 to 28 Feb 2019. The model outputs provided are daily averages of the following variables: Two-dimensional variables: Sea surface height (zeta), barotropic cross-grid velocity (u) and barotropic along-grid velocity (v). Three-dimensional variables: Temperature (temp), salinity (salt), density (rho), cross-grid velocity (u), along-grid velocity (v) and vertical velocity (w), temperature time rate of change (temp_rate), temperature horizontal advection term (temp_hadv), temperature vertical advection term (temp_vadv), temperature horizontal diffusion term (temp_hdiff), temperature vertical diffusion term (temp_vdiff). In this version, the heat budget terms (temp_rate, temp_hadv, temp_vadv, temp_hdiff and temp_vdiff) are set to be zeros on the land.</p> <p> </p> <p>This model is part of the <a href="../records/8294716"><strong>South East Australian Coastal Ocean Forecast System (SEA-COFS)</strong></a> suite of models.</p>
Likelihood maps of East Antarctic lithospheric domain boundaries.
<p>The first public version of maps generated by the methods described by Stål et al (to submit 2019). </p> <p>Updated with SCons sconstruct file containing all code used for the study. </p>
Raw multibeam bathymetry data collected in the wider polynya area around the Mertz glacier, East Antarctica on board the R/V Akademik Tryoshnikov during the austral summer of 2016/2017 as part of the Antarctic Circumnavigation Expedition (ACE).
<p><strong>Dataset abstract</strong></p> <p>An ELAC Nautik 3020 multibeam echo sounder with a 20 kHz transducer mounted on the hull of the R/V Akademik Tryoshnikov, was used to collect multibeam bathymetry data during the Antarctic Circumnavigation Expedition (ACE). This particular dataset was collected in the wider polynya area around the Mertz glacier, East Antarctica in the austral summer of 2016/2017.</p> <p>Bathymetry data were used live during the cruise to look for suitable locations where benthic trawling and remotely-operated vehicle deployments could take place, rather than to undertake specific bathymetric surveys.</p> <p>This raw dataset is provided without calibration information for the surface sound velocity or instrumentation itself and should be used with due caution.</p> <p><strong>Dataset contents</strong></p> <ul> <li>lineYYYYDDmonHHMMSS.xse, data file, proprietary format</li> <li>location.hydrostar, ancillary file, ASCII</li> <li>data_file_header.txt, metadata, text</li> <li>README.txt, metadata, text</li> </ul> <p><strong>Dataset license</strong></p> <p>This raw multibeam bathymetry dataset is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/l</p>
Raw multibeam bathymetry data collected around the Mertz glacier, East Antarcica on board the R/V Akademik Tryoshnikov during the austral summer of 2016/2017 as part of the Antarctic Circumnavigation Expedition (ACE).
<p><strong>Dataset abstract</strong></p> <p>An ELAC Nautik 3020 multibeam echo sounder with a 20 kHz transducer mounted on the hull of the R/V Akademik Tryoshnikov, was used to collect multibeam bathymetry data during the Antarctic Circumnavigation Expedition (ACE). This particular dataset was collected around the Mertz glacier, East Antarcica in the austral summer of 2016/2017.</p> <p>Bathymetry data were used live during the cruise to look for suitable locations where benthic trawling and remotely-operated vehicle deployments could take place, rather than to undertake specific bathymetric surveys.</p> <p>This raw dataset is provided without calibration information for the surface sound velocity or instrumentation itself and should be used with due caution.</p> <p><strong>Dataset contents</strong></p> <ul> <li>lineYYYYDDmonHHMMSS.xse, data file, proprietary format</li> <li>location.hydrostar, ancillary file, ASCII</li> <li>data_file_header.txt, metadata, text</li> <li>README.txt, metadata, text</li> </ul> <p><strong>Dataset license</strong></p> <p>This raw multibeam bathymetry dataset is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/</p>
Raw Data for Mapping Repositories and their Institutional Open Science Policies in the Middle East and North Africa (MENA)
<div> <p>Persistent Identifiers (PIDs), particularly Digital Object Identifiers (DOIs), are crucial for establishing a robust and globally accessible research infrastructure. In the Middle East and North Africa (MENA) region, a diverse array of research outputs and resources are produced and published in repositories. However, a significant number of these repositories, and outputs remain undiscoverable in global registries and aggregators. <br><br>These three datasets provides comprehensive information on the adoption of repositories, Open Access mandates, and DOIs adoption in MENA countries. It includes detailed records from different registry sources and repository platforms.<br><br>You can read the full report titled 'Mapping Repositories and their Institutional Open Science Policies in MENA' at <a href="https://doi.org/10.5281/zenodo.11370031">https://doi.org/10.5281/zenodo.11370031</a></p> </div>
East African topography and volcanism explained by a single, migrating plume: supplementary data
<p>These data accompany the following paper:</p> <p>Hassan, R., Williams, S.E., Gurnis, M. and Müller, D., 2020. East African topography and volcanism explained by a single, migrating plume. <em>Geoscience Frontiers</em>, <em>11</em>(5), pp.1669-1680.</p> <p>The data (in simple text form) correspond to the dynamic topography and change in dynamic topography shown in Figure 7.</p>
Bathymetry beneath the Amery ice shelf, East Antarctica, revealed by airborne gravity
<p>We estimated the seafloor topography beneath the Amery Ice Shelf, East Antarctica, from airborne gravity anomaly through a nonlinear inversion method called simulated annealing. The estimation results provide a view of the seafloor beneath the Amery Ice Shelf, where direct bathymetric observations are rare. The model, 'gravity_estimated_seafloor_topography_beneath_the_Amery_Ice_Shelf.nc', is in NetCDF format which can be read through MATLAB commands "ncdisp" and "ncread". Contents of the model can be found in "contents.txt". The MATLAB program "nc2mat.m" reads the NetCDF ".nc" format model and saves the variables in the model to a MATLAB ".mat" format file.</p>
Spatial and temporal heterogeneity in human mobility patterns in Holocene Southwest Asia and the East Mediterranean
<p>Koptekin et al. (2022) "<strong><em>Spatial and temporal heterogeneity in human mobility patterns in Holocene Southwest Asia and the East Mediterranean</em></strong>", Current Biology <a href="https://doi.org/10.1016/j.cub.2022.11.034">https://doi.org/10.1016/j.cub.2022.11.034</a></p>
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.