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.
23,670
datasets available to search
ShareScore release 0.7.1
Dataset results
23,670 results for “Site”
Forest-wide bird survey at 183 sample sites the Andrews Experimental Forest from 2009 to present (Reformatted to the ecocomDP Design Pattern)
This data package is formatted as an ecocomDP (Ecological Community Data Pattern). For more information on ecocomDP see https://github.com/EDIorg/ecocomDP. This Level 1 data package was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-and/4781/5. The abstract below was extracted from the Level 0 data package and is included for context: Bird occurrence data collected at 183 sample locations within the H. J. Andrews Experimental Forest (HJA) from 2009-present. We used a stratified, systematic, random design to select sample locations. We stratified across elevation, distance to road, and habitat type (plantation or mature/old-growth forest). We conduct point counts on six separate occasions from May – July, which corresponded to spring arrival and subsequent breeding period for the majority of bird species at HJA. Surveys occur between 05:15h and 10:30h and each consists of a 10-min point count where we record all birds seen or heard. The species of all birds seen and heard are recorded as well as all individual squirrels, chipmunks and pikas seen and heard. Survey-level information is also collected at each point count and includes: weather and wind conditions, stream noise, snow cover on the ground, phenology of vine maple and rhododendron. Data collection is ongoing. The H.J. Andrews Experimental Forest is a living laboratory that provides unparalleled opportunities for the study of forest and stream ecosystems in the central Cascade Range of Oregon. Since 1980, as a part of the National Science Foundation Long Term Ecological Research (NSF-LTER) program, the Andrews Experimental Forest has become a leader in the analysis of forest and stream ecosystem dynamics. Long-term field experiments and measurement programs have focused on climate dynamics, streamflow, water quality, and vegetation succession. Currently researchers are working to develop concepts and tools needed to predict effects of natural disturba
GRIME AI Water Segmentation Model for the USGS Lake Serene at Edgewood Camera Monitoring Site, MD, 2022-2024
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). All imagery was acquired from the USGS Hydrologic Imagery Visualization and Information System (HIVIS; see https://apps.usgs.gov/hivis/camera/MD_Lake_Serene_at_Edgewood 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) software (Version: Beta 16). Model performance plots were automatically generated during this process. This project was conducted in 2023-2025 by collaborators at the University of Nebraska-Lincoln, Uni
Water column chlorophyll concentrations from lagoon, river, and ocean sites along the Alaska Beaufort Sea coast, 2018-ongoing
Multiple water types (river, lagoon, ocean) from the North Slope of Alaska and nearshore Beaufort Sea are sampled seasonally by the Beaufort Lagoon Ecosystems LTER (BLE LTER) Core Program to investigate biogeochemical linkages between terrestrial, lagoon, and open ocean ecosystems. Water samples from multiple depths are collected during full ice cover (April), ice break-up (mid-June to early July), and open water (late July and August) periods for quantification of chlorophyll-a concentrations. Concentrations are reported in micrograms of chlorophyll per liter of filtered seawater (μg/L).
Colored dissolved organic matter (CDOM) absorbance from lagoon, ocean, and river sites along the Alaska Beaufort Sea coast, 2021-ongoing
Multiple water types (river, lagoon, ocean) from the North Slope of Alaska and nearshore Beaufort Sea are sampled seasonally by the Beaufort Lagoon Ecosystems LTER (BLE LTER) Core Program to investigate biogeochemical linkages between terrestrial, lagoon, and open ocean ecosystems. Water samples from multiple depths are collected during full ice cover (April), ice break-up (mid-June to early July), and open water (late July and August) periods, filtered, and analyzed for light absorption spectra within 24 hours of collection. Wavelength-specific light absorption coefficients are reported between 250 and 600 nanometers. The data is organized in "long" or "tidy" format, with columns of station, date, wavelength, and absorption. Please see included MakeColumnsAsWavelengths.R, MakeColumnsAsDates.R, and ReshapeDataInExcel.txt for some common ways to reorganize the table for further CDOM analysis. In 2022, data from 2019 were removed due to quality issues (please see revision 1 of this dataset for 2019 CDOM values). For users who may have used 2019 data from this dataset, there are additional files to inform decisions going forward. "BLE_LTER_CDOM_2019_sample_flags.csv" lists which 2019 samples are entirely unreliable, versus usable with caution. "BLE_LTER_CDOM_2021_blank_mean_sd_absorptions.csv" lists mean and standard deviations at each wavelength from all blanks taken in 2021; this is meant to give info on the instruments used and will not be updated further. Please see the methods section for more information on 2019 data.
Spot and continuous seasonal pCO2 sensor measurements from lagoon and river sites along the Alaska Beaufort Sea coast, 2019-ongoing
pCO2 (partial pressure of carbon dioxide) was measured in multiple seasons and depths in coastal ecosystems as part of the Beaufort Lagoons Ecosystems LTER core sampling program. Sites include several Beaufort Lagoons from across the North Slope of Alaska and several river sites near the lagoons. Data includes averages of sensor data for each site and depth deployment of pCO2 (uatm), CO2 (ppm), water temperature (°C), and absolute pressure (kPa). Standard deviation is included for pCO2 (uatm). Surface measurements were taken either 30 cm below the water surface, or bottom of the ice in ice-cover season, and bottom measurements were taken 30 cm from the seafloor of the lagoons. For lagoon sites, data were logged every one or five minutes; for river sites data were recorded every five minutes. Each site and depth was recorded for at least 30 minutes and up to four hours and taken as spot measurement.
Carbon and nitrogen content and stable isotope compositions from biota samples from lagoon sites along the Alaska Beaufort Sea coast, 2018-ongoing
Stable isotopic composition can be used to differentiate between predominantly marine and terrestrial food sources in nearshore marine food webs. The Beaufort Lagoon Ecosystems LTER (BLE LTER) Core Program employs spatial and temporal sampling regimes to track shifts in diet, both seasonally (ice cover, ice break-up, and open water), and spatially among lagoons along the Alaskan Beaufort Sea coast. Ice coring, net tows, ponar grabs, and trawls are employed to collect organisms associated with the sea-ice interface, the water column, and the benthos respectively. Tissues are analyzed for stable isotopic composition as well as organic carbon and nitrogen content.
Ice core, auger hole, conductivity, and shapefile data to determine bottomfast sea ice extent from lagoon sites along the Beaufort Sea Coast, Alaska, 2017-2021
The shapefile represents bottomfast sea ice (BSI) extent in lagoons along the Alaska Beaufort Sea coast during winter and spring, 2017-2021. It was created by digitizing extents from interferograms from the Alaska Satellite Facility Vertex portal. The result is used to identify BSI lateral extent in Arctic lagoons during the growth cycle seasonally. Comparing to future interferograms will identify the trend of BSI within Arctic lagoons. Each feature is attributed with applicable date range and area. Accurate data for the initial growth and maximum extent of BSI could only be collected for the winter and spring months. After the last collection in the spring, there is likely still BSI; however, the surface processes that take place after this point prevent further readings. For early winter time periods, if there are interferograms available (2017 and 2018 data had gaps in interferogram collection as Sentinel-1 was still new), the first date collected can be considered the onset of BSI formation. Ice cores are collected using a Snow, Ice, and Permafrost Research Establishment (SIPRE) corer and measured for salinity. The data is logged in Excel format following Seasonal Ice Zone Observing Network (SIZONet) practices, making it compatible with the PySIC Python toolkit for analysis. The auger data identifies key measurements collected from in-situ observations. Data are collected along five surveys and saved as a single CSV file. The data represent a 1-D representation of each auger hole. The data are used to verify satellite interpretations of BSI extent. The apparent conductivity data includes values at three frequencies (1000 Hz, 4000 Hz, 16000 Hz) recorded during the spring of 2021 in Western Elson Lagoon. Data are saved as an EMI file, which is a CSV format with specific column names and header information. MATLAB scripts to read and interpret data are included in this data package. The apparent conductivity values are used to identify the boundary between floating
Physiochemical water column parameters and hydrographic time series from river, lagoon, and open ocean sites along the Alaska Beaufort Sea coast, 2018-ongoing
To understand circulation and seasonality as part of the Beaufort Lagoon Ecosystem Long Term Ecological Research program, temperature, conductivity, salinity, pressure, depth, and current velocity are recorded hourly in situ, starting August 2018 in lagoons across the Beaufort Sea coast (Elson Lagoon, Kaktovik Lagoon, and Jago Lagoon). Moorings include combinations of 1) RBR Concerto CTDs with temperature, conductivity, and pressure sensors; 2) StarOddi CTs with temperature and conductivity sensors; and 3) Lowell TCM-1 Tilt Current meters with MAT-1 Data Loggers for velocity and bearing. In addition, during BLE LTER's annual sampling, water column physiochemical parameters (chlorophyll a, dissolved oxygen, phycoerythrin concentration, pH, temperature, conductivity, salinity) are measured by hand with a YSI data sonde at river, lagoon, and open ocean sites along the Beaufort Sea coast. Here we provide both quality controlled in situ mooring data and all YSI sonde data.
Total suspended solids from river, lagoon, and open ocean sites along the Alaska Beaufort Sea coast, 2022-ongoing
Multiple water types (river, lagoon, ocean) from the North Slope of Alaska and nearshore Beaufort Sea are sampled seasonally by the Beaufort Lagoon Ecosystems LTER (BLE LTER) Core Program to investigate biogeochemical linkages between terrestrial, lagoon, and open ocean ecosystems. Water samples from multiple depths are collected during full ice cover (April), ice break-up (mid-June to early July), and open water (late July and August) periods for quantification of total suspended solids and total organic suspended solids. Concentrations are reported in milligrams per liter of filtered seawater (mg/L).
Yearly survey of barnacle settlement near creekbank plots at GCE LTER study sites in October 2013
To characterize spatial variation in barnacle recruitment at the creekbank, and across a gradient in salinity and distance to ocean, we deployed PVC poles to passive sample barnacle settlement. Eight poles were deployed between 4-5m apart adjacent to the creekbank vegetation monitoring plots at each GCE LTER permanent monitoring site each Fall beginning in 2012. These poles were then collected the following Fall and all barnacle that settled on the poles were identified and counted on 50cm-long sections of the 8, 3/4" diameter PVC poles. Although a few other barnacle species are occur within this estuary, only Chthamalus fragilis settled on the poles.
Long-term mid-marsh grasshopper abundance and species diversity at eight GCE-LTER sampling sites
Grasshopper abundance and species diversity were investigated at eight sampling sites within the Georgia Coastal Ecosystems (GCE) LTER study area during July or August from 2000 to 2023. Visual surveys were conducted along 8-10 2m by 10m transects randomly allocated within the mid-marsh zone at each site. All grasshoppers observed within each transect were counted and identified to species, if possible. These surveys were conducted as part of the GCE invertebrate monitoring program, and are performed annually to assess long-term changes in relative species abundances across the GCE study area.
Mollusc population abundance monitoring: Fall 2016 mid-marsh and creekbank infaunal and epifaunal mollusc abundance based on collections from GCE marsh, monitoring sites 1-10
This data set is the Fall 2016 estimate of infaunal and epifaunal mollusc abundance at the GCE-LTER marsh sites used for population monitoring. Species abundance was determined by hand-collecting all the infaunal and epifaunal molluscs from within quadrats of known area in mid-marsh and creekbank zones (n = 4 quadrats per zone) at all sites. The molluscs were returned to the lab, fixed in ethanol, transferred to and preserved in ethanol, counted and measured (size data is reported separately). The counts were converted to number per square meter. Gastropod species are listed first, followed by bivalve species. Size distribution data for these collections may be found in the GCE-LTER data set INV-GCEM-1707a.
Mollusc population size distribution monitoring: Fall 2016 mid-marsh and creekbank infaunal and epifaunal mollusc size distributions based on collections from GCE marsh monitoring sites 1-10
This data set is the Fall 2016 report of infaunal and epifaunal mollusc species size distributions at the GCE-LTER marsh sites used for population monitoring. Infaunal and epifaunal molluscs were hand-collected from within quadrats of known area from mid-marsh and creekbank zones (n = 4 quadrats per zone) at all sites. The molluscs were returned to the lab, preserved in ethanol, measured and counted (count data is reported separately). Length of each measurable individual was determined using calipers or an ocular micrometer mounted in a stereomicroscope. Species abundance and density data for these collections may be found in the GCE-LTER data set INV-GCEM-1707. Numbers of individuals of each species in the abundance data file may not correspond exactly to the numbers of individuals in the size data file because some individuals may not have been measureable.
Yearly survey of barnacle settlement near creekbank plots at GCE LTER study sites in October 2014
To characterize spatial variation in barnacle recruitment at the creekbank, and across a gradient in salinity and distance to ocean, we deployed PVC poles to passive sample barnacle settlement. Eight poles were deployed between 4-5m apart adjacent to the creekbank vegetation monitoring plots at each GCE LTER permanent monitoring site each Fall beginning in 2012. These poles were then collected the following Fall and all barnacle that settled on the poles were identified and counted on 50cm-long sections of the 8, 3/4" diameter PVC poles. Although a few other barnacle species are occur within this estuary, only two species settled on poles: Chthamalus fragilis and Balanus spp.
Yearly survey of barnacle settlement near creekbank plots at GCE LTER study sites in October 2015
To characterize spatial variation in barnacle recruitment at the creekbank, and across a gradient in salinity and distance to ocean, we deployed PVC poles to passive sample barnacle settlement. Eight poles were deployed between 4-5m apart adjacent to the creekbank vegetation monitoring plots at each GCE LTER permanent monitoring site each Fall beginning in 2012. These poles were then collected the following Fall and all barnacle that settled on the poles were identified and counted on 50cm-long sections of the 8, 3/4" diameter PVC poles. Although a few other barnacle species are occur within this estuary, only two species settled on poles: Chthamalus fragilis and Balanus spp.
Yearly survey of barnacle settlement near creekbank plots at GCE LTER study sites in October 2016
To characterize spatial variation in barnacle recruitment at the creekbank, and across a gradient in salinity and distance to ocean, we deployed PVC poles to passive sample barnacle settlement. Eight poles were deployed between 4-5m apart adjacent to the creekbank vegetation monitoring plots at each GCE LTER permanent monitoring site each Fall beginning in 2012. These poles were then collected the following Fall and all barnacle that settled on the poles were identified and counted on 50cm-long sections of the 8, 3/4" diameter PVC poles. Although a few other barnacle species are occur within this estuary, only two species settled on poles: Chthamalus fragilis and Balanus spp.
Yearly survey of barnacle settlement near creekbank plots at GCE LTER study sites in October 2017
To characterize spatial variation in barnacle recruitment at the creekbank, and across a gradient in salinity and distance to ocean, we deployed PVC poles to passive sample barnacle settlement. Eight poles were deployed between 4-5m apart adjacent to the creekbank vegetation monitoring plots each GCE LTER permanent monitoring site each Fall beginning in 2012. These poles were then collected the following Fall and all barnacle that settled on the poles were identified and counted on 50cm-long sections of the 8, 3/4" diameter PVC poles. Although a few other barnacle species are occur within this estuary, only two species settled on poles: Chthamalus fragilis and Balanus spp.
Yearly survey of barnacle settlement near creekbank plots at GCE LTER study sites in October 2018
To characterize spatial variation in barnacle recruitment at the creekbank, and across a gradient in salinity and distance to ocean, we deployed PVC poles to passive sample barnacle settlement. Eight poles were deployed between 4-5m apart adjacent to the creekbank vegetation monitoring plots each GCE LTER permanent monitoring site each Fall beginning in 2012. These poles were then collected the following Fall and all barnacle that settled on the poles were identified and counted on 50cm-long sections of the 8, 3/4" diameter PVC poles. Although a few other barnacle species are occur within this estuary, only two species settled on poles: Chthamalus fragilis and Balanus spp. This year Geukensia and Oysters that settled on the poles were counted and recorded.
Yearly survey of barnacle settlement near creekbank plots at GCE LTER study sites in October 2019
To characterize spatial variation in barnacle recruitment at the creekbank, and across a gradient in salinity and distance to ocean, we deployed PVC poles to passive sample barnacle settlement. Eight poles were deployed between 4-5m apart adjacent to the creekbank vegetation monitoring plots at each GCE LTER permanent monitoring site each Fall beginning in 2012. These poles were then collected the following Fall and all barnacle that settled on the poles were identified and counted on 50cm-long sections of the 8, 3/4" diameter PVC poles. Four species settled on poles and were counted and recorded: Chthamalus fragilis, Balanus spp., Geukensia demissa, and Oysters (Crassostrea virginica).
Yearly survey of barnacle settlement near creekbank plots at GCE LTER study sites in October 2020
To characterize spatial variation in barnacle recruitment at the creekbank, and across a gradient in salinity and distance to ocean, we deployed PVC poles to passive sample barnacle settlement. Eight poles were deployed between 4-5m apart adjacent to the creekbank vegetation monitoring plots at each GCE LTER permanent monitoring site each Fall beginning in 2012. These poles were then collected the following Fall and all barnacle that settled on the poles were identified and counted on 50cm-long sections of the 8, 3/4" diameter PVC poles. Four species settled on poles and were counted and recorded: Chthamalus fragilis, Balanus spp., Geukensia demissa, and Oysters (Crassostrea virginica).
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.