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3,846 results for “2023”
PIE LTER 10-minute marsh water table height at Nelson Island, Rowley, MA from May-November 2023.
Measurements of water table height in the Nelson Island marsh located near the Nelson Island eddy flux tower, Rowley, MA. Measurements were taken every 10 minutes at each logger along a transect of water level loggers running perpendicular to the Nelson stream bank at Nelson Island from May-November 2023.
Migratory shorebird habitat use, diet, and prey selection on mudflats in the Virginia barrier island and lagoon system, 2023-2024
Migratory shorebirds require access to heterogenous resources during migration. Understanding how shorebirds utilize different foraging substrates and food resources across the coastal landscape is important for informing conservation. We compared shorebird habitat use and invertebrate prey communities between barrier island and mudflat foraging substrates. We counted shorebirds and collected prey samples at random points on sand, peat, and mudflat substrates during spring migration (May 14 - June 2), 2023 - 2024. We opportunistically collected fecal samples on mudflats in our study area and used fecal DNA metabarcoding with 18S (invertebrates) and 23S (biofilm) primers to describe the diets of dunlin (Calidris alpina), red knots (Calidris canutus rufa) and semipalmated sandpipers (Calidris pusilla). We then used network null modeling to determine if our focal species were selectively consuming invertebrates on mudflats. Peat banks were the most heavily used intertidal substrate and mudflats supported similar shorebird abundances and species richness to sand. Dunlin and semipalmated sandpipers were more abundant on peat and mudflats, while red knots were more abundant on sand and peat. Invertebrate density was highest on peat banks and similar between mudflat and sand substrate, though mudflats supported a more diverse prey community. Amphipod crustaceans, blue mussels (Mytilus edulis), and polychaete worms were main prey consumed by all species on mudflats. Dunlin and semipalmated sandpipers fed primarily on crustaceans whereas red knots mainly fed on bivalves. All species consumed biofilm and a high proportion of diatoms were observed in fecal samples collected from semipalmated sandpipers. Red knots and dunlin selectively consumed bivalves on mudflats while semipalmated sandpipers showed no dietary preferences. Managing staging sites to preserve a diversity of intertidal habitats is critical for meeting the variable foraging requirements of migratory shorebirds.
Testing of a benthic incubation chamber design in a Virginia coastal bay, 2023, 2024, and 2025
Benthic incubation chambers enclose a known volume of water overlying a known area to measure water chemistry changes and are typically used to quantify the metabolic activity of benthic organisms or communities. Here, we report data from a series of tests validating a new benthic incubation chamber design. This data includes dissolved oxygen (DO) concentrations and temperatures recorded during three test deployments in South Bay, Virginia during August 2023 (T1_chamber_do_test_data), as well as data from light transmission tests. Light transmission tests included per wavelength transmission of PAR and ultraviolet radiation through the chamber wall (T2_wall_transmission_test) and lid (T3_lid_transmission_test), an in-situ PAR transmission comparison for two different sensor arrangements (side-mounted versus top-mounted) during July 2025 (T4_sensor_shading_test), and an in-situ comparison of natural ambient PAR versus PAR translated through a deployed chamber during March 2024 (T5_in_situ_light_test).
PolarFront cruise 2023-08 ship logs from Helmer Hanssen
<p><strong>PolarFront 2023-08 ship logs</strong> </p><p>Original (ISO 8859-1 encoded) text files from the ship logger on Helmer Hanssen.</p>
BASE DE DATOS CON DIMENSIONES Y SUBDIMENSIONES CECAPEU 2023 para perfiles en manejo competencia AaA.sav
<p>Base de datos de 1234 sujetos de tres universidades de la ciudad de Valencia, dos públicas (Universidad de Valencia y Universidad Politécnica de Valencia), y una privada (Universidad Católica de Valencia).</p><p>La base de datos se utilizó para analizar los perfiles en el manejo de la competencia "aprender a aprender" de uma muestra de alumnos universitarios lo suficientemente representativa.</p><p>La base de datos, en SPSS 26.0, está integrada por 49 variables, siendo las cinco primeras nominales (Universidad, Facultad, Titulación, Curso, Sexo), la sexta ordinal (Edad), y las variables 8 a la 11 de escala, con valores que pueden oscilar de 0 a 10 (son calificaciones) y las restantes escalares. Desde de la variable 12 a la 49 son puntuaciones de escala, con valores que van de 1 (máximo desacuerdo) a 5 (máximo acuerdo) (se trata de puntuaciones medias de sumatorio de ítems integrantes de cada dimensión; los ítems de los que emergen tenían puntuación que oscilaba de 1 -máximo desacuerdo- a 5 máximo acuerdo-). Estas variables son puntuaciones de dimensiones y subdimensiones del cuestionario CECAPEU, que evalúa el aprendizaje de la competencia "aprender a aprender" del alumnado universitario. </p><p>En el fichero que se ha subido, en txt, junto a la base de datos, se explican las variables y otras cuestiones relativas a la base de datos.</p>
EOSC Task Force on FAIR Metrics and Data Quality: FAIR Evaluation community survey 2023
<p>The EOSC-A FAIR Metrics and Data Quality Task Force (TF) supported the European Open Science Cloud Association (EOSC-A) by providing strategic directions on FAIRness (Findable, Accessible, Interoperable, and Reusable) and data quality. The Task Force conducted a survey using the <a href="https://ec.europa.eu/eusurvey/">EUsurvey tool</a> between 15.11.2022 and 18.01.2023, targeting both developers and users of FAIR assessment tools. The survey aimed at supporting the harmonisation of FAIR assessments, in terms of what it evaluated and how, across existing (and future) tools and services, as well as explore if and how a community-driven governance on these FAIR assessments would look like. The survey received 78 responses, mainly from academia, representing various domains and organisational roles. This is the anonymised survey dataset in csv format; most open-ended answers have been dropped. The codebook contains variable names, labels, and frequencies.</p>
Datasets for: Generalizing Monin-Obukhov Similarity Theory (1954) for Complex Atmospheric Turbulence, Stiperski and Calaf 2023, PRL
<p>Scaling variables for the generalized flux-variance scaling relations that include turbulence anisotropy. Dataset is a companion to the manuscript Stiperski, I., Calaf, M., 2023: Generalizing Monin-Obukhov similarity theory (1954) for complex atmospheric turbulence. Physical Review Letters, 130 (12), 124001, https://doi.org/10.1103/PhysRevLett.130.124001</p> <p>The dataset contains the turbulence statistics from 13 datasets: AHATS, Cabauw, CASES-99, METCRAX II campaign (NEAR and RIM towers), T-Rex campaign (Central tower - TRexC, West tower - TRexW) and i-Box measurement network (CCS-VF0 tower - i-Box0, CS-SF1 tower - i-Box1, CS-NF10 tower - i-Box10, CS-NF27 tower - i-Box27, CS-MT21 tower - i-BoxTop, im Hinteren Eis tower - imHint).</p> <p><br>Data are organized in csv files for each datasets and only contain high quality (for applied criteria see the Supplemental Material of the companion paper, https://journals.aps.org/prl/supplemental/10.1103/PhysRevLett.130.124001) data with 30 min averaging for unstable stratification and 1 min for stable stratification. Since the data were used for scaling, there is no reference to time, but the measurement height is provided as an additional variable. </p> <p>Meaning of variables:</p> <p>zeta - z/L where z is height above ground and L is the local Obukhov length</p> <p>SigmaU - $\overline{u'u'}/u_*$ scaled standard deviation of streamwise velocity, where $u_*$ is the local friction velocity</p> <p>SigmaU - $\overline{v'v'}/u_*$ scaled standard deviation of spanwise velocity</p> <p>SigmaU - $\overline{v'v'}/u_*$ scaled standard deviation of surface-normal velocity</p> <p>SigmaT - $\overline{T'T'}/T_*$ scaled standard deviation of sonic temperature, where $T_*$ is the local temperature scale</p> <p>SigmaEpsU - scaled dissipation rate of the streamwise velocity</p> <p>SigmaEpsW - scaled dissipation rate of the surface-normal velocity </p>
Meiobenthos GeoEcoMar DOORS 2023
<p>The dataset contains the taxonomic and quantitative analysis of meiobenthic samples (free-living nematodes and harpacticoida groups), collected within the DOORS Leg 1 cruise carried out within 1-10 September 2023 in the framework of Horizon 2020 Project ‘Developing Optimal and Open Research Support for the Black Sea’ (DOORS). The samples have been collected with a Multiple Corer Mark II device. 3 out of the 6 samples that contain in their ID the word "inc" represent the incubated cores (for fluxes experiments), while the other 3 the "control" samples collected in the same station. The latter were washed through a 63 µm mesh sieve on board and preserved in buffered formaldehyde 4% for further laboratory analysis (Giere, 2009)</p>
Data from Phenocam (PHE) measurements at Freiburg–Chemiehochhaus (FRCHEM) from 2023-07-04 to 2023-12-31 [RAW]
<p>Original phenocam images separated into near-infrared (NIR) and visible (VIS).</p>
Quantitative Assessment of Research Data Management Practices - 2023
<p>This survey investigates <strong>Research Data Management (RDM) practices across five Swiss higher education institutions</strong>, including EPFL, ETH Zürich, Eawag, FHNW, and DaSCH, with the goal of gathering insights into how researchers manage data and code throughout the lifecycle of their projects, as well as using such findings to inform academic services related to RDM for researchers. Previous surveys, conducted at EPFL in 2017, 2019, and 2021, primarily focused on the planning and publishing stages of the research data lifecycle, such as data management planning and open data dissemination. The 2023 edition expanded to other institutes and places a stronger emphasis on <strong>Active Data Management</strong>, particularly during research projects, including a range of topics such as:</p> <ul> <li>Storage and backup solutions</li> <li>Data and code sharing platforms</li> <li>Documentation and metadata usage</li> <li>Compliance with legal and ethical standards</li> <li>Long-term data preservation strategies</li> <li>Use of open formats and open-source software</li> <li>Adoption of Data Management Plans (DMPs)</li> </ul> <p>This dataset was collected using the SurveyHero platform in compliance with GDPR and Swiss FADP regulations. enuvo GmbH acted as the data processor under a signed Data Processing Agreement. No personal identifiable information was purposefully collected, and data has been aggregated to further ensure respondents’ privacy.</p> <p>Included in this dataset:</p> <ul> <li>A CSV and XLSX file with the aggregated, anonymized data from the survey.</li> <li>Two PDF files containing graphical representations of the survey results, automatically generated by the SurveyHero platform in portrait and landscape mode.</li> <li>A README file providing context.</li> </ul> <p>This dataset is made openly available under the CC-BY 4.0 license. Users are encouraged to reuse it with appropriate attribution.</p>
Data from Phenocam (PHE) measurements at Paris – Romainville (PAROMA) from 2023-09-26 to 2023-12-31 [RAW]
<p>Original phenocam images separated into near-infrared (NIR) and visible (VIS).</p>
Data from Phenocam (PHE) measurements at Paris – SIRTA (PASIRT) from 2023-04-26 to 2023-12-31 [RAW]
<p>Original phenocam images separated into near-infrared (NIR) and visible (VIS).</p>
Data from Phenocam (PHE) measurements at Heraklion – FORTH (HEFORT) from 2023-03-24 to 2023-12-31 [RAW]
<p>Original phenocam images separated into near-infrared (NIR) and visible (VIS).</p>
Data from Phenocam (PHE) measurements at Berlin-Technical University of Berlin (BETUCC) from 2023-06-01 to 2023-12-31 [RAW]
<p>Original phenocam images separated into near-infrared (NIR) and visible (VIS).</p>
Data from Phenocam (PHE) measurements at Berlin – Rothenburgstrasse (BEROTH) from 2023-01-01 to 2023-12-31 [RAW]
<p>Original phenocam images separated into near-infrared (NIR) and visible (VIS).</p>
Physical oceanography and meteorological data from the W1M3A observatory, Ligurian Sea (North Western Mediterranean) October 2023 - May 2024
<p>Time series data of physical oceanography (salinity, temperature) and meteorology (atmospheric pressure, wind speed and direction, air temperature and humidity, shortwave radiation, longwave radiation and rain) collected from October 2023 up to May 2024 by observatory W1M3A at 1h interval. The file contains tabular data (tab delimited) with the following columns: TIME in UTC [yyyy-MM-ddThh:mm:ssZ]; Latitude [deg]; Longitude [deg]; nominal depth [m]; Atmospheric Pressure [hPa]; Wind speed [m/s]; Wind direction [deg]; Air Temperature [°C]; Relative air humidity [%]; Short wave Radiation [W/m2]; Long wave radiation [W/m2]; Rainfall [mm/h]; Sea temperature [°C]; Conductivity [mmS/cm]. Missing data are defined as NaN.</p>
EISCAT Svalbard radar Common Program data from February 26 to February 28 2023, which is processed by GUISDAP
<p>This is two-dimensional (time and altitude) ionospheric parameter data that contains electron density, electron temperature and ion temperature. It is estimated based on EISCAT Svalbard radar measurement implemeted as common program from February 26 to Feburuary 28, 2023 (https://portal.eiscat.se/) and processed by a software for incoherent scatter radar analysis, GUISDAP (https://gitlab.com/eiscat/guisdap9). The more detailed descriptions can be found as metadata in the uploaded netCDF file.</p>
Air temperature measurements from Automatic Weather Station (AWS) at Freiburg – Chemiehochhaus (FRCHEM) from 2023-01-01 to 2023-12-31 [L2]
<p>Quality controlled and gap-filled continuous air temperature data from the urban rooftop weather station at Freiburg-Chemiehochhaus (FRCHEM, 7.8486ºE, 48.0011ºN, 323.5 m) using an actively ventillated and shielded psychrometer operated 2m above roof level.</p> <ul> <li>Quality controlled air temperature data are available and aggregated at 10min, 30min, hourly, daily, monthly and yearly resolution for the year 2023.</li> <li>Average, minimum and maximum air temperatures are provided on hourly, daily, monthly and annual scales.</li> <li>Characteristic hours and days are reported on daily, monthly and annual scales (e.g. summer days with T_max > 25ºC, hot days with T_max > 30º, desert days with T_max > 35ºC, tropical nights with T_min > 20°, frost days with T_min < 0ºC and ice days with T_max < 0ºC, all based on 00:00 - 24:00 UTC).</li> <li>Detailed information on gap-filled data is provided.</li> <li>Note: All times are provided in UTC, not local time.</li> </ul> <p>For more details read `FRCHEM_2023_AirTemperature_MetaData.txt`.</p> <p>Version 1.1.0 contains additionally air temperature data aggregated at 10min and 30min.</p>
Air temperature measurements from Automatic Weather Station (AWS) at Freiburg – Werthmannstrasse (FRWRTM) from 2023-01-01 to 2023-12-31 [L2]
<p>Quality controlled and gap-filled continuous air temperature data from the urban weather station at Freiburg-Werthmannstrasse (FRWRTM, 7.8447ºE, 47.9928, 277 m) using a passively ventilated and shielded temperature and humidity probe (Campbell Scientific Inc., CS 215) operated in a Stevenson Screen 2m above ground level in the vegetated backyard of Werthmannstrasse 10.</p> <ul> <li>Quality controlled in-canopy air temperature data are available and aggregated at 10min, 30min, hourly, daily, monthly and yearly resolution for the year 2023.</li> <li>Average, minimum and maximum in-canopy air temperatures are provided on hourly, daily, monthly and annual scales.</li> <li>Characteristic hours and days are reported on daily, monthly and annual scales (e.g. summer days with T_max > 25ºC, hot days with T_max > 30º, desert days with T_max > 35ºC, tropical nights with T_min > 20°, frost days with T_min < 0ºC and ice days with T_max < 0ºC, all based on 00:00 - 24:00 UTC).</li> <li>Detailed information on gap-filled data is provided.</li> <li>Note: All times are provided in UTC, not local time.</li> </ul> <p>For more details read `FRWRTM_2023_AirTemperature_MetaData.txt`.</p> <p>Version 1.1.0 contains additionally air temperature data aggregated at 10min and 30min.</p>
Global Meteor Network observations of Crew-5 Dragon trunk re-entry 2023-04-27
<p>This dataset contains video observations by some stations of the Global Meteor Network of the re-entry of the Crew-5 dragon trunk above Arizona on 2023-04-27 around 08:52 UTC.</p> <p>There are several types of files:</p> <ul> <li>FF files: these are 10.24 second videos compressed in the four-frame format. They are just FITS files with four frames, containing per pixel 1) the maximum value over 256 frames 2) the frame nr (between 0 and 255) where the maximum occurred 3) the mean value of all 256 frames and 4) the RMS of the 256 values.</li> <li>FR files: compressed video recordings of detected fireballs. These can be read with the RMS software.</li> <li>MP4 files: rendered movies of combined FF and FR files for one station (more can be made with FR_binviewer from RMS software).</li> <li>Platepar-files: these contain astrometry corresponding to the FITS files. These can be interpreted by the RMS software.</li> <li>ECSV files: these contain manually picked points (with SkyFit2.py from RMS) along the track of the reentry. For each point, time and apparent coordinates are recorded. These files can be interpreted by the WesternMeteorPyLib trajectory solver.</li> <li>trajectory-points.txt: solutions from the trajectory solver.</li> <li>reentry-map-v4.png: a rendered map of the trajectory (made in QGIS).</li> <li>compilation.png: rendered version of the FF-files of most stations.</li> </ul> <p>The files can be processed with the software in https://github.com/CroatianMeteorNetwork/RMS and https://github.com/wmpg/WesternMeteorPyLib.</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.