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109 results for “year 2020”
FIG. 5 in State of the Amphibia 2020: A Review of Five Years of Amphibian Research and Existing Resources
FIG. 5. Phylogenetic heat map showing the number and proportion of species within each family that were described in 2016–2020 and the proportion of species within each family that have accessible phenotypic, genetic, and disease data. Lighter to darker colored matrix cells represent lower to higher specieslevel representation for each family and white cells indicate that no species from the corresponding family have those data types available. From left to right in the matrix: 1) the proportion of new species added in 2016–2020, 2) the proportion of species with call data available in one of the seven databases listed in Table 1, 3) the proportion of species with microCT data available on MorphoSource or Phenome10K, 4) the proportion of species with sequenced genomes, 5) the proportion of species with sequences in NCBI GenBank, 6) the proportion of species with sequences in the NCBI Sequence Read Archive, 7) the proportion of species in the Amphibian Disease Portal that have been tested for Bd, 8) the proportion of species in that have positive tests for Bd documented in the Amphibian Disease Portal. Data used to generate this figure can be found in Table S5 (see Data Accessibility).
FIG. 9 in State of the Amphibia 2020: A Review of Five Years of Amphibian Research and Existing Resources
FIG. 9. Samples of BatraChOChytriUM dendrObatidiS in the Amphibian Disease Portal. (A) A log-scale histogram of Bd swab counts, binned by the five-year time span in which the amphibian swabbed was captured. (B) A stacked histogram showing the proportional representation of swabs taken from different continents, binned by the same five-year blocks. Bsal data archived in the portal only includes sample data in the US (Waddle et al., 2020) and from the Bsal Consortium Germany (Vences and Lötters, 2020).
Horizon 2020 ER4STEM workshop data Year 1-3 UK
<p>This dataset was collected as part of the Educational Robotics for STEM (ER4STEM) project, funded by the European Commision's Horizon 2020 programme, grant agreement No. 665792. The dataset includes quantitative and qualitative data collected over 3 years of robotics workshops held in schools in the UK. Only data with informed consent to be shared via an open access repository is included. Only anonymised data is included and some data is excluded to project vulnerable participants. </p>
Horizon 2020 ER4STEM workshop data Year 1-3 Bulgaria
<p>This dataset was collected as part of the Educational Robotics for STEM (ER4STEM) project, funded by the European Commission’s Horizon 2020 programme, grant agreement No. 665792. The dataset includes quantitative and qualitative data collected over 3 years of robotics workshops held in schools in Bulgaria. Only data with informed consent to be shared via an open access repository is included. Only anonymised data is included and some data is excluded to protect vulnerable participants.</p>
Horizon 2020 ER4STEM workshop data Year 1-3 Austria-TU Wien
<p>This dataset was collected as part of the Educational Robotics for STEM (ER4STEM) project, funded by the European Commission’s Horizon 2020 programme, grant agreement No. 665792. The dataset includes quantitative and qualitative data collected over 3 years of robotics workshops held in the Technical University Wien in Austria. Only data with informed consent to be shared via an open access repository is included. Only anonymised data is included and some data is excluded to protect vulnerable participants.</p>
Horizon 2020 ER4STEM workshop data Year 1-3 Greece_UoA
<p>This dataset was collected as part of the Educational Robotics for STEM (ER4STEM) project, funded by the European Commision's Horizon 2020 programme, grant agreement No. 665792. The dataset includes quantitative and qualitative data collected over 3 years of robotics workshops held in schools in Greece by UoA. Only data with informed consent to be shared via an open access repository is included. Only anonymised data is included and some data is excluded to project vulnerable participants. </p>
Horizon 2020 ER4STEM workshop data Year 1-3 Austria-PRIA
<p>This dataset was collected as part of the Educational Robotics for STEM (ER4STEM) project, funded by the European Commission’s Horizon 2020 programme, grant agreement No. 665972. The dataset includes quantitative and qualitative data collected over 3 years of<br> robotics workshops held in schools in Austria. Only data with informed consent to be shared via an open access repository is included. Only anonymised data is included and some data is excluded to protect vulnerable participants.</p>
Horizon 2020 ER4STEM workshop data Year 1-3 : Malta
<p>The dataset was collected as part of the Educational Robotics for STEM (ER4STEM) project, funded by the European Commission's Horizon 2020 programme, grant agreement No. 665792. The dataset includes quantitative and qualitative data collected over 3 years of robotics workshops held in schools in Malta. Only data with informed consent to be shared via an open access repository is included. Only anonymised data is included and some data is excluded to protect vulnerable participants.</p>
Grassland mowing events across Germany detected from combined Sentinel-2 and Landsat 8 time series for the years 2017 - 2020
<p>Grasslands provide a wide range of important ecosystem services. Mapping and assessing the status and use intensity of grasslands is thus important for environmental monitoring. We here provide maps with detected mowing events, as a proxy for grassland use intensity, for grassland areas across Germany for the years 2017 to 2020.</p> <p>The algorithm used to derive the maps is described in Schwieder, et al. (accepted) and is available as a user-defined function for the FORCE (Frantz, D., 2019) environment (https://github.com/davidfrantz/force-udf/tree/main/python/ts/mowingDetection). The here provided GeoTiffs contain a band with the number of detected mowing events per pixel for the repsective year. In the products, only stable grassland areas that were consistently classified as grassland within three years (2017 - 2019) were considered, based on crop maps provided by Blickensdörfer et al. (2021). Note that grassland uses (pasture, mowed, mixed) were not separated prior to analysis. The maps for 2018, 2019, and 2020 were validated in different regions of Germany, with accuracies - in terms of Mean Absolute Percentage Error - ranging from 35% to 40% (for more details see Schwieder et al. accepted). The maps may thus give an indication of extensively or intensively grassland use.</p> <p>Please contact the authors, if you are interested in additional products e.g., regarding the estimated mowing dates.</p> <p>All satellite data were downloaded, pre-processed and structured in an analysis-ready data (ARD) cube using the open-source software FORCE - Framework for Operational Radiometric Correction for Environmental monitoring (Frantz, D., 2019; https://force-eo.readthedocs.io/en/latest/ last accessed: 15. October 2021).</p> <p> </p> <p>References:</p> <p>Blickensdörfer, L., Schwieder, M., Pflugmacher, D., Nendel, C., Erasmi, S., & Hostert, P.. (2021). National-scale crop type maps for Germany from combined time series of Sentinel-1, Sentinel-2 and Landsat 8 data (2017, 2018 and 2019) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.5153047 </p> <p>Frantz, D. (2019). FORCE—Landsat + Sentinel-2 Analysis Ready Data and Beyond. Remote Sensing, 11, 1124.</p> <p>Schwieder, M., Wesemeyer, M., Frantz, D., Pfoch, K., Erasmi, S., Pickert, J., Nendel, C., & Hostert, P. (2022). Mapping grassland mowing events across Germany based on combined Sentinel-2 and Landsat 8 time series. Remote Sensing of Environment, 269, 112795.</p> <p><a href="https://zenodo.org/record/5571613">Grassland mowing events across Germany</a> © 2022 by Schwieder, Marcel; Wesemeyer, Maximilian; Frantz, David; Pfoch, Kira; Erasmi, Stefan; Pickert, Jürgen; Nendel, Claas; Hostert, Patrick is licensed under <a href="http://creativecommons.org/licenses/by/4.0/?ref=chooser-v1">CC BY 4.0. </a></p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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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.