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8,375 results for “nationalism”
Herbarium specimen image of Ficus trichoclada Baker, part of the collection of National Museum of Natural History, Paris
Part of a training dataset of scanned herbarium specimens. The data paper and a summary landing page will be published on Zenodo as it gets published.<br><br>Content of this deposition:<br><br>- A JSON-LD datafile listing the label data associated with this herbarium specimen. The Darwin and Dublin Core data standards are used for most values.<br>- A JPEG image file of the scanned herbarium sheet.
Herbarium specimen image of Hyparrhenia bagirmica Stapf, part of the collection of National Museum of Natural History, Paris
Part of a training dataset of scanned herbarium specimens. The data paper and a summary landing page will be published on Zenodo as it gets published.<br><br>Content of this deposition:<br><br>- A JSON-LD datafile listing the label data associated with this herbarium specimen. The Darwin and Dublin Core data standards are used for most values.<br>- A JPEG image file of the scanned herbarium sheet.
Herbarium specimen image of Rhus cotinus L., part of the collection of National Museum of Natural History, Paris
Part of a training dataset of scanned herbarium specimens. The data paper and a summary landing page will be published on Zenodo as it gets published.<br><br>Content of this deposition:<br><br>- A JSON-LD datafile listing the label data associated with this herbarium specimen. The Darwin and Dublin Core data standards are used for most values.<br>- A JPEG image file of the scanned herbarium sheet.
Herbarium specimen image of Minuartia L., part of the collection of National Museum of Natural History, Paris
Part of a training dataset of scanned herbarium specimens. The data paper and a summary landing page will be published on Zenodo as it gets published.<br><br>Content of this deposition:<br><br>- A JSON-LD datafile listing the label data associated with this herbarium specimen. The Darwin and Dublin Core data standards are used for most values.<br>- A JPEG image file of the scanned herbarium sheet.
Herbarium specimen image of Clematis hirsuta Guill. & Perr., part of the collection of National Museum of Natural History, Paris
Part of a training dataset of scanned herbarium specimens. The data paper and a summary landing page will be published on Zenodo as it gets published.<br><br>Content of this deposition:<br><br>- A JSON-LD datafile listing the label data associated with this herbarium specimen. The Darwin and Dublin Core data standards are used for most values.<br>- A JPEG image file of the scanned herbarium sheet.
Herbarium specimen image of Phyllarthron megaphyllum Capuron, part of the collection of National Museum of Natural History, Paris
Part of a training dataset of scanned herbarium specimens. The data paper and a summary landing page will be published on Zenodo as it gets published.<br><br>Content of this deposition:<br><br>- A JSON-LD datafile listing the label data associated with this herbarium specimen. The Darwin and Dublin Core data standards are used for most values.<br>- A JPEG image file of the scanned herbarium sheet.
Herbarium specimen image of Carduus defloratus L., part of the collection of National Museum of Natural History, Paris
Part of a training dataset of scanned herbarium specimens. The data paper and a summary landing page will be published on Zenodo as it gets published.<br><br>Content of this deposition:<br><br>- A JSON-LD datafile listing the label data associated with this herbarium specimen. The Darwin and Dublin Core data standards are used for most values.<br>- A JPEG image file of the scanned herbarium sheet.
Herbarium specimen image of Eleocharis palustris (L.) Roem. & Schult., part of the collection of National Museum of Natural History, Paris
Part of a training dataset of scanned herbarium specimens. The data paper and a summary landing page will be published on Zenodo as it gets published.<br><br>Content of this deposition:<br><br>- A JSON-LD datafile listing the label data associated with this herbarium specimen. The Darwin and Dublin Core data standards are used for most values.<br>- A JPEG image file of the scanned herbarium sheet.
Herbarium specimen image of Anthriscus caucalis M.Bieb., part of the collection of National Museum of Natural History, Paris
Part of a training dataset of scanned herbarium specimens. The data paper and a summary landing page will be published on Zenodo as it gets published.<br><br>Content of this deposition:<br><br>- A JSON-LD datafile listing the label data associated with this herbarium specimen. The Darwin and Dublin Core data standards are used for most values.<br>- A JPEG image file of the scanned herbarium sheet.
H2020 PrimeFish National Level Competitiveness Iceland Norway Spain Vietnam Newfoundland
<p>The data set contains data on individual indicators of national seafood competitiveness. Data are collected as part of the EU H2020 project PrimeFish (grant no 635761). The analysis follows the general framework of the annual World Economic Forum Competitiveness Report. Indicators are taken from three sources; directly from the World Economic Forum report, survey among national experts and hard data such as stock sizes and wages. All data are numeric, and on a 1-7 scale. Data were collected from the World Economic Forum 2017 competitiveness report and surveys and hard data collected in 2017.</p> <p> </p> <p>Indicators are grouped in several catergories, that again are grouped in higher level categories, ultimately yielding a single competitiveness indicator for the seafood sector.</p>
Data Potential Bias in Peer Review of Grant Applications at the Swiss National Science Foundation
<p>Potential biases in the peer review of grant applications at the Swiss National Science Foundation.</p> <p> </p>
National Energy and Climate Plans - Preliminary analysis on Prosumerism for 9 EU Member States
<p>Preliminary check on the provisions on self-consumption and energy communities in the draft National Energy and Climate Plans (NECPs) of nine EU Member States (BE, DE, ES, FR, HR, IT, NL, PT, UK). The main findings are that only France and Spain put a reasonable emphasis on the importance of self-consumption and energy communities as suggested by RED II. Germany and Italy show some efforts while the NECPs of the other five member states contain only weak or no provisions on prosumerism. Most countries don’t define neither targets nor measures.</p>
Temporally enhanced RSEI and Nighttime Lights Reveal Long-Term Ecological Changes and Effective Protection in China's Inaugural National Parks
<p>China's inaugural national parks play a crucial role in preserving biodiversity and maintaining ecosystem services. These protected areas are characterized by diverse landscapes and sensitive ecological environments. Over recent decades, the interplay between intensified human activities and global climate change has posed significant challenges to the ecological quality of these regions. Accurate and scientific assessment of ecological quality is essential for informed management and policy-making.</p> <p>This dataset is based on multiple MODIS datasets, incorporating NDVI, LST, WET, and NDBSI as indicators. Using principal component analysis (PCA), we produced the Improved Remote Sensing Ecological Index (RSEI) for these parks from 2000 to 2022 at a 500m spatial resolution.</p> <p>The RSEI was calculated using four component indices: greenness, heat, dryness, and wetness. Data for dryness and wetness were derived from the 8-day composite 500m resolution surface reflectance product MOD09A1. Heat was calculated using the 8-day composite 1km resolution land surface temperature product MOD11A2, which was resampled to 500m resolution. Greenness was derived from the 16-day composite 500m resolution vegetation index product MOD13A1.</p> <p>The improved RSEI calculation method enhances the temporal stability and comparability of the data, making it more suitable for long-term ecological monitoring.</p> <p>The improved RSEI effectively integrates dynamic changes of multiple variables and offers better temporal comparability for long-term ecological monitoring. Our results indicate that the ecological environment quality within the inaugural national parks significantly improved over the study period, with more noticeable improvements following the implementation of pilot conservation programs.</p> <p>This dataset provides foundational information for understanding the long-term ecological trends in China's national parks. It serves as a crucial resource for researchers, policymakers, and conservationists dedicated to the sustainable management and development of these vital ecological regions.</p> <p>The dataset contains five RAR compressed files, each corresponding to one of the national parks. These files include the Remote Sensing Ecological Index (RSEI) data from 2000 to 2022 for each respective park:</p> <ul> <li><strong>NTLNP-RSEI.rar</strong>: Contains the RSEI data for the Northeast Tiger and Leopard National Park (NTLNP) from 2000 to 2022.</li> <li><strong>HTRNP-RSEI.rar</strong>: Contains the RSEI data for the Hainan Tropical Rainforest National Park (HTRNP) from 2000 to 2022.</li> <li><strong>WNP-RSEI.rar</strong>: Contains the RSEI data for the Wuyishan National Park (WNP) from 2000 to 2022.</li> <li><strong>SNP-RSEI.rar</strong>: Contains the RSEI data for the Sanjiangyuan National Park (SNP) from 2000 to 2022.</li> <li><strong>GPNP-RSEI.rar</strong>: Contains the RSEI data for the Giant Panda National Park (GPNP) from 2000 to 2022.</li> </ul> <p>Each of these compressed files includes the improved RSEI calculations for the respective national park, providing a comprehensive view of the ecological quality changes over the 22-year period.</p> <p>The details of the data are as follows:</p> <ul> <li><strong>Data Format</strong>: GeoTiff</li> <li><strong>Pixel Values</strong>: Represent RSEI, ranging from 0 to 1, with no units.</li> <li><strong>Compatibility</strong>: The data can be directly opened and processed using remote sensing and GIS software such as ENVI and ArcGIS.</li> <li><strong>Data Quality</strong>: Due to the application of water and snow masks to remove the influence of water bodies and snow/ice on the WET component, there are some missing data areas.</li> </ul> <p>These datasets offer valuable insights into the ecological quality changes within each national park over the specified period, making them essential for researchers, policymakers, and conservationists involved in the sustainable management and development of these protected areas.</p> <p>For using the data and code provided in this dataset, please cite the following paper:</p> <p>Wen, C., Long, T., He, G., Jiao, W., & Jiang, W. (2025). Temporally enhanced RSEI and nighttime lights reveal long-term ecological changes and effective protection in China’s inaugural national parks. <em>Ecological Indicators, 170</em>, 112981. <a href="https://doi.org/10.1016/j.ecolind.2024.112981" target="_new" rel="noopener">https://doi.org/10.1016/j.ecolind.2024.112981</a></p> <p>The calculation of the RSEI is completed using Google Earth Engine. The link to the calculation code is:</p> <p><a href="https://code.earthengine.google.com/fab5452cd224d1f06226aece4c1a1016">https://code.earthengine.google.com/089d74f423e91a0da9490f5098c55021</a></p>
National Checklists 2017: Guatemala Species List
Lists of taxa for each country and a few other administrative zones harvested from effechecka using simplified versions of geonames polygons. See <p></p>https://github.com/diatomsRcool/checklists for details<p></p>A list of species from Guatemala collected using effechecka and geonames polygons
National Checklists 2017: South America Species List
Lists of taxa for each country and a few other administrative zones harvested from effechecka using simplified versions of geonames polygons. See <p></p>https://github.com/diatomsRcool/checklists for details<p></p>List of species from South America inferred from individual country lists that were derived from effechecka and modified geonames polygons
National Checklists 2017: Oceania Species List
Lists of taxa for each country and a few other administrative zones harvested from effechecka using simplified versions of geonames polygons. See <p></p>https://github.com/diatomsRcool/checklists for details<p></p>List of species from Oceania inferred from individual country lists that were derived from effechecka and modified geonames polygons
National Checklists 2017: North America Species List
Lists of taxa for each country and a few other administrative zones harvested from effechecka using simplified versions of geonames polygons. See <p></p>https://github.com/diatomsRcool/checklists for details<p></p>List of species from North America inferred from individual country lists that were derived from effechecka and modified geonames polygons
National Checklists 2017: Asia Species List
Lists of taxa for each country and a few other administrative zones harvested from effechecka using simplified versions of geonames polygons. See <p></p>https://github.com/diatomsRcool/checklists for details<p></p>List of species from Asia inferred from individual country lists that were derived from effechecka and modified geonames polygons
National Checklists 2017: Europe Species List
Lists of taxa for each country and a few other administrative zones harvested from effechecka using simplified versions of geonames polygons. See <p></p>https://github.com/diatomsRcool/checklists for details<p></p>List of species from Europe inferred from individual country lists that were derived from effechecka and modified geonames polygons
National Checklists 2017: Africa Species List
Lists of taxa for each country and a few other administrative zones harvested from effechecka using simplified versions of geonames polygons. See <p></p>https://github.com/diatomsRcool/checklists for details<p></p>List of species from the continent of Africa inferred from individual country lists that were derived from effechecka and modified geonames polygons
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
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.