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Found 153 result(s)
The GRSF, the Global Record of Stocks and Fisheries, integrates data from three authoritative sources: FIRMS (Fisheries and Resources Monitoring System), RAM (RAM Legacy Stock Assessment Database) and FishSource (Program of the Sustainable Fisheries Partnership). The GRSF content publicly disseminated through this catalogue is distributed as a beta version to test the logic to generate unique identifiers for stocks and fisheries. The access to and review of collated stock and fishery data is restricted to selected users. This beta release can contain errors and we welcome feedback on content and software performance, as well as the overall usability. Beta users are advised that information on this site is provided on an "as is" and "as available" basis. The accuracy, completeness or authenticity of the information on the GRSF catalogue is not guaranteed. It is reserved the right to alter, limit or discontinue any part of this service at its discretion. Under no circumstances shall the GRSF be liable for any loss, damage, liability or expense suffered that is claimed to result from the use of information posted on this site, including without limitation, any fault, error, omission, interruption or delay. The GRSF is an active database, updates and additions will continue after the beta release. For further information, or for using the GRSF unique identifiers as a beta tester please contact FIRMS-Secretariat@fao.org.
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The INESC TEC data repository showcases datasets produced or used by INESC TEC researchers and their partners. The repository is organized in four groups (institutional clusters). Computer Science, Power and Energy, Network and Intelligent Systems and Power and Energy.
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UBC Dataverse Collection is a free research data repository for our faculty, students and staff. The platform makes it possible for researchers to deposit data, create appropriate metadata, obtain DOIs for permanent links, and maintain version control of their datasets. All files are held in a secure environment on Canadian servers. Researchers are encouraged to make their data available publicly, but can choose to restrict access to their data if they wish.
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The Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) and German Plant Phenotyping Network (DPPN) has jointly initiated the Plant Genomics and Phenomics Research Data Repository (PGP) as infrastructure to comprehensively publish plant research data. This covers in particular cross-domain datasets that are not being published in central repositories because of its volume or unsupported data scope, like image collections from plant phenotyping and microscopy, unfinished genomes, genotyping data, visualizations of morphological plant models, data from mass spectrometry as well as software and documents.
Apollo (previously DSpace@Cambridge) is the University of Cambridge’s Institutional Repository (IR), preserving and providing access to content created by members of the University. The repository stores a range of content and provides different levels of access, but its primary focus is on providing open access to the University’s research publications.
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<<<!!!<<< This repository is no longer available. >>>!!!>>> The Plant Organelles Database Version 3 (PODB3) is a specialized database project to promote a comprehensive understanding of organelle dynamics, including organelle function, biogenesis, differentiation, movement, and interactions with other organelles. This database consists of 6 individual parts, 'The Electron Micrograph Database', 'The Perceptive Organelles Database', 'The Organelles Movie Database', 'The Organellome Database', 'The Functional Analysis Database', and 'External Links to other databases and Web pages'. All the data and protocols in these databases are populated by direct submission of experimentally determined data from plant researchers.
SRUC is currently on a transformational journey as we move towards becoming a unique, market-led and mission diverse 21st Century rural university, driving the future needs of a dynamic, innovative and competitive rural sector in Scotland, and working with our collaborators and partners worldwide to solve the biggest global agrifood challenges. Our researchers already carry out strategic and applied research on global and local food security issues, and actively support the translation of research results into practice. Our research ethos is strongly collaborative, and we have a long history of industrial, NGO and academic partnerships locally and internationally. As well as having longstanding disciplinary strengths in several key areas, we actively promote interdisciplinary research, especially linking natural and social sciences. We have a particular interest in research that helps inform policy, with Scottish and UK Government rural affairs and environment departments and the EU as key research clients.
OpenML is an open ecosystem for machine learning. By organizing all resources and results online, research becomes more efficient, useful and fun. OpenML is a platform to share detailed experimental results with the community at large and organize them for future reuse. Moreover, it will be directly integrated in today’s most popular data mining tools (for now: R, KNIME, RapidMiner and WEKA). Such an easy and free exchange of experiments has tremendous potential to speed up machine learning research, to engender larger, more detailed studies and to offer accurate advice to practitioners. Finally, it will also be a valuable resource for education in machine learning and data mining.
When published in 2005, the Millennium Run was the largest ever simulation of the formation of structure within the ΛCDM cosmology. It uses 10(10) particles to follow the dark matter distribution in a cubic region 500h(−1)Mpc on a side, and has a spatial resolution of 5h−1kpc. Application of simplified modelling techniques to the stored output of this calculation allows the formation and evolution of the ~10(7) galaxies more luminous than the Small Magellanic Cloud to be simulated for a variety of assumptions about the detailed physics involved. As part of the activities of the German Astrophysical Virtual Observatory we have created relational databases to store the detailed assembly histories both of all the haloes and subhaloes resolved by the simulation, and of all the galaxies that form within these structures for two independent models of the galaxy formation physics. We have implemented a Structured Query Language (SQL) server on these databases. This allows easy access to many properties of the galaxies and halos, as well as to the spatial and temporal relations between them. Information is output in table format compatible with standard Virtual Observatory tools. With this announcement (from 1/8/2006) we are making these structures fully accessible to all users. Interested scientists can learn SQL and test queries on a small, openly accessible version of the Millennium Run (with volume 1/512 that of the full simulation). They can then request accounts to run similar queries on the databases for the full simulations. In 2008 and 2012 the simulations were repeated.
The repository is part of the National Research Data Infrastructure initiative Text+, in which the University of Tübingen is a partner. It is housed at the Department of General and Computational Linguistics. The infrastructure is maintained in close cooperation with the Digital Humanities Centre, which is a core facility of the university, colaborating with the library and computing center of the university. Integration of the repository into the national CLARIN-D and international CLARIN infrastructures gives it wide exposure, increasing the likelihood that the resources will be used and further developed beyond the lifetime of the projects in which they were developed. Among the resources currently available in the Tübingen Center Repository, researchers can find widely used treebanks of German (e.g. TüBa-D/Z), the German wordnet (GermaNet), the first manually annotated digital treebank (Index Thomisticus), as well as descriptions of the tools used by the WebLicht ecosystem for natural language processing.
York Digital Library (YODL) is a University-wide Digital Library service for multimedia resources used in or created through teaching, research and study at the University of York. YODL complements the University's research publications, held in White Rose Research Online and PURE, and the digital teaching materials in the University's Yorkshare Virtual Learning Environment. YODL contains a range of collections, including images, past exam papers, masters dissertations and audio. Some of these are available only to members of the University of York, whilst other material is available to the public. YODL is expanding with more content being added all the time
N U C A S T R O D A T A . O R G is your WWW resource for utilizing nuclear information in studies of astrophysical systems. This site hyperlinks all online nuclear astrophysics datasets, hosts the Computational Infrastructure for Nuclear Astrophysics, and provides a mechnanism for researchers to share files online. We created the first online "cloud computing" system for nuclear astrophysics, a virtual pipeline that enables results from the nuclear laboratory to be rapidly incorporated into astrophysical simulations. This system, the Computational Infrastructure for Nuclear Astrophysics or CINA, came online at nucastrodata.org
BeiDare2 is currently at beta version. All new users should try the new service as we no longer provide training for the classic BioDare. - BioDare stands for Biological Data Repository, its main focus is data from circadian experiments. BioDare is an online facility to share, store, analyse and disseminate timeseries data, focussing on circadian clock data, with browser and web service interfaces. Toolbox features include an improved, speedier FFT-NLLs routine and ROBuST’s Spectrum Resampling tool that will analyse rhythmic time series data.
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SAFER-Data is a web-based interface to the Environmental Data Archive maintained by the Environmental Research Centre (ERC) in the Environmental Protection Agency (EPA) of Ireland, who has responsibilities for a wide range of licensing, enforcement, monitoring and assessment activities associated with environmental protection.
Data.gov increases the ability of the public to easily find, download, and use datasets that are generated and held by the Federal Government. Data.gov provides descriptions of the Federal datasets (metadata), information about how to access the datasets, and tools that leverage government datasets
The International Maize and Wheat Improvement Center (CIMMYT) provides a free, open access repository of research software, studies, and datasets produced and developed by CIMMYT scientists as well as the results of the Seeds of Discovery project, which makes available genetic profiles of wheat and maize, two of mankind's three major cereal crops.
The Cornell Center for Social Sciences (CCSS) houses an extensive collection of research data files in the social sciences with particular emphasis on data that matches the interests of Cornell University researchers. CCSS intentionally uses a broad definition of social sciences in recognition of the interdisciplinary nature of Cornell research. CCSS collects and maintains digital research data files in the social sciences, with a current emphasis on Cornell-based social science research, Results Reproduction packages, and potentially at-risk datasets. Our archive historically has focused on a broad range of social science data, including data on demography, economics and labor, political and social behavior, family life, and health. You can search our holdings or browse studies by subject area.
The NF Data Portal is designed to help openly explore and share NF datasets, analysis tools, resources, and publications related to neurofibromatosis. Anyone can join the NF Open Science Initiative (NF-OSI) to participate! We welcome contributions from anyone in the neurofibromatosis and schwannomatosis research community, such as original datasets generated by the community or analyses of data from the NF Data Portal.
<<<!!!<<< Stated 2019-10-30: Dash is no longer available. Researchers are advised to store their research data at Dryad https://www.re3data.org/repository/r3d100000044 >>>!!!>>> Dash is an open data publication platform for upload, access, and re-use of research data. Submissions to Dash may be from researchers at participating UC campuses, researchers in earth science and ecology (DataONE), and researchers submitting to the UC Press journals Elementa and Collabra. Self-service depositing of research data through Dash fulfills publisher, funder, and data management plan requirements regarding data sharing and preservation. When researchers publish their datasets through Dash, their datasets are issued a DOI (DataCite) to optimize citability, and are publicly available for download and re-use under a CC BY 4.0 or CC-0 license. Deposited data are preserved in Merritt, California Digital Library’s preservation repository.
The ChemBio Hub vision is to provide the tools that will make it easier for Oxford University scientists to connect with colleagues to improve their research, to satisfy funders that the data they have paid for is being managed according to their policies, and to make new alliances with pharma and biotech partners. Funding and development of the ChemBio Hub was ending on the 30th June 2016. Please be reassured that the ChemBio Hub system and all your data will continue to be secured on the SGC servers for the foreseeable future. You can continue to use the services as normal.
California Digital Library (CDL) seeks to be a catalyst for deeply collaborative solutions providing a rich, intuitive and seamless environment for publishing, sharing and preserving our scholars’ increasingly diverse outputs, as well as for acquiring and accessing information critical to the University of California’s scholarly enterprise. University of California Curation Center (UC3) is the digital curation program within CDL. The mission of UC3 is to provide transformative preservation, curation, and research data management systems, services, and initiatives that sustain and promote open scholarship.
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KEGG is a database resource for understanding high-level functions and utilities of the biological system, such as the cell, the organism and the ecosystem, from molecular-level information, especially large-scale molecular datasets generated by genome sequencing and other high-throughput experimental technologies