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Found 136 result(s)
BOARD (Bicocca Open Archive Research Data) is the institutional data repository of the University of Milano-Bicocca. BOARD is an open, free-to-use research data repository, which enables members of University of Milano-Bicocca to make their research data publicly available. By depositing their research data in BOARD researchers can: - Make their research data citable - Share their data privately or publicly - Ensure long-term storage for their data - Keep access to all versions - Link their article to their data
The repository of the Hamburg Centre for Speech Corpora is used for archiving, maintenance, distribution and development of spoken language corpora. These usually consist of audio and / or video recordings, transcriptions and other data and structured metadata. The corpora treat the focus on multilingualism and are generally freely available for research and teaching. Most of the measures maintained by the HZSK corpora were created in the years 2000-2011 in the framework of the SFB 538 "Multilingualism" at the University of Hamburg. The HZSK however also strives to take linguistic data from other projects or contexts, and to provide also the scientific community for research and teaching are available, provided that they are compatible with the current focus of HZSK, ie especially spoken language and multilingualism.
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The Research Data Center Qualiservice provides services for archiving and reusing qualitative research data from the social sciences. We advise and accompany research projects in the process of long-term data archiving and data sharing. Data curation is conducted by experts for the social sciences. We also provide research data and relevant context information for reuse in scientific research and teaching. Internationally interoperable metadata ensure that data sets are searchable and findable. Persistent identifiers (DOI) ensure that data and study contexts are citable. Qualiservice was accredited by the German Data Forum (RatSWD) in 2019 and adheres to its quality assurance criteria. Qualiservice is committed to the German Research Foundation’s (DFG) Guidelines for Safeguarding Good Scientific Practice and takes into account the FAIR Guiding Principles for scientific data management and stewardship as well as the OECD Principles and Guidelines for Access to Research Data from Public Funding. Qualiservice coordinates the networking and further development of scientific infrastructures for archiving and secondary use of qualitative data from social research within the framework of the National Research Data Infrastructure.
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Research Data Australia is the data discovery service of the Australian Research Data Commons (ARDC). The ARDC is supported by the Australian Government through the National Collaborative Research Infrastructure Strategy Program. Research Data Australia helps you find, access, and reuse data for research from over one hundred Australian research organisations, government agencies, and cultural institutions. We do not store the data itself here but provide descriptions of, and links to, the data from our data publishing partners.
The Comparative Welfare Entitlements Project (CWEP) collects data on institutional features of social insurance programs in 33 countries dating back to the early 1970s. The project extends and updates information collected and published online as CWED by Lyle Scruggs and CWED 2 by Lyle Scruggs, Detlef Jahn, and Kati Kuitto. Data is currently provided for unemployment and sickness insurance benefits as well as for standard and minimum pensions and covers income replacement rates of cash benefits, eligibility criteria and coverage of the programs. Replacement rates are available for ten household types, making CWEP one of the most comprehensive datasets on replacement rates for social insurance programs.
>>>!!!<<< Sorry.we are no longer in operation >>>!!!<<< The Beta Cell Biology Consortium (BCBC) was a team science initiative that was established by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK). It was initially funded in 2001 (RFA DK-01-014), and competitively continued both in 2005 (RFAs DK-01-17, DK-01-18) and in 2009 (RFA DK-09-011). Funding for the BCBC came to an end on August 1, 2015, and with it so did our ability to maintain active websites.!!! One of the many goals of the BCBC was to develop and maintain databases of useful research resources. A total of 813 different scientific resources were generated and submitted by BCBC investigators over the 14 years it existed. Information pertaining to 495 selected resources, judged to be the most scientifically-useful, has been converted into a static catalog, as shown below. In addition, the metadata for these 495 resources have been transferred to dkNET in the form of RDF descriptors, and all genomics data have been deposited to either ArrayExpress or GEO. Please direct questions or comments to the NIDDK Division of Diabetes, Endocrinology & Metabolic Diseases (DEM).
The LINZ Data Service provides free online access to New Zealand’s most up-to-date land and seabed data. The data can be searched, browsed and downloaded. The LINZ web services can be also integrated into other applications.
Kochi Core Center (KCC) houses one of the 3 Inernationational Ocean Discovery Program (IODP) core repositories, accompanied by images and x-ray CT scanning data viewable by the Virtual Core Library. And it hosts Japan Agency for Marine-Earth Science and Technology (JAMSTEC) marine core samples and associated analytical data for general scientific or educational uses, after 2 years have passed since collection of core samples.
ZENODO builds and operates a simple and innovative service that enables researchers, scientists, EU projects and institutions to share and showcase multidisciplinary research results (data and publications) that are not part of the existing institutional or subject-based repositories of the research communities. ZENODO enables researchers, scientists, EU projects and institutions to: easily share the long tail of small research results in a wide variety of formats including text, spreadsheets, audio, video, and images across all fields of science. display their research results and get credited by making the research results citable and integrate them into existing reporting lines to funding agencies like the European Commission. easily access and reuse shared research results.
Within WASCAL a large number of heterogeneous data are collected. These data are mainly coming from different initiated research activities within WASCAL (Core Research Program, Graduate School Program) from the hydrological-meteorological, remote sensing, biodiversity and socio economic observation networks within WASCAL, and from the activities of the WASCAL Competence Center in Ouagadougou, Burkina-Faso.
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.
Eurostat is the statistical office of the European Union situated in Luxembourg. Its task is to provide the European Union with statistics at European level that enable comparisons between countries and regions. Eurostat offers a whole range of important and interesting data that governments, businesses, the education sector, journalists and the public can use for their work and daily life.
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The 2008-launched German Family Panel pairfam (“Panel Analysis of Intimate Relationships and Family Dynamics”) is a multi-disciplinary, longitudinal study for researching partnership and family dynamics in Germany. The annually collected survey data from a nationwide random sample of more than 12,000 persons of the three birth cohorts 1971-73, 1981-83, 1991-93 and their partners, parents and children offers unique opportunities for the analysis of partner and generational relationships as they develop over the course of multiple life phases.
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.
The International Food Policy Research Institute (IFPRI) seeks sustainable solutions for ending hunger and poverty. In collaboration with institutions throughout the world, IFPRI is often involved in the collection of primary data and the compilation and processing of secondary data. The resulting datasets provide a wealth of information at the local (household and community), national, and global levels. IFPRI freely distributes as many of these datasets as possible and encourages their use in research and policy analysis. IFPRI Dataverse contains following dataverses: Agricultural Science and Knowledge Indicators - ASTI, HarvestChoice, Statistics on Public Expenditures for Economic Development - SPEED, International Model for Policy Analysis of Agricultural Commodities and Trade - IMPACT, Africa RISING Dataverse and Food Security Portal Dataverse.
The Centre’s vision is a rural transformation in the developing world as smallholder households strategically increase their use of trees in agricultural landscapes to improve their food security, nutrition, income, health, shelter, social cohesion, energy resources and environmental sustainability. The Centre’s mission is to generate science-based knowledge about the diverse roles that trees play in agricultural landscapes, and to use its research to advance policies and practices, and their implementation, that benefit the poor and the environment.
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.
Currently the institute has more than 700 collections consisting of (digital) research data, digitized material, archival collections, printed material, handwritten questionnaires, maps and pictures. The focus is on resources relevant for the study of function, meaning and coherence of cultural expressions and resources relevant for the structural, dialectological and sociolinguistic study of language variation within the Dutch language. An overview is here https://meertens.knaw.nl/en/datasets/
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The NIRD Research Data Archive is a repository that provides long-term storage for research data and is compliant with the Open Archival Information System (OAIS) reference model . The aim of the archive is to provide (public) access to published research data and to promote cross-disciplinary studies. The NIRD Research Data Archive (NIRD Archive) is in full production. The NIRD Archive will operate on a “subject to approval” basis and will accept any type of research data from Norwegian academically funded projects that is no longer considered proprietary.
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.