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Found 13 result(s)
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sciencedata.dk is a research data store provided by DTU, the Danish Technical University, specifically aimed at researchers and scientists at Danish academic institutions. The service is intended for working with and sharing active research data as well as for safekeeping of large datasets. The data can be accessed and manipulated via a web interface, synchronization clients, file transfer clients or the command line. The service is built on and with open-source software from the ground up: FreeBSD, ZFS, Apache, PHP, ownCloud/Nextcloud. DTU is actively engaged in community efforts on developing research-specific functionality for data stores. Our servers are attached directly to the 10-Gigabit backbone of "Forskningsnettet" (the National Research and Education Network of Denmark) - implying that up and download speed from Danish academic institutions is in principle comparable to those of an external USB hard drive. Data store for research data allowing private sharing and sharing via links / persistent URLs.
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Unidata – Bicocca Data Archive is an interdepartmental center of the University of Milan-Bicocca, born in 2015. The center is the Italian point of reference for the research data archiving and dissemination, based on the example of the National Archives located in major European countries and beyond. UniData inherits the long work from the ADPSS-Sociodata Data Archive, born in 1999 in the Department of Sociology and Social Research at the same University. Here you can find only individual data from 2010. For older surveys please visit ADPSS Sociodata, Data Archive for Social Sciences - Archivio Dati e Programmi Per le Scienze Soziali: https://www.unidata.unimib.it/old/ and ADPSS-SOCIODATA Archivio Dati e Programmi per le Scienze Sociali Dataverse : https://dataverse.harvard.edu/dataverse/adpss
IBICT is providing a research data repository that takes care of long-term preservation and archiving of good practices, so that researchers can share, maintain control and get recognition for your data. The repository supports research data sharing with Quote persistent data, allowing them to be played. The Dataverse is a large open data repository of all disciplines, created by the Institute for Quantitative Social Science at Harvard University. IBICT the Dataverse repository provides a means available for free to deposit and find specific data sets stored by employees of the institutions participating in the Cariniana network.
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The Repositorio de datos del Ministerio de Educación del Perú provides the scientific community with a series of data sets for its reuse. The MINEDU Data Repository is integrated into the Digital National Repository of Science, Technology and Innovation of Open Access - ALICIA (http://alicia.concytec.gob.pe) managed and administrated by CONCYTEC.
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Maenduar in Tupi means "to remember". The Maenduar repository, created by LARHUD is an institutional repository (IBICT) dedicated to research data in Digital Humanities and Humanities. The repository encompasses the production of LARHUD members and partners and extends to the public space as a public deposit repository. Researchers, professors, students linked to any institutions will be able to deposit their research data, understanding that Maenduar becomes, from this action, a public, national repository, dedicated to the production of knowledge in the Humanities in the face of the development of digital culture in all areas of the world. social world.
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.
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The Portuguese Archive of Social Information (APIS) is a scientific infrastructure acting on the domain of preservation and dissemination of social science data. Based at Instituto de Ciências Sociais, University of Lisbon, the archive works towards the acquisition and sharing of digital data for the purposes of public consultation, secondary analysis and pedagogical use. The archive comprises a range of datasets provided by research projects of the national scientific community.
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Arquivo.pt is a research infrastructure that preserves millions of files collected from the web since 1996 and provides a public search service over this information. It contains information in several languages. Periodically it collects and stores information published on the web. Then, it processes the collect data to make it searchable, providing a “Google-like” service that enables searching the past web (English user interface available at https://arquivo.pt/?l=en). This preservation workflow is performed through a large-scale distributed information system and can also accessed through API (https://arquivo.pt/api).
<<<!!!<<< The repository is no longer available. 2018-11-20; COMPASS used to be provided and available at FORS but is no longer supported. >>>!!!>>>
FORS is the Swiss Centre of Expertise in the Social Sciences. FORS maintains a national digital archive for social science research data, implements large-scale national and international surveys, offers data and research information services to researchers and academic institutions, and conducts methodological and thematic research. FORS Data Service is FORS’ resource centre for research and teaching in the social sciences. It provides data management support and training, and it archives, disseminates and promotes quantitative and qualitative data. The Data Service maintains a comprehensive and up-to-date inventory of social science research projects in Switzerland, and makes available a wide range of datasets for secondary analysis. Databases at the FORS Data Service are: SWISSUbase and DeVisu (for variable level metadata for important surveys).
The Comparative Study of Electoral Systems (CSES) is a collaborative, cross-national program of comparative electoral behavior among over 60 election study teams from around the world. The CSES allows examination into how societal, political, economic and structural contexts shape citizen behavior and condition democratic choice; the nature of political and social divisions; and how citizens in different political systems evaluate democratic institutions and processes. Participating countries include a common module of survey questions in their post-election studies. The resulting data are deposited along with voting, demographic, district and macro variables. The studies are then merged into a single, free, public dataset for use in comparative study and cross-level analysis. The research agenda, questionnaires, and study design are developed by an international committee of leading scholars of electoral politics and political science. The design is implemented in each country by their foremost social scientists.
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The Queen's Research Data Centre is a member of the Canadian Research Data Centre Network (CRDCN) that provides researchers with access to microdata 'masterfiles' from population and health surveys. Access to the RDC is limited to those with projects approved by Statistics Canada. Before applying to an RDC, you will have to show that your research cannot be conducted using Public Use Microdata Files (PUMFs) available through the Data Liberation Initiative (DLI). Access to DLI PUMFS at Queen's is available through the Social Science Data Centre, using the ODESI data portal.
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Attention! Data sets are not updated anymore. Please, visit the BonaRes Repositor​ium​ for new datasets. Open Research Data provides quality assessed data and their metadata such as context information on measurement objectives, equipment, methods, testing and investigation areas. The purpose of the repository is to secure quality, integrity and long-term availability of landscape and ecosystem research data as well as to enhance accessibility of free data from ZALF long-term monitoring campaigns, landscape laboratories (Agro-ScapeLabs), field trials and experiments. The Leibniz Centre for Agricultural Landscape Research (ZALF) explores ecosystems in agricultural landscapes and the development of ecologically and economically viable land use systems. ZALF combines scientific expertise from agricultural science, geosciences, biosciences and socio-economics.