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Found 11 result(s)
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Research Data Centres offer a secure access to detailed microdata from Statistics Canada's surveys, and to Canadian censuses' data, as well as to an increasing number of administrative data sets. The search engine was designed to help you find out more easily which dataset among all the surveys available in the RDCs best suits your research needs.
>>>!!!<<< This site is going away on April 1, 2021. General access to the site has been disabled and community users will see an error upon login. >>>!!!<<< Socrata’s cloud-based solution allows government organizations to put their data online, make data-driven decisions, operate more efficiently, and share insights with citizens.
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Edmond is the institutional repository of the Max Planck Society for public research data. It enables Max Planck scientists to create citable scientific assets by describing, enriching, sharing, exposing, linking, publishing and archiving research data of all kinds. Further on, all objects within Edmond have a unique identifier and therefore can be clearly referenced in publications or reused in other contexts.
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<<<!!!<<< This repository is no longer available. The Social Sciences Library of the former Center for Advanced Studies in Social Sciences (CEACS) of the Juan March Institute has been integrated into the Social and Legal Sciences Library of the Carlos III University of Madrid since September 2013. In the University's catalog you can consult what used to be its collection of monographs and journals. >>>!!!>>>
ICPSR maintains a data archive of more than 250,000 files of research in the social and behavioral sciences. It hosts 21 specialized collections of data in education, aging, criminal justice, substance abuse, terrorism, and other fields. ICPSR advances and expands social and behavioral research, acting as a global leader in data stewardship and providing rich data resources and responsive educational opportunities for present and future generations.
Mulce (MUltimodal contextualized Learner Corpus Exchange) is a research project supported by the National Research Agency (ANR programme: "Corpus and Tools in the Humanities", ANR-06-CORP-006). A teaching corpus (LETEC - Learning and Teaching Corpora) combines a systematic and structured data set, particularly of interactional data, and traces left by a training course experimentation, conducted partially or completely online and completed by additional technical, human, pedagogical and scientific information to enable the data to be analysed in context.
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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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The Research Data Centre (Forschungsdatenzentrum, FDZ) at the Institute for Educational Quality Improvement (Institut zur Qualitätsentwicklung im Bildungswesen, IQB) archives and documents data sets resulting from national and international assessment studies (such as DESI, PIRLS, PISA, IQB-Bildungstrends). Moreover, the FDZ makes these data sets available for re- and secondary analysis. Members of the scientific community can apply for access to the data sets archived at the FDZ.
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.