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The CEACS Data Library aims to support its research community to conduct quantitative research with primary and secondary data of the highest quality. The Data Library provides integrated access to an extensive collection of data for research and teaching. This collection comprises studies from major data centres as well as public collections and other datasets of special interest to members of CEACS. This section offers the possibility to search and browse the collection. The links go to records on the catalogue or the data directly on our servers or the web. If you cannot locate or access the data you are after please contact the Data Librarian for further assistance.
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.
e-cienciaDatos is a multidisciplinary data repository that houses the scientific datasets of researchers from the public universities of the Community of Madrid and the UNED, members of the Consorcio Madroño, in order to give visibility to these data, to ensure its preservation And facilitate their access and reuse. e-cienciaDatos is structured as a system constituted by different communities that collects datasets of each of the individual universities. e-cienciaDatos offers the deposit and publication of datasets, assigning a digital object identifier DOI to each of them. The association of a dataset with a DOI will facilitate data verification, dissemination, reuse, impact and long-term access. In addition, the repository provides a standardized citation for each dataset, which contains sufficient information so that it can be identified and located, including the DOI.