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Found 43 result(s)
The Australian National University undertake work to collect and publish metadata about research data held by ANU, and in the case of four discipline areas, Earth Sciences, Astronomy, Phenomics and Digital Humanities to develop pipelines and tools to enable the publication of research data using a common and repeatable approach. Aims and outcomes: To identify and describe research data held at ANU, to develop a consistent approach to the publication of metadata on the University's data holdings: Identification and curation of significant orphan data sets that might otherwise be lost or inadvertently destroyed, to develop a culture of data data sharing and data re-use.
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 Brown Digital Repository (BDR) is a place to gather, index, store, preserve, and make available digital assets produced via the scholarly, instructional, research, and administrative activities at Brown.
The Carleton University Data Repository Dataverse is the research data repository for Carleton University. It is managed by the Data Services in the MacOdrum Library. The repository also houses the MacOdrum Library Dataverse Collection which contains numerous public opinion polls.
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 repository is no longer available. further information and data see: Oxford University Research Archive: https://www.re3data.org/repository/r3d100011230 >>>!!!>>>
Online storage, sharing and registration of research data, during the research period and after its completion. DataverseNL is a shared service provided by participating institutions and DANS.
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DATICE was established in late 2018 and is funded by the University of Iceland's (UI) School of Social Sciences, with a contribution from the university's Centennial Fund. DATICE is the appointed service provider for the Consortium of European Social Science Data Archives (CESSDA ERIC) in Iceland and is located within the UI Social Science Research Institute (SSRI). The main goal of the data service is to ensure open and free access to high quality research data for the research community as well as the general public.
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Adattár stores research data associated with the University of Debrecen, and provides services such as data transfer, storage and sharing. As a result, research data is easily accessible and more visible to the scientific community in each field, following disciplinary standards. Adattár aims to foster best practices of findability and accessibility of research data, and will provide guidance regarding issues of access, privacy, and copyright. Adattár aims to be a widely used, inter-disciplinary, trusted platform for managing, sharing, and archiving research data created by the researchers associated with the university.
A Research Data Repository (RDR) for researchers in India. Any registered researchers of Indian Universities can manage their research data on eSHODHMANTHAN-RDR free of cost. This research data repository is configured to provide free of cost research data management services to existing and forthcoming researchers throughout their research life. eSHODHMANTHAN-RDR is powered by Dataverse project of Harvard University
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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.
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The FDZ-DZA (Forschungsdatenzentrum DZA) is a facility of the German Centre of Gerontology (Deutsches Zentrum für Altersfragen, DZA) and has received accreditation as research data center DZA by the German Data Forum (RatSWD). Its main task is to make data of the German Ageing Survey DEAS and the German Survey on Volunteering (FWS) accessible to researchers by providing user-friendly Scientific Use Files (SUF), documentation of the contents and instruments as well support for scholars using the data.
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BIBB has a strong tradition of survey-based research. It initiates and realises the collection of individual and firm-level data on crucial positions and transitions in the education and labour market system. The BIBB-FDZ covers a variety of data deploying different units of analysis and temporal designs and focusing on various thematic issues. Standard access to well prepared firm- and individual-level data on the attainment and utilization of vocational education and training Documentation of these data sets, i.e. a description of their central characteristics, main issues and variables, data collection, anonymisation, weighting and recoding etc. Advisory service on data choice, data access and handling, research potential and scope and validity of the data. Supply of a range of data tools such as standard measures and classifications in the fields of education, occupations, industries and regions (if possible also including cross-national fields), formally anonymous data for remote data access, or references to publications with the data.
ICRISAT performs crop improvement research, using conventional as well as methods derived from biotechnology, on the following crops: Chickpea, Pigeonpea, Groundnut, Pearl millet,Sorghum and Small millets. ICRISAT's data repository collects, preserves and facilitates access to the datasets produced by ICRISAT researchers to all users who are interested in. Data includes Phenotypic, Genotypic, Social Science, and Spatial data, Soil and Weather.
The LISS panel (Longitudinal Internet Studies for the Social sciences) is the principal component of the MESS project. It consists of 5000 households, comprising approximately 7500 individuals. The panel is based on a true probability sample of households drawn from the population register by Statistics Netherlands. Households that could not otherwise participate are provided with a computer and Internet connection. In addition to the LISS panel an Immigrant panel was available from October 2010 up until December 2014. This Immigrant panel consisted of around 1,600 households (2,400 individuals) of which 1,100 households (1,700 individuals) were of non-Dutch origin. The data from this panel are still available through the LISS data archive (https://www.dataarchive.lissdata.nl/study_units/view/162). Panel members complete online questionnaires every month of about 15 to 30 minutes in total. They are paid for each completed questionnaire. One member in the household provides the household data and updates this information at regular time intervals.
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The Economics & Business Data Center (EBDC) is a combined platform for empirical research in business administration and economics of the Ludwig–Maximilian University of Munich (LMU) and the Ifo Institute and aims at opening new fields for empirical research in business administration and economics. In this regard, the EBDC provides innovative datasets of German companies, containing both survey data of the Ifo Institute as well as external balance sheet data. Therefore, the tasks of the EBDC also include the procurement and administration of data sources for research and teaching, the central provision, updating and documentation of external databases, as well as the acquisition of corresponding support tools. Beyond that, the EBDC serves as a contact and central coordinator on licensing economic firm-level datasets for LMU’s Munich School of Management and LMU’s Department of Economics and supports researchers and guests of the LMU and the Ifo Institute on site. In the future, it will also conduct academic conferences on research with company data.
The Minnesota Population Center (MPC) is a University-wide interdisciplinary cooperative for demographic research. The MPC serves more than 80 faculty members and research scientists from eight colleges and institutes at the University of Minnesota. As a leading developer and disseminator of demographic data, we also serve a broader audience of some 50,000 demographic researchers worldwide. MPC is a DataONE member node: https://search.dataone.org/#profile/US_MPC
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The nature of the ‘Bridge of Data’ project is to design and build a platform that allows collecting, searching, analyzing and sharing open research data and to provide it with unique data collected from the three most important Pomeranian universities: Gdańsk University of Technology, Medical University of Gdańsk and the University of Gdańsk. These data will be made available free of charge to the scientific community, entrepreneurs and the public. A bridge will be built to allow reuse of Open Research Data. The available research data will be described by standards developed by dedicated, experienced scientific teams. The metadata will allow other external computer systems to interpret the collected data. ORD descriptions will also include data reuse or reduction scenarios to facilitate further processing.