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Found 10 result(s)
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The information system Graffiti in Germany (INGRID) is a cooperation project between the linguistics department at the University of Paderborn and the art history department at the Karlsruhe Institute of Technology (KIT). As part of the joint project, graffiti image collections will be compiled, stored in an image database and made available for scientific use. At present, more than 100,000 graffiti from the years 1983 to 2018 from major German cities are recorded, including Cologne, Mannheim and Munich.
The Arizona State University (ASU) Research Data Repository provides a platform for ASU-affiliated researchers to share, preserve, cite, and make research data accessible and discoverable. The ASU Research Data Repository provides a permanent digital identifier for research data, which complies with data sharing policies. The repository is powered by the Dataverse open-source application, developed and used by Harvard University. Both the ASU Research Data Repository and the KEEP Institutional Repository are managed by the ASU Library to ensure research produced at Arizona State University is discoverable and accessible to the global community.
A research data repository for the education and developmental sciences.
RUresearch Data Portal is a subset of RUcore (Rutgers University Community Repository), provides a platform for Rutgers researchers to share their research data and supplementary resources with the global scholarly community. This data portal leverages all the capabilities of RUcore with additional tools and services specific to research data. It provides data in different clusters (research-genre) with excellent search facility; such as experimental data, multivariate data, discrete data, continuous data, time series data, etc. However it facilitates individual research portals that include the Video Mosaic Collaborative (VMC), an NSF-funded collection of mathematics education videos for Teaching and Research. Its' mission is to maintain the significant intellectual property of Rutgers University; thereby intended to provide open access and the greatest possible impact for digital data collections in a responsible manner to promote research and learning.
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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.
The UCI Machine Learning Repository is a collection of databases, domain theories, and data generators that are used by the machine learning community for the empirical analysis of machine learning algorithms. It is used by students, educators, and researchers all over the world as a primary source of machine learning data sets. As an indication of the impact of the archive, it has been cited over 1000 times.
Country
More than a quarter of a million people — one in 10 NSW men and women aged over 45 — have been recruited to our 45 and Up Study, the largest ongoing study of healthy ageing in the Southern Hemisphere. The baseline information collected from all of our participants is available in the Study’s Data Book. This information, which researchers use as the basis for their analyses, contains information on key variables such as height, weight, smoking status, family history of disease and levels of physical activity. By following such a large group of people over the long term, we are developing a world-class research resource that can be used to boost our understanding of how Australians are ageing. This will answer important health and quality-of-life questions and help manage and prevent illness through improved knowledge of conditions such as cancer, heart disease, depression, obesity and diabetes.