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Found 7 result(s)

Imperial College Research Computing Service Data Repository

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A lightweight digital repository for data based on the concepts of collections of filesets. Both the collection and the fileset are assigned a DOI by the DataCite organisation which can be quoted in articles

Danish National Birth Cohort

DNBC

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Exposures in the period from conception to early childhood - including fetal growth, cell division, and organ functioning - may have long-lasting impact on health and disease susceptibility. To investigate these issues the Danish National Birth Cohort (Better health in generations) was established. A large cohort of pregnant women with long-term follow-up of the offspring was the obvious choice because many of the exposures of interest cannot be reconstructed with suffcient validity back in time. The study needed to be large, and the aim was to recruit 100,000 women early in pregnancy, and to continue follow-up for decades. Exposure information was collected by computer-assisted telephone interviews with the women twice during pregnancy and when their children were six and 18 months old. Participants were also asked to fill in a self-administered food frequency questionnaire in mid-pregnancy. Furthermore, a biological bank has been set up with blood taken from the mother twice during pregnancy and blood from theumbilical cord taken shortly after birth.

Lok Dhaba

Lok Dhaba Food For Political Thought

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The Centre conducts real-time data collection on all ongoing and incoming General and Assembly Elections, and diffuses data-driven analysis through print and electronic media. The coverage includes the analysis, contextualization, and visualisation of results and the profiling of main parties candidates. For each election, we assemble a team of field researchers and scholars to complete and expand existing data. Besides the ECI results data, we collect information on the socio-demographic profile of main parties’ candidates and on the sociological profile of constituencies.

Grand Challenge Data Collection

Carnegie Mellon University Multi-Modal Activity Database

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The CMU Multi-Modal Activity Database (CMU-MMAC) database contains multimodal measures of the human activity of subjects performing the tasks involved in cooking and food preparation. The CMU-MMAC database was collected in Carnegie Mellon's Motion Capture Lab. A kitchen was built and to date twenty-five subjects have been recorded cooking five different recipes: brownies, pizza, sandwich, salad, and scrambled eggs.

UFS Figshare

University of the Free State Figshare

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figshare is the RDM system at the University. It is a cloud-based data repository that supports multiple file formats. Research data in the form of datasets, code, audio, images and more can be disseminated via the University's figshare. Citations can be traced for datasets (not just the final research output/article) and analytics will show who is looking at our research data around the world. figshare enables researchers to store research data in a secure way. The system is user-friendly, with easy access, and shareable with colleagues and collaborators on research projects. Where appropriate it enables researchers to make research data openly accessible.

Edmond

The Open Research Data Repository of the Max Planck Society

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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.

DataverseNO

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DataverseNO (https://dataverse.no) is a curated, FAIR-aligned national generic repository for open research data from all academic disciplines. DataverseNO commits to facilitate that published data remain accessible and (re)usable in a long-term perspective. The repository is owned and operated by UiT The Arctic University of Norway. DataverseNO accepts submissions from researchers primarily from Norwegian research institutions. Datasets in DataverseNO are grouped into institutional collections as well as special collections. The technical infrastructure of the repository is based on the open source application Dataverse (https://dataverse.org), which is developed by an international developer and user community led by Harvard University.