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LSHTM Data Compass is a curated digital repository of research outputs that have been produced by staff and students at the London School of Hygiene & Tropical Medicine and their collaborators. It is used to share outputs intended for reuse, including: qualitative and quantitative data, software code and scripts, search strategies, and data collection tools.
With the creation of the Metabolomics Data Repository managed by Data Repository and Coordination Center (DRCC), the NIH acknowledges the importance of data sharing for metabolomics. Metabolomics represents the systematic study of low molecular weight molecules found in a biological sample, providing a "snapshot" of the current and actual state of the cell or organism at a specific point in time. Thus, the metabolome represents the functional activity of biological systems. As with other ‘omics’, metabolites are conserved across animals, plants and microbial species, facilitating the extrapolation of research findings in laboratory animals to humans. Common technologies for measuring the metabolome include mass spectrometry (MS) and nuclear magnetic resonance spectroscopy (NMR), which can measure hundreds to thousands of unique chemical entities. Data sharing in metabolomics will include primary raw data and the biological and analytical meta-data necessary to interpret these data. Through cooperation between investigators, metabolomics laboratories and data coordinating centers, these data sets should provide a rich resource for the research community to enhance preclinical, clinical and translational research.
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LIVIVO is an interdisciplinary search engine for literature and information in the field of life sciences. It is run by ZB MED – Information Centre for Life Sciences. LIVIVO automatically searches for the terms you enter in a central index of all the databases. The ZB MED Searchportal already provides a large amount of research data from DataCite data centres (e.g. Beijing Genomics Institute, Natural Environment Research Council) in the field of life sciences. These can be searched directly using the "Documenttype=research data" filter. A further integration of data from life science data repositories is planned.