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mdw Repository provides researchers with a robust infrastructure for research data management and ensures accessibility of research data during and after completion of research projects, thus, providing a quality boost to contemporary and future research.
The range of CIRAD's research has given rise to numerous datasets and databases associating various types of data: primary (collected), secondary (analysed, aggregated, used for scientific articles, etc), qualitative and quantitative. These "collections" of research data are used for comparisons, to study processes and analyse change. They include: genetics and genomics data, data generated by trials and measurements (using laboratory instruments), data generated by modelling (interpolations, predictive models), long-term observation data (remote sensing, observatories, etc), data from surveys, cohorts, interviews with players.
>>>!!!<<< This repository is no longer available, pleas use DataON http://doi.org/10.17616/R31NJMV3 >>>!!!<<< Domestic and foreign research data information in one place It is a national research data portal.
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MIDAS is a national research data repository. The aim of MIDAS is to collect, process, store and analyse research data and other relevant information in all fields of knowledge, enabling free, easy and convenient access to the data via the Internet. MIDAS provides services for registered and unregistered users: students, listeners, academics, researchers, scientists, research administrators, other actors of the research and studies ecosystem, and all individuals interested in research data. MIDAS consists of the MIDAS portal and MIDAS user account. The MIDAS portal is a public space accessible to anyone interested in discovering and viewing published research Data and their metadata, whereas MIDAS user account is available to registered users only. MIDAS is managed by Vilnius University.
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The sources of the data sets include data sets donated by researchers, surveys carried out by SRDA, as well as by government department and other academic organizations. Prior to the release of data sets, the confidentiality and sensitivity of every survey data set are evaluated. Standard data management and cleaning procedures are applied to ensure data accuracy and completeness. In addition, metadata and relevant supplement files are also edited and attached.