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Found 4 result(s)
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The BonaRes Repository stores, manage and publishes soil and agricultural research data from research projects, agricultural long-term field experiments and soil profiles which contribute significantly to the analysis of changes of soil and soil functions over the long term. Research data are described by the metadata following the BonaRes Metadata Schema (DOI: 10.20387/bonares-5pgg-8yrp) which combines international recognized standards for the description of geospatial data (INSPIRE Directive) and research data (DataCite 4.0). Metadata includes AGROVOC keywords. Within the BonaRes Repository research data is provided for free reuse under the CC License and can be discovered by advanced text and map search via a number of criteria.
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The Leibniz Data Manager (LDM) is a scientific repository for research data from the fields of science and technology. The service supports a better re-usability of research data for scientific projects. The LDM fosters the management and access to heterogeneous research data publications and assists researchers in the selection of relevant data sets for their respective disciplines. The LDM currently offers the following functions for the visualization of research data: · Supports data collections and publications with different formats. · Different views on the same data set (2D and 3D support). · Visualization of Auto CAD files. · Jupyter Notes for demonstrating live code. · RDF Description of data collections.
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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.
The Integrated Resource for Reproducibility in Macromolecular Crystallography includes a repository system and website designed to make the raw data of protein crystallography more widely available. Our focus is on identifying, cataloging and providing the metadata related to datasets, which could be used to reprocess the original diffraction data. The intent behind this project is to make the resulting three dimensional structures more reproducible and easier to modify and improve as processing methods advance.