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Found 6 result(s)
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Data Publication Server Forschungszentrum Juelich is a web server for providing large data sets to the general public. It's main application is publishing data belonging to scientific publications.
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In the framework of the Collaborative Research Centre/Transregio 32 ‘Patterns in Soil-Vegetation-Atmosphere Systems: Monitoring, Modelling, and Data Assimilation’ (CRC/TR32, www.tr32.de), funded by the German Research Foundation from 2007 to 2018, a RDM system was self-designed and implemented. The so-called CRC/TR32 project database (TR32DB, www.tr32db.de) is operating online since early 2008. The TR32DB handles all data including metadata, which are created by the involved project participants from several institutions (e.g. Universities of Cologne, Bonn, Aachen, and the Research Centre Jülich) and research fields (e.g. soil and plant sciences, hydrology, geography, geophysics, meteorology, remote sensing). The data is resulting from several field measurement campaigns, meteorological monitoring, remote sensing, laboratory studies and modelling approaches. Furthermore, outcomes of the scientists such as publications, conference contributions, PhD reports and corresponding images are collected in the TR32DB.
The GTN-P database is an object-related database open for a diverse range of data. Because of the complexity of the PAGE21 project, data provided in the GTN-P management system are extremely diverse, ranging from active-layer thickness measurements once per year to flux measurement every second and everthing else in between. The data can be assigned to two broad categories: Quantitative data which is all data that can be measured numerically. Quantitative data comprise all in situ measurements, i.e. permafrost temperatures and active layer thickness (mechanical probing, frost/thaw tubes, soil temperature profiles). Qualitative data (knowledge products) are observations not based on measurements, such as observations on soils, vegetation, relief, etc.
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The geothermal information system (GeotIS) provides information and data compilations on deep aquifers in Germany relevant for geothermal exploitation. GeotIS is a public internet based information system and satisfies the demand for a comprehensive, largely scale-independent form of a geothermal atlas which can be continuously updated. GeotIS helps users identify geothermal potentials by visualizing temperature, hydraulic properties and depth levels of relevant stratigraphic units. A sophisticated map interface simplifies the navigation to all areas of interest. An additional component contains a catalogue of all geothermal installations in Germany. The primary objective of this project is to improve the quality of geothermal-plant project-planning and the estimation of the exploration risk for geothermal projects on selectable locations. However, concrete, location-specific analyses still remain the task of local feasibility studies.
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The Marine Data Portal is a product of the “Underway”- Data initiative of the German Marine Research Alliance (Deutsche Allianz Meeresforschung - DAM) and is supported by the marine science centers AWI, GEOMAR and Hereon of the Helmholtz Association. This initiative aims to improve and standardize the systematic data collection and data evaluation for expeditions with German research vessels and marine observation. It supports scientists in their data management duties and fosters (data) science through FAIR and open access to marine research data. AWI, GEOMAR and Hereon develop this marine data hub (Marehub) to build a decentralized data infrastructure for processing, long-term archiving and dissemination of marine observation and model data and data products. The Marine Data Portal provides user-friendly, centralized access to marine research data, reports and publications from a wide range of data repositories and libraries in the context of German marine research and its international collaboration. The Marine Data Portal is developed by scientists for scientists in order to facilitate Findability and Access of marine research data for Reuse. It supports machine-readable and data driven science. Please note that the quality of the data may vary depending on the purpose for which it was originally collected.