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Found 15 result(s)
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BExIS is the online data repository and information system of the Biodiversity Exploratories Project (BE). The BE is a German network of biodiversity related working groups from areas such as vegetation and soil science, zoology and forestry. Up to three years after data acquisition, the data use is restricted to members of the BE. Thereafter, the data is usually public available (https://www.bexis.uni-jena.de/ddm/publicsearch/index).
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The Mansfeld's World Database of Agriculture and Horticultural Crops is an online database. As a contribution to the project "Federal Information System on Genetic Resources" (BIG, http://www.big-flora.de/). It reflects the contents of "Mansfeld's Encyclopedia of Agricultural and Horticultural Crops" (Hanelt and IPK 2001) and contains information on 6,100 crop plant species, excluding forestry and ornamental plants. Each species entry provides nomenclature and synonymy, common names in different languages, spontaneous distribution and regions of cultivation, uses, images, references, but also the ancestral species and notes on the phylogeny, variation and history.
CottonGen is a new cotton community genomics, genetics and breeding database being developed to enable basic, translational and applied research in cotton. It is being built using the open-source Tripal database infrastructure. CottonGen consolidates and expands the data from CottonDB and the Cotton Marker Database, providing enhanced tools for easy querying, visualizing and downloading research data.
This is a database for vegetation data from West Africa, i.e. phytosociological and dendrometric relevés as well as floristic inventories. The West African Vegetation Database has been developed in the framework of the projects “SUN - Sustainable Use of Natural Vegetation in West Africa” and “Biodiversity Transect Analysis in Africa” (BIOTA, https://www.biota-africa.org/).
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Attention! Data sets are not updated anymore. Please, visit the BonaRes Repositor​ium​ for new datasets. Open Research Data provides quality assessed data and their metadata such as context information on measurement objectives, equipment, methods, testing and investigation areas. The purpose of the repository is to secure quality, integrity and long-term availability of landscape and ecosystem research data as well as to enhance accessibility of free data from ZALF long-term monitoring campaigns, landscape laboratories (Agro-ScapeLabs), field trials and experiments. The Leibniz Centre for Agricultural Landscape Research (ZALF) explores ecosystems in agricultural landscapes and the development of ecologically and economically viable land use systems. ZALF combines scientific expertise from agricultural science, geosciences, biosciences and socio-economics.
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The Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) is a community-driven climate impact modeling initiative that aims to contribute to a quantitative and cross-sectoral synthesis of the various impacts of climate change, including associated uncertainties. It is designed as a continuous model intercomparison and improvement process for climate impact models and is supported by the international climate impact research community. ISIMIP is organized into simulation rounds, for which a simulation protocol specifies a set of common experiments. The protocol further describes a set of climate and direct human forcing data to be used as input data for all ISIMIP simulations. Based on this information, modelling groups from different sectors (e.g. agriculture, biomes, water) perform simulations using various climate impact models. After the simulations are performed, the data is collected by the ISIMIP data team, quality controlled and eventually published on the ISIMIP Repository. From there, it can be freely accessed for further research and analyses. The data is widely used within academia, but also by companies and civil society. ISIMIP was initiated by the Potsdam Institute for Climate Impact Research (PIK) and the International Institute for Applied Systems Analysis (IIASA).
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The TRR228DB is the project-database of the Collaborative Research Centre 228 "Future Rural Africa: Future-making and social-ecological transformation" (CRC/Transregio 228, https://www.crc228.de) funded by the German Research Foundation (DFG, German Research Foundation – Project number 328966760). The project-database is a new implementation of the TR32DB and online since 2018. It handles all data including metadata, which are created by the involved project participants from several institutions (e.g. Universities of Cologne and Bonn) and research fields (e.g. anthropology, agroeconomics, ecology, ethnology, geography, politics and soil sciences). The data is resulting from several field campaigns, interviews, surveys, remote sensing, laboratory studies and modelling approaches. Furthermore, outcomes of the scientists such as publications, conference contributions, PhD reports and corresponding images are collected.
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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.
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The Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) and German Plant Phenotyping Network (DPPN) has jointly initiated the Plant Genomics and Phenomics Research Data Repository (PGP) as infrastructure to comprehensively publish plant research data. This covers in particular cross-domain datasets that are not being published in central repositories because of its volume or unsupported data scope, like image collections from plant phenotyping and microscopy, unfinished genomes, genotyping data, visualizations of morphological plant models, data from mass spectrometry as well as software and documents.
Subject(s)
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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.
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The company RapidEye AG of Brandenburg brought on 29 August 2008 five satellites into orbit that can be aligned within a day to any point on Earth. The data are interesting for a number of large and small companies for applications from harvest planning to assessment of insurance claims case of natural disasters. Via the Rapid Eye Science Archive (RESA) science users can receive, free of charge, optical image data of the RapidEye satellite fleet. Imagery is allocated based on a proposal to be submitted via the RESA Portal which will be evaluated by independent experts.
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The CRC1211DB is the project-database of the Collaborative Research Centre 1211 "Earth -Evolution at the dry limit" (CRC1211, https://sfb1211.uni-koeln.de/) funded by the German Research Foundation (DFG, German Research Foundation – Projektnummer 268236062). The project-database is a new implementation of the TR32DB and online since 2016. It 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, biology, geography, geology, meteorology and 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.
Content type(s)
LIAS is a global information system for Lichenized and Non-Lichenized Ascomycetes. It includes several interoperable data repositories. In recent years, the two core components ‘LIAS names’ and ‘LIAS light’ have been much enlarged. LIAS light is storing phenotypic trait data. They includes > 10,700 descriptions (about 2/3 of all known lichen species), each with up to 75 descriptors comprising 2,000 traits (descriptor states and values), including 800 secondary metabolites. 500 traits may have biological functions and more than 1,000 may have phylogenetic relevance. LIAS is thus one of the most comprehensive trait databases in organismal biology. The online interactive identification key for more than 10,700 lichens is powered by the Java applet NaviKey and has been translated into 19 languages (besides English) in cooperation with lichenologists worldwide. The component ‘LIAS names’ is a platform for managing taxonomic names and classifications with currently >50,000 names, including the c. 12,000 accepted species and recognized synonyms. The LIAS portal contents, interfaces, and databases run on servers of the IT Center of the Bavarian Natural History Collections and are maintained there. 'LIAS names' and ‘LIAS light’ also deliver content data to the Catalogue of Life, acting as the Global Species Database (GSD) for lichens. LIAS gtm is a database for visualising the geographic distribution of lichen traits. LIAS is powered by the Diversity Workbench database framework with several interfaces for data management and publication. The LIAS long-term project was initiated in the early 1990s and has since been continued with funding from the DFG, the BMBF, and the EU.