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Found 4 result(s)
The database aims to bridge the gap between agent repositories and studies documenting the effect of antimicrobial combination therapies. Most notably, our primary aim is to compile data on the combination of antimicrobial agents, namely natural products such as AMP. To meet this purpose, we have developed a data curation workflow that combines text mining, manual expert curation and graph analysis and supports the reconstruction of AMP-Drug combinations.
Country
FinBIF is an integral part of the global biodiversity informatics framework, dedicated to managing species information. Its mission encompasses a wide array of services, including the generation of digital data through various processes, as well as the sourcing, collation, integration, and distribution of existing digital data. Key initiatives under FinBIF include the digitization of collections, the development of data systems for collections Kotka (https://biss.pensoft.net/article/37179/) and observations (https://biss.pensoft.net/article/39150/), and the establishment of a national DNA barcode reference library. FinBIF manages data types such as verbal species descriptions (which include drawings, pictures, and other media types), biological taxonomy, scientific collection specimens, opportunistic systematic and event-based observations, and DNA barcodes. It employs a unified IT architecture to manage data flows, delivers services through a single online portal, fosters collaboration under a cohesive umbrella concept, and articulates development visions under a unified brand. The portal Laji.fi serves as the entry point to this harmonized open data ecosystem. FinBIF's portal is accessible in Finnish, Swedish, and English. Data intended for restricted use are made available to authorities through a separate portal, while open data are also shared with international systems, such as GBIF.
Country
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 figshare service for The Open University was launched in 2016 and allows researchers to store, share and publish research data. It helps the research data to be accessible by storing metadata alongside datasets. Additionally, every uploaded item receives a Digital Object Identifier (DOI), which allows the data to be citable and sustainable. If there are any ethical or copyright concerns about publishing a certain dataset, it is possible to publish the metadata associated with the dataset to help discoverability while sharing the data itself via a private channel through manual approval.