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DBpedia is a crowd-sourced community effort to extract structured information from Wikipedia and make this information available on the Web. DBpedia allows you to ask sophisticated queries against Wikipedia, and to link the different data sets on the Web to Wikipedia data. We hope that this work will make it easier for the huge amount of information in Wikipedia to be used in some new interesting ways. Furthermore, it might inspire new mechanisms for navigating, linking, and improving the encyclopedia itself.
The Analytical Geomagnetic Data Center of the Trans-Regional INTERMAGNET Segment is operated by the Geophysical Center of the Russian Academy of Sciences (GC RAS). Geomagnetic data are transmitted from observatories and stations located in Russia and near-abroad countries. The Center also provides access to spaceborne data products. The MAGNUS hardware-software system underlies the operation of the Center. Its particular feature is the automated real-time recognition of artificial (anthropogenic) disturbances in incoming data. Being based on fuzzy logic approach, this quality control service facilitates the preparation of the definitive magnetograms from preliminary records carried out by data experts manually. The MAGNUS system also performs on-the-fly multi-criteria estimation of geomagnetic activity using several indicators and provides online tools for modeling electromagnetic parameters in the near-Earth space. The collected geomagnetic data are stored using relational database management system. The geomagnetic database is intended for storing both 1-minute and 1-second data. The results of anthropogenic and natural disturbance recognition are also stored in the database.
MalaCards is an integrated database of human maladies and their annotations, modeled on the architecture and richness of the popular GeneCards database of human genes. MalaCards mines and merges varied web data sources to generate a computerized web card for each human disease. Each MalaCard contains disease specific prioritized annotative information, as well as links between associated diseases, leveraging the GeneCards relational database, search engine, and GeneDecks set-distillation tool. As proofs of concept of the search/distill/infer pipeline we find expected elucidations, as well as potentially novel ones.