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As with most biomedical databases, the first step is to identify relevant data from the research community. The Monarch Initiative is focused primarily on phenotype-related resources. We bring in data associated with those phenotypes so that our users can begin to make connections among other biological entities of interest. We import data from a variety of data sources. With many resources integrated into a single database, we can join across the various data sources to produce integrated views. We have started with the big players including ClinVar and OMIM, but are equally interested in boutique databases. You can learn more about the sources of data that populate our system from our data sources page https://monarchinitiative.org/about/sources.
D-PLACE contains cultural, linguistic, environmental and geographic information for over 1400 human ‘societies’. A ‘society’ in D-PLACE represents a group of people in a particular locality, who often share a language and cultural identity. All cultural descriptions are tagged with the date to which they refer and with the ethnographic sources that provided the descriptions. The majority of the cultural descriptions in D-PLACE are based on ethnographic work carried out in the 19th and early-20th centuries (pre-1950).
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 Human Mortality Database (HMD) was created to provide detailed mortality and population data to researchers, students, journalists, policy analysts, and others interested in the history of human longevity. The Human Mortality Database (HMD) contains original calculations of death rates and life tables for national populations (countries or areas), as well as the input data used in constructing those tables. The input data consist of death counts from vital statistics, plus census counts, birth counts, and population estimates from various sources.
The information accumulated in the SPECTR-W3 ADB contains over 450,000 records and includes factual experimental and theoretical data on ionization potentials, energy levels, wavelengths, radiation transition probabilities, oscillator strengths, and (optionally) the parameters of analytical approximations of electron-collisional cross-sections and rates for atoms and ions. Those data were extracted from publications in physical journals, proceedings of the related conferences, special-purpose publications on atomic data, and provided directly by authors. The information is supplied with references to the original sources and comments, elucidating the details of experimental measurements or calculations, where necessary and available. To date, the SPECTR-W3 ADB is the largest factual database in the world containing the information on spectral properties of multicharged ions.
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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.
This database will provide a central location for scientists to browse uniquely observed proteoforms and to contribute their own datasets. Top-down proteomics is a method of protein identification that uses an ion trapping mass spectrometer to store an isolated protein ion for mass measurement and tandem mass spectrometry analysis.
This repository stores and links the openly available power-grid frequency recordings across the globe. This database is comprised of open data existent across three dimensions: - TSO data: Transmission System's Operator (TSO) recordings made public; - Research projects: Open-data database research projects; - Independent Gatherings: Industrial, private, or personal recordings that were made publicly available.
Welcome to INTERMAGNET - the global network of observatories, monitoring the Earth's magnetic field. At this site you can find data and information from geomagnetic observatories around the world. The INTERMAGNET programme exists to establish a global network of cooperating digital magnetic observatories, adopting modern standard specifications for measuring and recording equipment, in order to facilitate data exchanges and the production of geomagnetic products in close to real time.