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The British Geological Survey (BGS), the world’s oldest national geological survey, has over 400 datasets including environmental monitoring data, digital databases, physical collections (borehole core, rocks, minerals and fossils), records and archives.
mzCloud is an extensively curated database of high-resolution tandem mass spectra that are arranged into spectral trees. MS/MS and multi-stage MSn spectra were acquired at various collision energies, precursor m/z, and isolation widths using Collision-induced dissociation (CID) and Higher-energy collisional dissociation (HCD). Each raw mass spectrum was filtered and recalibrated giving rise to additional filtered and recalibrated spectral trees that are fully searchable. Besides the experimental and processed data, each database record contains the compound name with synonyms, the chemical structure, computationally and manually annotated fragments (peaks), identified adducts and multiply charged ions, molecular formulas, predicted precursor structures, detailed experimental information, peak accuracies, mass resolution, InChi, InChiKey, and other identifiers. mzCloud is a fully searchable library that allows spectra searches, tree searches, structure and substructure searches, monoisotopic mass searches, peak (m/z) searches, precursor searches, and name searches. mzCloud is free and available for public use online.
The UCD Digital Library is a platform for exploring cultural heritage, engaging with digital scholarship, and accessing research data. The UCD Digital Library allows you to search, browse and explore a growing collection of historical materials, photographs, art, interviews, letters, and other exciting content, that have been digitised and made freely available.
The Human Ageing Genomic Resources (HAGR) is a collection of databases and tools designed to help researchers study the genetics of human ageing using modern approaches such as functional genomics, network analyses, systems biology and evolutionary analyses.
When published in 2005, the Millennium Run was the largest ever simulation of the formation of structure within the ΛCDM cosmology. It uses 10(10) particles to follow the dark matter distribution in a cubic region 500h(−1)Mpc on a side, and has a spatial resolution of 5h−1kpc. Application of simplified modelling techniques to the stored output of this calculation allows the formation and evolution of the ~10(7) galaxies more luminous than the Small Magellanic Cloud to be simulated for a variety of assumptions about the detailed physics involved. As part of the activities of the German Astrophysical Virtual Observatory we have created relational databases to store the detailed assembly histories both of all the haloes and subhaloes resolved by the simulation, and of all the galaxies that form within these structures for two independent models of the galaxy formation physics. We have implemented a Structured Query Language (SQL) server on these databases. This allows easy access to many properties of the galaxies and halos, as well as to the spatial and temporal relations between them. Information is output in table format compatible with standard Virtual Observatory tools. With this announcement (from 1/8/2006) we are making these structures fully accessible to all users. Interested scientists can learn SQL and test queries on a small, openly accessible version of the Millennium Run (with volume 1/512 that of the full simulation). They can then request accounts to run similar queries on the databases for the full simulations. In 2008 and 2012 the simulations were repeated.
The ADAS Project is a self-funding (i.e. funded by participants) project consisting of most major fusion laboratories along with other astrophysical and university groups. As an implementation, it is an interconnected set of computer codes and data collections for modelling the radiating properties of ions and atoms in plasmas. It can address plasmas ranging from the interstellar medium through the solar atmosphere and laboratory thermonuclear fusion devices to technological plasmas. ADAS assists in the analysis and interpretation of spectral emission and supports detailed plasma models.