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Found 3159 result(s)
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.
Numerical database of atomic and molecular processes and particle-surface interactions. ALADDIN has formatted data on atomic structure and spectra (energy levels,wave lengths, and transition probabilities); electron and heavy particle collisions with atoms, ions, and molecules (cross sections and/or rate coefficients, including, in most cases, analytic fit to the data); sputtering of surfaces by impact of main plasma constituents and self sputtering; particle reflection from surfaces; thermophysical and thermomechanical properties of beryllium and pyrolytic graphites.
The EUROLAS Data Center (EDC) is one of the two data centers of the International Laser Ranging Service (ILRS). It collects, archives and distributes tracking data, predictions and other tracking relevant information from the global SLR network. Additionally EDC holds a mirror of the official Web-Pages of the ILRS at Goddard Space Flight Center (GSFC). And as result of the activities of the Analysis Working Group (AWG) of the ILRS, DGFI has been selected as analysis centers (AC) and as backup combination center (CC). This task includes weekly processing of SLR observations to LAGEOS-1/2 and ETALON-1/2 to compute station coordinates and earth orientation parameters. Additionally the combination of SLR solutions from the various analysis centres to a combinerd ILRS SLR solution.
The National Institute of Mental Health Data Archive (NDA) makes available human subjects data collected from hundreds of research projects across many scientific domains. The NDA provides infrastructure for sharing research data, tools, methods, and analyses enabling collaborative science and discovery. De-identified human subjects data, harmonized to a common standard, are available to qualified researchers. Summary data is available to all. The primary point of entry to the NDA is currently through the National Database for Autism Research (NDAR) website, which serves the autism research community. All NDA repositories can be accessed through this website for data contribution and querying with other scientific communities, allowing for aggregation and secondary analysis of data.
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.
TPA is a database that contains sequences built from the existing primary sequence data in GenBank. TPA records are retrieved through the Nucleotide Database and feature information on the sequence, how it was cataloged, and proper way to cite the sequence information.
The USDA Economics, Statistics and Market Information System contains reports and datasets of multiple agencies within the United States Department of Agriculture, including the Agricultural Marketing Service, the Economic Research Service, the Foreign Agricultural Service, the National Agricultural Statistics Service, and the World Agricultural Outlook Board. Historical and current reports and datasets are included.
The Gene database provides detailed information for known and predicted genes defined by nucleotide sequence or map position. Gene supplies gene-specific connections in the nexus of map, sequence, expression, structure, function, citation, and homology data. Unique identifiers are assigned to genes with defining sequences, genes with known map positions, and genes inferred from phenotypic information. These gene identifiers are used throughout NCBI's databases and tracked through updates of annotation. Gene includes genomes represented by NCBI Reference Sequences (or RefSeqs) and is integrated for indexing and query and retrieval from NCBI's Entrez and E-Utilities systems.
dbEST is a division of GenBank that contains sequence data and other information on "single-pass" cDNA sequences, or "Expressed Sequence Tags", from a number of organisms. Expressed Sequence Tags (ESTs) are short (usually about 300-500 bp), single-pass sequence reads from mRNA (cDNA). Typically they are produced in large batches. They represent a snapshot of genes expressed in a given tissue and/or at a given developmental stage. They are tags (some coding, others not) of expression for a given cDNA library. Most EST projects develop large numbers of sequences. These are commonly submitted to GenBank and dbEST as batches of dozens to thousands of entries, with a great deal of redundancy in the citation, submitter and library information. To improve the efficiency of the submission process for this type of data, we have designed a special streamlined submission process and data format. dbEST also includes sequences that are longer than the traditional ESTs, or are produced as single sequences or in small batches. Among these sequences are products of differential display experiments and RACE experiments. The thing that these sequences have in common with traditional ESTs, regardless of length, quality, or quantity, is that there is little information that can be annotated in the record. If a sequence is later characterized and annotated with biological features such as a coding region, 5'UTR, or 3'UTR, it should be submitted through the regular GenBank submissions procedure (via BankIt or Sequin), even if part of the sequence is already in dbEST. dbEST is reserved for single-pass reads. Assembled sequences should not be submitted to dbEST. GenBank will accept assembled EST submissions for the forthcoming TSA (Transcriptome Shotgun Assembly) division. The individual reads which make up the assembly should be submitted to dbEST, the Trace archive or the Short Read Archive (SRA) prior to the submission of the assemblies.
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OCTOPUS is an Open Geospatial Consortium (OGC) compliant web-enabled database that allows users to visualise, query, and download cosmogenic 10Be and 26Al, luminescence, and radiocarbon ages and denudation rates associated with erosional landscapes, Quaternary depositional landforms and archaeological records, along with associated geospatial (vector and raster) data layers.
The Research Collection is ETH Zurich's publication platform. It unites the functions of a university bibliography, an open access repository and a research data repository within one platform. Researchers who are affiliated with ETH Zurich, the Swiss Federal Institute of Technology, may deposit research data from all domains. They can publish data as a standalone publication, publish it as supplementary material for an article, dissertation or another text, share it with colleagues or a research group, or deposit it for archiving purposes. Research-data-specific features include flexible access rights settings, DOI registration and a DOI preview workflow, content previews for zip- and tar-containers, as well as download statistics and altmetrics for published data. All data uploaded to the Research Collection are also transferred to the ETH Data Archive, ETH Zurich’s long-term archive.
The U.S. Department of Energy’s (DOE) Environmental Systems Science Data Infrastructure for a Virtual Ecosystem (ESS-DIVE) data archive serves Earth and environmental science data. ESS-DIVE is funded by the Data Management program within the Climate and Environmental Science Division under the DOE’s Office of Biological and Environmental Research program (BER), and is maintained by the Lawrence Berkeley National Laboratory. ESS-DIVE will archive and publicly share data obtained from observational, experimental, and modeling research that is funded by the DOE’s Office of Science under its Subsurface Biogeochemical Research (SBR) and Terrestrial Ecosystem Science (TES) programs within the Environmental Systems Science (ESS) activity. ESS-DIVE was launched in July 2017, and is designed to provide long-term stewardship and use of data from observational, experimental and modeling activities in the DOE in the Subsurface Biogeochemical Research (SBR) and Terrestrial Ecosystem Science (TES) Programs in the Environmental System Science (ESS) activity.
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DABAR (Digital Academic Archives and Repositories) is the key component of the Croatian e-infrastructure’s data layer. It provides technological solutions that facilitate maintenance of higher education and science institutions' digital assets, i.e., various digital objects produced by the institutions and their employees.
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The population-based cancer registries in each German federal state transfer data to the German Centre for Cancer Registry Data, as required by the Federal Cancer Registry Data Act. These data are combined, quality-checked, analysed and evaluated, and the results published in collaboration with the public health institutions of the federal states.
The Tromsø Repository of Language and Linguistics (TROLLing) is a FAIR-aligned repository of linguistic data and statistical code. The archive is open access, which means that all information is available to everyone. All data are accompanied by searchable metadata that identify the researchers, the languages and linguistic phenomena involved, the statistical methods applied, and scholarly publications based on the data (where relevant). Linguists worldwide are invited to deposit data and statistical code used in their linguistic research. TROLLing is a special collection within DataverseNO (http://doi.org/10.17616/R3TV17), and C Centre within CLARIN (Common Language Resources and Technology Infrastructure, a networked federation of European data repositories; http://www.clarin.eu/), and harvested by their Virtual Language Observatory (VLO; https://vlo.clarin.eu/).
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The University of Lodz Repository is an institutional repository whose purpose is to disseminate the scholarly output of its staff and promote research conducted at the UL. It is an archive of its own electronic documents – each deposited publication or collection of research data is given a permanent identifier (handle), enabling the document to be cited and indexed in scientific databases. The University of Lodz Repository operates as an institutional repository based on Regulation No. 51 of the Rector of the University of Lodz of 31 March 2015.
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The Informatics Research Data Repository is a Japanese data repository that collects data on disciplines within informatics. Such sub-categories are things like consumerism and information diffusion. The primary data within these data sets is from experiments run by IDR on how one group is linked to another.
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DataverseNO (https://dataverse.no) is a curated, FAIR-aligned national generic repository for open research data from all academic disciplines. DataverseNO commits to facilitate that published data remain accessible and (re)usable in a long-term perspective. The repository is owned and operated by UiT The Arctic University of Norway. DataverseNO accepts submissions from researchers primarily from Norwegian research institutions. Datasets in DataverseNO are grouped into institutional collections as well as special collections. The technical infrastructure of the repository is based on the open source application Dataverse (https://dataverse.org), which is developed by an international developer and user community led by Harvard University.