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Found 5 result(s)

Inspire-HEP

Inspire-High Energy Physics

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CERN, DESY, Fermilab and SLAC have built the next-generation High Energy Physics (HEP) information system, INSPIRE. It combines the successful SPIRES database content, curated at DESY, Fermilab and SLAC, with the Invenio digital library technology developed at CERN. INSPIRE is run by a collaboration of CERN, DESY, Fermilab, IHEP, IN2P3 and SLAC, and interacts closely with HEP publishers, arXiv.org, NASA-ADS, PDG, HEPDATA and other information resources. INSPIRE represents a natural evolution of scholarly communication, built on successful community-based information systems, and provides a vision for information management in other fields of science.

Collaborative Research in Computational Neuroscience

CRCNS

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This website makes data available from the first round of data sharing projects that were supported by the CRCNS funding program. To enable concerted efforts in understanding the brain experimental data and other resources such as stimuli and analysis tools should be widely shared by researchers all over the world. To serve this purpose, this website provides a marketplace and discussion forum for sharing tools and data in neuroscience. To date we host experimental data sets of high quality that will be valuable for testing computational models of the brain and new analysis methods. The data include physiological recordings from sensory and memory systems, as well as eye movement data.

GAVO Data Centre

German Astrophysical Virtual Observatory Data Centre

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The GAVO data centre at Zentrum für Astronomie Heidelberg publishes astronomical data of all kinds – e.g., catalogues, images, spectra, time series, simulation results – in accordance with Virtual Observatory standards, making them findable and immediately usable through popular clients like TOPCAT, Aladin, or programatically through the astropy-affiliated package pyVO or the Java library STIL. We pay particular attention to providing thorough metadata to the VO Registry in order to facilitate discovery and reuse. While we have a clear focus on data produced with German contributions, we will usually publish data of other provenance, too. See https://docs.g-vo.org/DaCHS/data_checklist.html for an overview of what resource-level metadata we ask for; contact us for further information on how to publish through the German Astronomical Virtual Observatory.

Open Energy Platform

Open Energy Database

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The Open Energy Family aims to ensure quality, transparency and reproducibility in energy system research. It is a collection of various tools and information and that help working with energy related data. It is a collaborative community effort, everything is openly developed and therefore constantly evolving. The main module is the Open Energy Platform (OEP), a web interface to access most of the modules, especially the community database. It provides a way to publish data with proper documentation (metadata), and link it to source code and underlying assumptions. Open Energy Database is an open community database for energy, climate and modelling data.

Discover

UB Discover

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Discover provides access to research data from projects related to LMU Munich, which are stored and preserved in repositories of the University Library LMU.