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Found 1510 result(s)
The Durham High Energy Physics Database (HEPData), formerly: the Durham HEPData Project, has been built up over the past four decades as a unique open-access repository for scattering data from experimental particle physics. It currently comprises the data points from plots and tables related to several thousand publications including those from the Large Hadron Collider (LHC). The Durham HepData Project has for more than 25 years compiled the Reactions Database containing what can be loosly described as cross sections from HEP scattering experiments. The data comprise total and differential cross sections, structure functions, fragmentation functions, distributions of jet measures, polarisations, etc... from a wide range of interactions. In the new HEPData site (hepdata.net), you can explore new functionalities for data providers and data consumers, as well as the submission interface. HEPData is operated by CERN and IPPP at Durham University and is based on the digital library framework Invenio.
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The GeoPortal.rlp allows the central search and visualization of geo data. Inside the geo data infrastructure of Rhineland-Palatinate the GeoPortal.rlp inherit the central duty a service orientated branch exchange between user and offerer of geo data. The GeoPortal.rlp establishes the access to geo data over the electronic network. The GeoPortal.rlp was brought on line on January, 8th 2007 for the first time, on February, 2nd 2011 it occured a site-relaunch.
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Three parts of a database provide published and unpublished chemical analysis results of archaeological ceramics. These are the results of forty years of applying WD-XRF and other mineralogical and physical laboratory methods to the analysis of sherds from excavations and museums. Drawing on some 30,000 analyses from research projects in Europe, Turkey, the near East, and Sudan, the part published here covers the results of three long-term projects: Early pottery in Thessaly, Greece (1,305 records), Firmalampen and other Roman lamps (1,666 records), and Roman and other pottery produced in Central Europe (4,043 records). This collated information provides an opportunity to work directly on published and unpublished data. These can be used as chemical reference groups for comparison for fine ware classification and in provenance studies.
>>>!!!<<< 2019-01: Global Land Cover Facility goes offline see https://spatialreserves.wordpress.com/2019/01/07/global-land-cover-facility-goes-offline/ ; no more access to http://www.landcover.org >>>!!!<<< The Global Land Cover Facility (GLCF) provides earth science data and products to help everyone to better understand global environmental systems. In particular, the GLCF develops and distributes remotely sensed satellite data and products that explain land cover from the local to global scales.
The Deep Blue Data repository is a means for University of Michigan researchers to make their research data openly accessible to anyone in the world, provided they meet collections criteria. Submitted data sets undergo a curation review by librarians to support discovery, understanding, and reuse of the data.
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Open Government Data Portal of Tamil Nadu is a platform (designed by the National Informatics Centre), for Open Data initiative of the Government of Tamil Nadu. The portal is intended to publish datasets collected by the Tamil Nadu Government for public uses in different perspective. It has been created under Software as A Service (SaaS) model of Open Government Data (OGD) and publishes dataset in open formats like CSV, XLS, ODS/OTS, XML, RDF, KML, GML, etc. This data portal has following modules, namely (a) Data Management System (DMS) for contributing data catalogs by various state government agencies for making those available on the front end website after a due approval process through a defined workflow; (b) Content Management System (CMS) for managing and updating various functionalities and content types; (c) Visitor Relationship Management (VRM) for collating and disseminating viewer feedback on various data catalogs; and (d) Communities module for community users to interact and share their views and common interests with others. It includes different types of datasets generated both in geospatial and non-spatial data classified as shareable data and non-shareable data. Geospatial data consists primarily of satellite data, maps, etc.; and non-spatial data derived from national accounts statistics, price index, census and surveys produced by a statistical mechanism. It follows the principle of data sharing and accessibility via Openness, Flexibility, Transparency, Quality, Security and Machine-readable.
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<<<!!!<<< The website www.geobase.ca/ closed in January 2015. >>>!!!>>> All GeoBase products are available on the Open Government of Canada portal: https://open.canada.ca/data/en/dataset?q=geobase&organization=nrcan-rncan GeoBase initiative provides geospatial data of the entire Canadian landmass for government, business, and/or personal assessments of sustainable resource development, public safety, sanitation, and environmental protection. Data is available for download as ESRI Shapefile, FGDB, KML, and GML.
We present the MUSE-Wide survey, a blind, 3D spectroscopic survey in the CANDELS/GOODS-S and CANDELS/COSMOS regions. Each MUSE-Wide pointing has a depth of 1 hour and hence targets more extreme and more luminous objects over 10 times the area of the MUSE-Deep fields (Bacon et al. 2017). The legacy value of MUSE-Wide lies in providing "spectroscopy of everything" without photometric pre-selection. We describe the data reduction, post-processing and PSF characterization of the first 44 CANDELS/GOODS-S MUSE-Wide pointings released with this publication. Using a 3D matched filtering approach we detected 1,602 emission line sources, including 479 Lyman-α (Lya) emitting galaxies with redshifts 2.9≲z≲6.3. We cross-match the emission line sources to existing photometric catalogs, finding almost complete agreement in redshifts and stellar masses for our low redshift (z < 1.5) emitters. At high redshift, we only find ~55% matches to photometric catalogs. We encounter a higher outlier rate and a systematic offset of Δz≃0.2 when comparing our MUSE redshifts with photometric redshifts. Cross-matching the emission line sources with X-ray catalogs from the Chandra Deep Field South, we find 127 matches, including 10 objects with no prior spectroscopic identification. Stacking X-ray images centered on our Lya emitters yielded no signal; the Lya population is not dominated by even low luminosity AGN. A total of 9,205 photometrically selected objects from the CANDELS survey lie in the MUSE-Wide footprint, which we provide optimally extracted 1D spectra of. We are able to determine the spectroscopic redshift of 98% of 772 photometrically selected galaxies brighter than 24th F775W magnitude. All the data in the first data release - datacubes, catalogs, extracted spectra, maps - are available at the website.
coastDat is a model based data bank developed mainly for the assessment of long-term changes in data sparse regions. A sequence of numerical models is employed to reconstruct all aspects of marine climate (such as storms, waves, surges etc.) over many decades of years relying only on large-scale information such as large-scale atmospheric conditions or bathymetry.
The repository is no longer available. >>>!!!<<< 2021-01-25: no more access to California Water CyberInfrastructure >>>!!!<<<
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The TRR228DB is the project-database of the Collaborative Research Centre 228 "Future Rural Africa: Future-making and social-ecological transformation" (CRC/Transregio 228, https://www.crc228.de) funded by the German Research Foundation (DFG, German Research Foundation – Project number 328966760). The project-database is a new implementation of the TR32DB and online since 2018. It handles all data including metadata, which are created by the involved project participants from several institutions (e.g. Universities of Cologne and Bonn) and research fields (e.g. anthropology, agroeconomics, ecology, ethnology, geography, politics and soil sciences). The data is resulting from several field campaigns, interviews, surveys, remote sensing, laboratory studies and modelling approaches. Furthermore, outcomes of the scientists such as publications, conference contributions, PhD reports and corresponding images are collected.
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UCrea offers electronic access to documents generated by UC members in their academic, learning or research activity. The aim is to give greater visibility to academic production, increase impact and ensure preservation. UCrea supports documentation in various electronic formats and can include academic papers, research projects, preprints, articles, conference papers, etc.
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The Libraries offer members of the Université de Montréal community the opportunity to publish their research data in a Dataverse repository space
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The OPA Division deals with the development of models and methods for interdisciplinary research on marine operational forecasting, on the interactions between coastal areas and the open ocean, on the development of services and applications for all maritime economy sectors, including transport, security and management of coastal areas and marine resources, in the context of climate change adaptation problems.
Water DAMS (Water Data Analysis and Management System) provides access to foundational water treatment technology data that enable researchers and decision-makers to identify and quantify opportunities for technology innovations to reduce the cost and energy intensity of desalination. It is the submission point for all data generated by research conducted by the National Alliance for Water Innovation (NAWI) and is designed to be used by the broader water research community. With publicly accessible contributions from a variety of academic and industrial partners, Water DAMS seeks to enable data discoverability, improve accessibility, and accelerate collaboration that contributes to pipe parity and innovation in water treatment technologies.
The NREL Data Catalog is where descriptive information (i.e., metadata) is maintained about public data resulting from federally funded research conducted by the National Renewable Energy Laboratory (NREL) researchers and analysts. Our Goal: Making Federally Funded Data Publicly Available NREL's mission is to develop clean energy and energy efficiency technologies and practices, advance related science and engineering, and provide knowledge and innovations to integrate energy systems at all scales. The NREL Data Catalog helps accomplish this by ensuring the data behind the science and engineering are well-documented and useful to the scientific community at large.
HepSim is a public repository with Monte Carlo simulations for particle-collision experiments. It contains predictions from leading-order (LO) parton shower models, next-to-leading order (NLO) and NLO with matched parton showers. It also includes Monte Carlo events after fast ("parametric") and full (Geant4) detector simulations and event reconstruction.
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AUB ScholarWorks is a digital service that collects, preserves, and distributes digital material. AUB ScholarWorks hosts not only articles, but any other kind of research output, such as research data.
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Dataverse for faculty, researchers, and students at St. Francis Xavier University or affiliated institutions. Hosted by Borealis.
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TIB’s core task is to provide science and industry with both elementary and highly technical specialist and researchinformation. TIB has globally unique collections in the subject areas of science and technology, as well as architecture,chemistry, computer science, mathematics and physics. Besides textual materials, the library’s collections also includeknowledge objects such as research data, 3D models and audiovisual media. The TIB has assumed responsibility for the long-term preservation and availability of the digital materials it collects and documents, as well as their interpretability for use by different target groups. To this end, it has created the necessary infrastructure and guarantees the permanent provision of both material and human resources. Search for research data search at: https://www.tib.eu/en/search-discover/research-data