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Found 498 result(s)
The Universal Protein Resource (UniProt) is a comprehensive resource for protein sequence and annotation data. The UniProt databases are the UniProt Knowledgebase (UniProtKB), the UniProt Reference Clusters (UniRef), and the UniProt Archive (UniParc).
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The Research Data Center for Higher Education Research and Science Studies (FDZ-DZHW) at the German Centre for Higher Education Research and Science Studies (DZHW) in Hannover provides the scientific community with quantitative and qualitative research data from the field of higher education and science studies for research and teaching purposes. The data pool of the Research Data Centre is based on two sources: Firstly, it contains the current surveys of the panels conducted in-house (especially DZHW Graduate Panel, Social Survey, DZHW Panel Study of School Leavers with a Higher Education Entrance Qualification, DZHW Scientists Survey), which are integrated by default. Secondly, the Research Data Centre constantly processes, documents and integrates inventory data of the DZHW and its prior organisations. External data from the research area is also integrated into the FDZ data pool.
The Arizona State University (ASU) Research Data Repository provides a platform for ASU-affiliated researchers to share, preserve, cite, and make research data accessible and discoverable. The ASU Research Data Repository provides a permanent digital identifier for research data, which complies with data sharing policies. The repository is powered by the Dataverse open-source application, developed and used by Harvard University. Both the ASU Research Data Repository and the KEEP Institutional Repository are managed by the ASU Library to ensure research produced at Arizona State University is discoverable and accessible to the global community.
META-SHARE, the open language resource exchange facility, is devoted to the sustainable sharing and dissemination of language resources (LRs) and aims at increasing access to such resources in a global scale. META-SHARE is an open, integrated, secure and interoperable sharing and exchange facility for LRs (datasets and tools) for the Human Language Technologies domain and other applicative domains where language plays a critical role. META-SHARE is implemented in the framework of the META-NET Network of Excellence. It is designed as a network of distributed repositories of LRs, including language data and basic language processing tools (e.g., morphological analysers, PoS taggers, speech recognisers, etc.). Data and tools can be both open and with restricted access rights, free and for-a-fee.
Research data from University of Pretoria. This data repository facilitates data publishing, sharing and collaboration of academic research, allowing UP to manage and in some cases showcase its data to the wider research community. Previously UPSpace (https://repository.up.ac.za/) was used for both datasets and research outputs. Now UP Research Data Repository is dedicated for datasets.
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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.
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.
The Perovskite Database Project aims at making all perovskite device data, both past and future, available in a form adherent to the FAIR data principles, i.e. findable, accessible, interoperable, and reusable.
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.
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GEOFON seeks to facilitate cooperation in seismological research and earthquake and tsunami hazard mitigation by providing rapid transnational access to seismological data and source parameters of large earthquakes, and keeping these data accessible in the long term. It pursues these aims by operating and maintaining a global network of permanent broadband stations in cooperation with local partners, facilitating real time access to data from this network and those of many partner networks and plate boundary observatories, providing a permanent and secure archive for seismological data. It also archives and makes accessible data from temporary experiments carried out by scientists at German universities and institutions, thereby fostering cooperation and encouraging the full exploitation of all acquired data and serving as the permanent archive for the Geophysical Instrument Pool at Potsdam (GIPP). It also organises the data exchange of real-time and archived data with partner institutions and international centres.
EBRAINS offers one of the most comprehensive platforms for sharing brain research data ranging in type as well as spatial and temporal scale. We provide the guidance and tools needed to overcome the hurdles associated with sharing data. The EBRAINS data curation service ensures that your dataset will be shared with maximum impact, visibility, reusability, and longevity, hhttps://www.ebrains.eu/data/find-data/. Find data - the user interface of the EBRAINS Knowledge Graph - allows you to easily find data of interest. EBRAINS hosts a wide range of data types and models from different species. All data are well described and can be accessed immediately for further analysis.
BSRN is a project of the Radiation Panel (now the Data and Assessment Panel) from the Global Energy and Water Cycle Experiment (GEWEX) under the umbrella of the World Climate Research Programme (WCRP). It is the global baseline network for surface radiation for the Global limate Observing System (GCOS), contributing to the Global Atmospheric Watch (GAW), and forming a ooperative network with the Network for the Detection of Atmospheric Composition Change NDACC).
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AUSSDA - The Austrian Social Science Data Archive is a certified, national research infrastructure for the social science community. We offer sustainable and easy-to-use services in the field of digital archiving and preservation. The main beneficiaries are researchers, students, educational institutions and media professionals. We implement international standards to make research data findable, accessible, interoperable and reusable according to the FAIR principles. AUSSDA supports the open science movement to maximize the potential for data reuse. We stand for integrity in archiving and advocate for compliance with data protection and ethical principles in research data management. AUSSDA represents Austria as a national service provider in CESSDA ERIC, has locations at the universities of Vienna, Graz, Linz, Innsbruck, Krems and at the OeAW (Austrian Academy of Sciences) and works within a network of national and international partners.
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The project analyzes educational processes in Germany from early childhood to late adulthood. The National Educational Panel Study (NEPS) has been set up to find out more about the acquisition of education in Germany, to plot the consequences of education for individual biographies, and to describe central educational processes and trajectories across the entire life span. Such an interdisciplinary consortium of research institutes, researcher groups, and research. personalities has been assembled in Bamberg. In addition, the competencies and experiences with longitudinal research available at numerous other locations have been networked to form a cluster of excellence.
The Arctic Permafrost Geospatial Centre (APGC) is an Open Access Circum-Arctic Geospatial Data Portal that promotes, describes and visualizes geospatial permafrost data. A data catalogue and a WebGIS application allow to easily discover and view data and metadata. Data can be downloaded directly via link to the publishing data repository.
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.
Yoda publishes research data on behalf of researchers that are affiliated with Utrecht University, its research institutes and consortia where it acts as a coordinating body. Data packages are not limited to a particular field of research or license. Yoda publishes data packages via Datacite. To find data publications use: https://public.yoda.uu.nl/, or the Datacite search engine: https://commons.datacite.org/doi.org?query=client.uid:delft.uu
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Research Data Finder is QUT’s discovery service for research data created or collected by QUT researchers. Designed to promote the visibility of QUT research datasets, Research Data Finder provides descriptions about shareable, reusable datasets available via open or mediated access.
The ZINC Database contains commercially available compounds for structure based virtual screening. It currently has compounds that can simply be purchased. It is provided in ready-to-dock, 3D formats with molecules represented in biologically relevant forms. It is available in subsets for general screening as well as target-, chemotype- and vendor-focused subsets. ZINC is free for everyone to use and download at the website zinc.docking.org.
NACDA acquires and preserves data relevant to gerontological research, processing as needed to promote effective research use, disseminates them to researchers, and facilitates their use. By preserving and making available the largest library of electronic data on aging in the United States, NACDA offers opportunities for secondary analysis on major issues of scientific and policy relevance
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BIBB has a strong tradition of survey-based research. It initiates and realises the collection of individual and firm-level data on crucial positions and transitions in the education and labour market system. The BIBB-FDZ covers a variety of data deploying different units of analysis and temporal designs and focusing on various thematic issues. Standard access to well prepared firm- and individual-level data on the attainment and utilization of vocational education and training Documentation of these data sets, i.e. a description of their central characteristics, main issues and variables, data collection, anonymisation, weighting and recoding etc. Advisory service on data choice, data access and handling, research potential and scope and validity of the data. Supply of a range of data tools such as standard measures and classifications in the fields of education, occupations, industries and regions (if possible also including cross-national fields), formally anonymous data for remote data access, or references to publications with the data.
>>>>!!!<<<<As of March 28, 2016, the 'NSF Arctic Data Center' will serve as the current repository for NSF-funded Arctic data. The ACADIS Gateway http://www.aoncadis.org is no longer accepting data submissions. All data and metadata in the ACADIS system have been transferred to the NSF Arctic Data Center system. There is no need for you to resubmit existing data. >>>>!!!<<<< ACADIS is a repository for Arctic research data to provide data archival, preservation and access for all projects funded by NSF's Arctic Science Program (ARC). Data include long-term observational timeseries, local, regional, and system-scale research from many diverse domains. The Advanced Cooperative Arctic Data and Information Service (ACADIS) program includes data management services.
Data Observation Network for Earth (DataONE) is the foundation of new innovative environmental science through a distributed framework and sustainable cyberinfrastructure that meets the needs of science and society for open, persistent, robust, and secure access to well-described and easily discovered Earth observational data. Supported by the U.S. National Science Foundation (Grant #OCI-0830944) as one of the initial DataNets, DataONE will ensure the preservation, access, use and reuse of multi-scale, multi-discipline, and multi-national science data via three primary cyberinfrastucture elements and a broad education and outreach program.