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Found 128 result(s)
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<<<!!!<<< The ZACAT server is end-of-life The ZACAT server is EOL and has been taken offline. The software driving the portal has been unmaintained for several years and could no longer be reasonably sustained. We have expanded https://search.gesis.org to include information on the studies' variable level where available, which is a superset of the studies in ZACAT. Please use the variable search on https://search.gesis.org to identify and download datasets. >>>!!!>>>
The repository contains the complete model of the Bern campaign; only the upper part of the vault could not be measured due to renovation works carried out on the dome at the time of the campaign.
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The German Neuroinformatics Node's data infrastructure (GIN) services provide a platform for comprehensive and reproducible management and sharing of neuroscience data. Building on well established versioning technology, GIN offers the power of a web based repository management service combined with a distributed file storage. The service addresses the range of research data workflows starting from data analysis on the local workstation to remote collaboration and data publication.
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The Edition Topoi research platform is an innovative, reliable information infrastructure. It serves the publication of citable research data such as 3D models, high-resolution pictures, data and databases. The content and its meta data are subject to peer review and made available on an Open Access basis. The published or publishable combination of citable research content and its technical and contextually relevant meta data is defined as Citable. The public data are generated via a cloud and can be directly connected with the individual computing environment.
The measured values of the panel form the basis for a 3D reconstruction of the panel, which was calculated using photos taken by Gerd Graßhoff and Joanna Pruszynska with kind support of the Museum Warmii in autumn 2016. This repository contains the photos, the models, and the research data derived from them.
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.
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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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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.
Sharing and preserving data are central to protecting the integrity of science. DataHub, a Research Computing endeavor, provides tools and services to meet scientific data challenges at Pacific Northwest National Laboratory (PNNL). DataHub helps researchers address the full data life cycle for their institutional projects and provides a path to creating findable, accessible, interoperable, and reusable (FAIR) data products. Although open science data is a crucial focus of DataHub’s core services, we are interested in working with evidence-based data throughout the PNNL research community.
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SODHA is the federal Belgian data archive for social sciences and the digital humanities. SODHA is a new service of the State Archives of Belgium and acts as the Belgian service provider for the Consortium of European Social Science Data Archives (CESSDA).
With the Program EnviDat we develop a unified and managed access portal for WSL's rich reservoir of environmental monitoring and research data. EnviDat is designed as a portal to publish, connect and search across existing data but is not intended to become a large data centre hosting original data. While sharing of data is centrally facilitated, data management remains decentralised and the know-how and responsibility to curate research data remains with the original data providers.
A community platform to Share Data, Publish Data with a DOI, and get Citations. Advancing Spinal Cord Injury research through sharing of data from basic and clinical research.
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Lithuanian Data Archive for Social Sciences and Humanities (LiDA) is a virtual digital infrastructure for SSH data and research resources acquisition, long-term preservation and dissemination. All the data and research resources are documented in both English and Lithuanian according to international standards. Access to the resources is provided via Dataverse repository. LiDA curates different types of resources and they are published into catalogues according to the type: Survey Data, Aggregated Data (including Historical Statistics), Encoded Data (including News Media Studies), and Textual Data. Also, LiDA holds collections of social sciences and humanities data deposited by Lithuanian science and higher education institutions and Lithuanian state institutions (Data of Other Institutions). LiDA is hosted by the Centre for Data Analysis and Archiving of Kaunas University of Technology (data.ktu.edu).
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Global Change Research Data Publishing and Repository (GCdataPR) is an open data infrastructure on earth science, particular on the global environmental changes. The GCdataPR’ management policies following the international common understanding to the data sharing principles and guidelines is the key to make the qualified data publishing and sharing smoothly and successfully. The data management policies including dataset submission for publishing policy, peer review policy data quality control policy data long-term preservation policy, data sharing policy, 10% rule for identify original dataset policy, claim discovery with both data and paper policy, and data service statistics policy.
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Launched in February 2020, data.sciencespo is a repository that offers visibility, sharing and preservation of data collected, curated and processed at Sciences Po. The repository is based on the Dataverse open-source software and organised into collections: CDSP Collection This collection managed by the Centre des données socio-politiques (CDSP) includes the catalogue of surveys, in the social science and humanities, processed and curated by CDSP engineers since 2005. This catalogue brings together surveys produced at Sciences Po and other French and international institutions. - Sciences Po collection (self-deposit) This collection, which is managed by the Direction des ressources et de l'information scientifique (DRIS), is intended to host data produced by researchers affiliated with Sciences Po, following the self-deposit process assisted by the Library's staff.
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The BonaRes Repository stores, manage and publishes soil and agricultural research data from research projects, agricultural long-term field experiments and soil profiles which contribute significantly to the analysis of changes of soil and soil functions over the long term. Research data are described by the metadata following the BonaRes Metadata Schema (DOI: 10.20387/bonares-5pgg-8yrp) which combines international recognized standards for the description of geospatial data (INSPIRE Directive) and research data (DataCite 4.0). Metadata includes AGROVOC keywords. Within the BonaRes Repository research data is provided for free reuse under the CC License and can be discovered by advanced text and map search via a number of criteria.
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media/rep/ is the disciplinary repository for German-language media studies. It offers free and open access to publications and research data in media studies and related disciplines.
Cocoon "COllections de COrpus Oraux Numériques" is a technical platform that accompanies the oral resource producers, create, organize and archive their corpus; a corpus can consist of records (usually audio) possibly accompanied by annotations of these records. The resources registered are first cataloged and stored while, and then, secondly archived in the archive of the TGIR Huma-Num. The author and his institution are responsible for filings and may benefit from a restricted and secure access to their data for a defined period, if the content of the information is considered sensitive. The COCOON platform is jointly operated by two joint research units: Laboratoire de Langues et civilisations à tradition orale (LACITO - UMR7107 - Université Paris3 / INALCO / CNRS) and Laboratoire Ligérien de Linguistique (LLL - UMR7270 - Universités d'Orléans et de Tours, BnF, CNRS).
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This data repository allows users to publish animal tracking datasets that have been uploaded to Movebank (https://www.movebank.org/ ). Published datasets have gone through a submission and review process, and are typically associated with a written study published in an academic journal. All animal tracking data in this repository are available to the public.
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Agri-environmental Research Data collection is part of the University of Guelph Research Data Repositories (University of Guelph Dataverse). The purpose of this collection is to provide access to, and long-term stewardship of, agricultural and environmental data created at or in cooperation with the University of Guelph.
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The Research Data Centre (Forschungsdatenzentrum, FDZ) at the Institute for Educational Quality Improvement (Institut zur Qualitätsentwicklung im Bildungswesen, IQB) archives and documents data sets resulting from national and international assessment studies (such as DESI, PIRLS, PISA, IQB-Bildungstrends). Moreover, the FDZ makes these data sets available for re- and secondary analysis. Members of the scientific community can apply for access to the data sets archived at the FDZ.
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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.
UCLA Library is adopting Dataverse, the open source web application designed for sharing, preserving and using research data. UCLA Dataverse will allow data, text, software, scripts, data visualizations, etc., created from research projects at UCLA to be made publicly available, widely discoverable, linkable, and ultimately, reusable