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Found 44 result(s)
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SMU Research Data Repository (SMU RDR) is a tool and service for researchers from Singapore Management University (SMU) to store, share and publish their research data. SMU RDR accepts a wide range of research data and outputs generated from research projects.
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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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ACU Research Bank is the Australian Catholic University's institutional research repository. It serves to collect, preserve, and showcase the research publications and outputs of ACU staff and higher degree students. Where possible and permissible, a full text version of a research output is available as open access.
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bonndata is the institutional, FAIR-aligned and curated, cross-disciplinary research data repository for the publication of research data for all researchers at the University of Bonn. The repository is fully embedded into the University IT and Data Center and curated by the Research Data Service Center (https://www.forschungsdaten.uni-bonn.de/en). The software that bonndata is based on is the open source software Dataverse (https://dataverse.org)
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.
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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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Created and managed by the Library, DataSpace@HKUST is the data repository and workspace service for HKUST research community. Faculty members and research postgraduate students can use the platform to store, share, organize, preserve and publish research data. It is built on Dataverse, an open source web application developed at Harvard’s Institute for Quantitative Social Science. Using Dataverse architecture, the repository hosts multiple "dataverses". Each dataverse contains datasets; while each dataset may contain multiple data files and the corresponding descriptive metadata.
ICRISAT performs crop improvement research, using conventional as well as methods derived from biotechnology, on the following crops: Chickpea, Pigeonpea, Groundnut, Pearl millet,Sorghum and Small millets. ICRISAT's data repository collects, preserves and facilitates access to the datasets produced by ICRISAT researchers to all users who are interested in. Data includes Phenotypic, Genotypic, Social Science, and Spatial data, Soil and Weather.
Brainlife promotes engagement and education in reproducible neuroscience. We do this by providing an online platform where users can publish code (Apps), Data, and make it "alive" by integragrate various HPC and cloud computing resources to run those Apps. Brainlife also provide mechanisms to publish all research assets associated with a scientific project (data and analyses) embedded in a cloud computing environment and referenced by a single digital-object-identifier (DOI). The platform is unique because of its focus on supporting scientific reproducibility beyond open code and open data, by providing fundamental smart mechanisms for what we refer to as “Open Services.”
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Swedish National Data Service (SND) is a research data infrastructure designed to assist researchers in preserving, maintaining, and disseminating research data in a secure and sustainable manner. The SND Search function makes it easy to find, use, and cite research data from a variety of scientific disciplines. Together with an extensive network of almost 40 Swedish higher education institutions and other research organisations, SND works for increased access to research data, nationally as well as internationally.
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The UWA Profiles and Research Repository contains research publications, research datasets, theses, equipment, grants and activities created by researchers and postgraduates affiliated with the University of Western Australia (UWA). It is managed by the University Library and provides access to research datasets held at UWA. The information about each dataset has been provided by UWA research groups. Dataset metadata is harvested into Research Data Australia (RDA) https://researchdata.edu.au/.
Content type(s)
A machine learning data repository with interactive visual analytic techniques. This project is the first to combine the notion of a data repository with real-time visual analytics for interactive data mining and exploratory analysis on the web. State-of-the-art statistical techniques are combined with real-time data visualization giving the ability for researchers to seamlessly find, explore, understand, and discover key insights in a large number of public donated data sets. This large comprehensive collection of data is useful for making significant research findings as well as benchmark data sets for a wide variety of applications and domains and includes relational, attributed, heterogeneous, streaming, spatial, and time series data as well as non-relational machine learning data. All data sets are easily downloaded into a standard consistent format. We also have built a multi-level interactive visual analytics engine that allows users to visualize and interactively explore the data in a free-flowing manner.
The figshare service for The Open University was launched in 2016 and allows researchers to store, share and publish research data. It helps the research data to be accessible by storing metadata alongside datasets. Additionally, every uploaded item receives a Digital Object Identifier (DOI), which allows the data to be citable and sustainable. If there are any ethical or copyright concerns about publishing a certain dataset, it is possible to publish the metadata associated with the dataset to help discoverability while sharing the data itself via a private channel through manual approval.
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GESIS preserves (mainly quantitative) social research data to make it available to the scientific research community. The data is described in a standardized way, secured for the long term, provided with a permanent identifier (DOI), and can be easily found and reused through browser-optimized catalogs (https://search.gesis.org/).
CPES provides access to information that relates to mental disorders among the general population. Its primary goal is to collect data about the prevalence of mental disorders and their treatments in adult populations in the United States. It also allows for research related to cultural and ethnic influences on mental health. CPES combines the data collected in three different nationally representative surveys (National Comorbidity Survey Replication, National Survey of American Life, National Latino and Asian American Study).
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Sikt archives research data on people and society to make sure the data can be shared and is made available for reuse. We continuously enrich our data collections to provide a richer basis for research. Sikt’s main focus is quantitative data matrices on individuals, organisations, administrative, political, and geographical actors. The archive specialise in survey data, which undergoes extensive curation at the variable level and detailed metadata is produced and published in Norwegian and English.
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As Germany’s first disciplinary repository in the field of international and interdisciplinary legal scholarship <intR>²Dok offers to all academic scholars currently affiliated with a university, college or research institute the opportunity to self-archive their quality-assured research data, research papers, pre-prints and previously published articles by means of open access. The disciplinary repository <intR>²Dok is a service offer provided by the Scientific Information Service for International and Interdisciplinary Legal Research (Fachinformationsdienst für internationale und interdisziplinäre Rechtsforschung) established at Berlin State Library (Staatsbibliothek zu Berlin) and funded by the German Research Foundation (Deutsche Forschungsgemeinschaft).
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The purpose of the Social Data Repository (RDS) is to make available in the Internet social data, consisting of data sets and accompanying technical or methodological documentation. The use of Repository is open for everyone. The repository is operated by the University of Warsaw (Interdisciplinary Centre for Mathematical and Computational Modelling, University of Warsaw). Individual collections in the Social Data Repository are subject to editorial review by University of Warsaw or collection administrators, under separate rules for a given collection. In particular, the supervising editor for the collection “Archive of Quantitative Social Data” is the Team of the Archive of Quantitative Social Data.
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<<<!!!<<< The digital archive of the Historical Data Center Saxony-Anhalt was transferred to the share-it repositor https://www.re3data.org/repository/r3d100013014 >>>!!!>>> The Historical Data Centre Saxony-Anhalt was founded in 2008. Its main tasks are the computer-aided provision, processing and evaluation of historical research data, the development of theoretically consolidated normative data and vocabularies as well as the further development of methods in the context of digital humanities, research data management and quality assurance. The "Historical Data Centre Saxony-Anhalt" sees itself as a central institution for the data service of historical data in the federal state of Saxony-Anhalt and is thus part of a nationally and internationally linked infrastructure for long-term data storage and use. The Centre primarily acquires individual-specific microdata for the analysis of life courses, employment biographies and biographies (primarily quantitative, but also qualitative data), which offer a broad interdisciplinary and international analytical framework and meet clearly defined methodological and technical requirements. The studies are processed, archived and - in compliance with data protection and copyright conditions - made available to the scientifically interested public in accordance with internationally recognized standards. The degree of preparation depends on the type and quality of the study and on demand. Reference studies and studies in high demand are comprehensively documented - often in cooperation with primary researchers or experts - and summarized in data collections. The Historical Data Centre supports researchers in meeting the high demands of research data management. This includes the advisory support of the entire life cycle of data, starting with data production, documentation, analysis, evaluation, publication, long-term archiving and finally the subsequent use of data. In cooperation with other infrastructure facilities of the state of Saxony-Anhalt as well as national and international, interdisciplinary data repositories, the Data Centre provides tools and infrastructures for the publication and long-term archiving of research data. Together with the University and State Library of Saxony-Anhalt, the Data Centre operates its own data repository as well as special workstations for the digitisation and analysis of data. The Historical Data Centre aims to be a contact point for very different users of historical sources. We collect data relating to historical persons, events and historical territorial units.
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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, Krems, Linz, Innsbruck and the Austrian Academy of Sciences and works within a network of national and international partners.