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Found 48 result(s)
Country
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.
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.
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.
Country
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.
From now on you no longer deposit archaeological data here in EASY . Please see: https://archaeology.datastations.nl/ EASY is the online archiving system of Data Archiving and Networked Services (DANS). EASY offers you access to thousands of datasets in the humanities, the social sciences and other disciplines. EASY can also be used for the online depositing of research data.
In order to meet the needs of research data management for Peking University. The PKU library cooperate with the NSFC-PKU data center for management science, PKU science and research department, PKU social sciences department to jointly launch the Peking University Open Research Data Platform. PKU Open research data provides preservation, management and distribution services for research data. It encourage data owner to share data and data users to reuse data.
Country
As a research data hub for social and economic history, Emporion enables the free and standards-compliant publication of time series, historical statistical and panel data, georeferenced vector data, text mining analyses and data papers. Emporion is also open to contributions from the fields of business and environmental history and the history of technology. Emporion's supporting institutions are the DFG Priority Programme 1859 'Experience and Expectations. Historical Foundations of Economic Behavior' and the Gesellschaft für Sozial- und Wirtschaftsgeschichte in conjunction with the Staatsbibliothek zu Berlin – Preußischer Kulturbesitz.
The Odum Institute Archive Dataverse contains social science data curated and archived by the Odum Institute Data Archive at the University of North Carolina at Chapel Hill. Some key collections include the primary holdings of the Louis Harris Data Center, the National Network of State Polls, and other Southern-focused public opinion data. Please note that some datasets in this collection are restricted to University of North Carolina at Chapel Hill affiliates. Access to these datasets require UNC ONYEN institutional login to the Dataverse system.
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Edmond is the institutional repository of the Max Planck Society for public research data. It enables Max Planck scientists to create citable scientific assets by describing, enriching, sharing, exposing, linking, publishing and archiving research data of all kinds. Further on, all objects within Edmond have a unique identifier and therefore can be clearly referenced in publications or reused in other contexts.
The Henry A. Murray Research Archive is Harvard's endowed, permanent repository for quantitative and qualitative research data at the Institute for Quantitative Social Science, and provides physical storage for the entire IQSS Dataverse Network. Our collection comprises over 100 terabytes of data, audio, and video. We preserve in perpetuity all types of data of interest to the research community, including numerical, video, audio, interview notes, and other data. We accept data deposits through this web site, which is powered by our Dataverse Network software
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The Research Data Center (RDC) “International Survey Programs“ provides researchers with data, services, and consultation on a number of important international study series which are under intensive curation by GESIS. They all cover numerous countries and, quite often, substantial time spans. The RDC provides optimal data preparation and access to a wide scope of data and topics for comparative analysis.
Country
The Slovenian Social Science Data Archives (Slovenski Arhiv Družboslovnih podatkov - ADP) were established in 1997 as an organizational unit within the Institute of Social Sciences at the Faculty of Social Sciences, University of Ljubljana. Its tasks are to acquire significant data sources within a wide range of social science disciplines of interest to Slovenian social scientists, review and prepare them for digital preservation, and to disseminate them for further scientific, educational and other purposes.
The Harvard Dataverse is open to all scientific data from all disciplines worldwide. It includes the world's largest collection of social science research data. It is hosting data for projects, archives, researchers, journals, organizations, and institutions.
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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 Society of American Archivists (SAA) Dataverse is an SAA data service that was established to support the needs and interests of SAA’s members and the broader archives community. The SAA Dataverse supports the reuse of datasets for purposes of fostering knowledge, insights, and a deeper understanding of archival organizations, the status of archivists, and the impact of archives and archival work on the broader society. Deposited datasets should be “actionable” in that they should support direct analysis and interpretation. The SAA Dataverse welcomes deposits of collections of quantitative or qualitative data and associated documentation. SAA membership is not required to deposit or use data in the SAA Dataverse.
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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.
The OpenNeuro project (formerly known as the OpenfMRI project) was established in 2010 to provide a resource for researchers interested in making their neuroimaging data openly available to the research community. It is managed by Russ Poldrack and Chris Gorgolewski of the Center for Reproducible Neuroscience at Stanford University. The project has been developed with funding from the National Science Foundation, National Institute of Drug Abuse, and the Laura and John Arnold Foundation.
Mulce (MUltimodal contextualized Learner Corpus Exchange) is a research project supported by the National Research Agency (ANR programme: "Corpus and Tools in the Humanities", ANR-06-CORP-006). A teaching corpus (LETEC - Learning and Teaching Corpora) combines a systematic and structured data set, particularly of interactional data, and traces left by a training course experimentation, conducted partially or completely online and completed by additional technical, human, pedagogical and scientific information to enable the data to be analysed in context.