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Found 185 result(s)
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.
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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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sciencedata.dk is a research data store provided by DTU, the Danish Technical University, specifically aimed at researchers and scientists at Danish academic institutions. The service is intended for working with and sharing active research data as well as for safekeeping of large datasets. The data can be accessed and manipulated via a web interface, synchronization clients, file transfer clients or the command line. The service is built on and with open-source software from the ground up: FreeBSD, ZFS, Apache, PHP, ownCloud/Nextcloud. DTU is actively engaged in community efforts on developing research-specific functionality for data stores. Our servers are attached directly to the 10-Gigabit backbone of "Forskningsnettet" (the National Research and Education Network of Denmark) - implying that up and download speed from Danish academic institutions is in principle comparable to those of an external USB hard drive. Data store for research data allowing private sharing and sharing via links / persistent URLs.
The Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) Data and Specimen Hub (DASH) is a centralized resource that allows researchers to share and access de-identified data from studies funded by NICHD. DASH also serves as a portal for requesting biospecimens from selected DASH studies.
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This data archive of experiments studying the dynamics of pedestrians is build up by the Institute for Advanced Simulation 7: Civil Safety Research of Forschungszentrum Jülich. The landing page provides our own data of experiments. Data of research colleagues are listed within the data archive at https://ped.fz-juelich.de/extda For most of the experiments, the video recordings, as well as the resulting trajectories of single pedestrians, are available. The experiments were performed under laboratory conditions to focus on the influence of a single variable. You are very welcome to use our data for further research, as long as you name the source of the data. If you have further questions feel free to contact Maik Boltes.
DataON is Korea's National Research Data Platform. It provides integrated search of metadata for KISTI's research data and domestic and international research data and links to raw data. DataON allows users (researchers, policy makers, etc.) to perform the following tasks: Easily search for various types of research data in all scientific fields. By registering research results, research data can be posted and cited. Build a community among researchers and enable collaborative research. It provides a data analysis environment that allows one-stop analysis of discovered research data.
IBICT is providing a research data repository that takes care of long-term preservation and archiving of good practices, so that researchers can share, maintain control and get recognition for your data. The repository supports research data sharing with Quote persistent data, allowing them to be played. The Dataverse is a large open data repository of all disciplines, created by the Institute for Quantitative Social Science at Harvard University. IBICT the Dataverse repository provides a means available for free to deposit and find specific data sets stored by employees of the institutions participating in the Cariniana network.
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.
diversitydata.org is an online tool for exploring quality of life data across metropolitan areas for people of different racial/ethnic groups in the United States. It provides values and rankings for the largest U.S. metropolitan areas on different indicators in 8 areas of life (domains), including demographics, education, economic opportunity, housing, neighborhoods, and health. It also provides a simple mapping utility, showing the range of indicator values for metros across the U.S. Data from 1999 indicators is archives in the companion Diversity Data Archive (https://diversitydata-archive.org/). For a wider selection of data on child wellbeing, visit our partner site, diversitydatakids.org (https://www.diversitydatakids.org/). diversitydata.org has been named a Health Data All Star by the Health Data Consortium. The list was compiled in consultation with leading health researchers, government officials, entrepreneurs, advocates and others to identify the health data resources that matter most.
The European Prospective Investigation into Cancer and Nutrition (EPIC) study is one of the largest cohort studies in the world, with more than half a million (521 000) participants recruited across 10 European countries and followed for almost 15 years. EPIC was designed to investigate the relationships between diet, nutritional status, lifestyle and environmental factors, and the incidence of cancer and other chronic diseases. EPIC investigators are active in all fields of epidemiology, and important contributions have been made in nutritional epidemiology using biomarker analysis and questionnaire information, as well as genetic and lifestyle investigations.
The Constituency-Level Elections Archive (CLEA) is a repository of detailed election results at the constituency level for lower house legislative elections from around the world. Our motivation is to preserve and consolidate these valuable data in one comprehensive and reliable resource that is ready for analysis and publicly available at no cost. This public good is expected to be of use to a range of audiences for research, education, and policy-making.
The Cape Peninsula University of Technology uses Figshare for institutions for their data repository and it is called eSango. The repository's Designated community are academics at the university who produce outputs for funded research. It fits with the University's ambition to increase the visibility, reach, and impact of its research. The Designated Community consists of researchers from all the discipline areas researched at CPUT Figshare (as evidenced by https://cput.figshare.com)
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The objective of the PDRC is to construct and collect a well-designed and large-scale panel data set and provide rigorous empirical studies based on these data sets. The data will enable us (i) to provide international comparisons and fact-findings on the household income changes, social mobility, changes in employment status and the investment activities; (ii) to verify the hypotheses related to the dynamics of economic behavior derived from economic theory; and (iii) to evaluate important policy changes in the tax system and social security program, which might have lagged effects.
Pandora is an open data platform devoted to the study of the human story. Data may be deposited from various disciplines and research topics that investigate humans from their early beginnings until present in addition to their environmental context (e.g. archeology, anthropology history, ancient DNA, isotopes, zooarchaeology, archaeobotany, and paleoenvironmental and paleoclimatic studies, etc.). Pandora allows autonomous data communities to self-manage their webspace and community membership. Data communities self-curate their data plus other supporting resources. Datasets may be assigned a new DOI and a schema markup is employed to improve data findability. Pandora also allows for links to datasets stored externally and having previously assigned DOIs. Through this, it becomes possible to establish data networks devoted to specific topics that may combine a mix of datasets stored either within Pandora or externally.
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PubData is Leuphana's institu­tional research data reposi­tory for the long-term preser­vation, documen­tation and publi­cation of research data from scienti­fic projects. PubData is main­tained by Leuphana's Media and Infor­mation Centre (MIZ) and is free of charge. The service is primarily aimed at Leuphana em­ployees and additionally at re­searchers from coope­ration partners con­tractually asso­ciated with Leuphana.
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The Research Data Center of the Federal Institute for Occupational Safety and Health (FDZ-BAuA) provides selected data from BAuA research. The Public Use Files can be used by scientists as well as by the interested public.
Discovery is the digital repository of research, and related activities, undertaken at the University of Dundee. The content held in Discovery is varied and ranges from traditional research outputs such as peer-reviewed articles and conference papers, books, chapters and post-graduate research theses and data to records for artefacts, exhibitions, multimedia and software. Where possible Discovery provides full-text access to a version of the research. Discovery is the data catalogue for datasets resulting from research undertaken at the University of Dundee and in some instances the publisher of research data.
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The Research Data Repository of FID move is a digital long-term repository for open data from the field of transport and mobility research. All datasets are provided with an open licence and are assigned a persistent DataCite DOI (Digital Object Identifier). Both data search and archiving are free. The Specialised Information Service for Mobility and Transport Research (FID move) has been set up by the Saxon State and University Library Dresden (SLUB) and the German TIB – Leibniz Information Centre for Science and Technology as part of the DFG funding programme "Specialised Information Services".
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The Research Data Centre (FDZ-RV) was set-up in 2004 as an integral part of the German Federal Pension Insurance (Deutsche Rentenversicherung). Since then, the Research Data Centre produced several cross-sectional and longitudinal datasets, also called Scientific Use Files (SUF), available to researchers interested in issues of retirement, disability and rehabilitation. The datasets are released on an annual basis. The Scientific Use Files are subsamples drawn from the pool of individuals who are insured in the Federal Pension Insurance. The information provided in the original datasets is necessary to administer the beneficiaries of the pension insurance.
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PsychArchives is a disciplinary repository for psychological science and neighboring disciplines. Accommodating 20 different digital research object (DRO) types, including articles, preprints, research data, code, supplements, preregistrations, tests and multimedia objects, PsychArchives provides a digital space that integrates all research-related content relevant to psychology. PsychArchives is committed to the FAIR principles, facilitating the findability, accessibility, interoperability and reusability of research and research data.
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TUL Open Research Data Repository (RDB.open) is a service addressed to the scientific and research community of the Lodz University of Technology. The main purpose of RDB.open is to collect, share and store the open research data, both during the research and after its completion, at least for the minimum period indicated by the funder or the scientists. The RDB.open is a place where research data can be openly shared, accessed and then reused by others.