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Found 72 result(s)
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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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Dataverse for faculty, researchers, and students at St. Francis Xavier University or affiliated institutions. Hosted by Borealis.
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VinaR is the digital repository of the VinÄŤa Institute of Nuclear Sciences, University of Belgrade. VinaR provides open access to the publications, as well as to other outputs of the research projects implemented in these institutions. The software platform meets the current requirements that apply to the dissemination of scholarly publications and it is compatible with relevant international infrastructures.
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DUnAs is the institutional research data repository of the University of Aveiro. This repository is intended to share, archive, preserve, cite, access, and explore research data produced in the university scientific research activities.
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Veterinar – Electronic Repository of Research and Scientific Papers is the institutional digital repository of the University of Belgrade - Faculty of Veterinary Medicine. It provides open access to publications and other research outputs resulting from the projects implemented by the Faculty of Veterinary Medicine. The software platform of the repository is adapted to the modern standards applied in the dissemination of scientific publications and is compatible with international infrastructure in this field.
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BExIS is the online data repository and information system of the Biodiversity Exploratories Project (BE). The BE is a German network of biodiversity related working groups from areas such as vegetation and soil science, zoology and forestry. Up to three years after data acquisition, the data use is restricted to members of the BE. Thereafter, the data is usually public available (https://www.bexis.uni-jena.de/ddm/publicsearch/index).
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.
The Magnetics Information Consortium (MagIC) improves research capacity in the Earth and Ocean sciences by maintaining an open community digital data archive for rock magnetic, geomagnetic, archeomagnetic (archaeomagnetic) and paleomagnetic (palaeomagnetic) data. Different parts of the website allow users access to archive, search, visualize, and download these data. MagIC supports the international rock magnetism, geomagnetism, archeomagnetism (archaeomagnetism), and paleomagnetism (palaeomagnetism) research and endeavors to bring data out of private archives, making them accessible to all and (re-)useable for new, creative, collaborative scientific and educational activities. The data in MagIC is used for many types of studies including tectonic plate reconstructions, geomagnetic field models, paleomagnetic field reversal studies, magnetohydrodynamical studies of the Earth's core, magnetostratigraphy, and archeology. MagIC is a domain-specific data repository and directed by PIs who are both producers and consumers of rock, geo, and paleomagnetic data. Funded by NSF since 2003, MagIC forms a major part of https://earthref.org which integrates four independent cyber-initiatives rooted in various parts of the Earth, Ocean and Life sciences and education.
The figshare service for the University of Sheffield 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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The arctic data archive system (ADS) collects observation data and modeling products obtained by various Japanese research projects and gives researchers to access the results. By centrally managing a wide variety of Arctic observation data, we promote the use of data across multiple disciplines. Researchers use these integrated databases to clarify the mechanisms of environmental change in the atmosphere, ocean, land-surface and cryosphere. That ADS will be provide an opportunity of collaboration between modelers and field scientists, can be expected.
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.
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The University of Northern British Columbia Dataverse is a research data repository for research data from UNBC researchers. Files are held in a secure environment on Canadian servers. The platform makes it possible for researchers to deposit data, create appropriate metadata, and version documents as they work. Researchers can choose to make content available publicly, to specific individuals, or to keep it locked.
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The institutional research data repository of the Universität Innsbruck is a service to enable storing, sharing and publishing of research data according to the FAIR principles for its employees and project partners.
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The SMU Dataverse is a research data repository for our faculty, students, and staff. Files are held in a secure environment on Canadian servers. Researchers can choose to make content available publicly, to specific individuals, or to keep it locked.
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UWinnipeg Research Data Repository accepts research data and datasets that have been created by researchers and research groups at the University of Winnipeg. Files are held in a secure environment on Canadian servers. The UWinnipeg Data Repository accepts finalized datasets that are ready for publication and sharing.
The WashU Research Data repository accepts any publishable research data set, including textual, tabular, geospatial, imagery, computer code, or 3D data files, from researchers affiliated with Washington University in St. Louis. Datasets include metadata and are curated and assigned a DOI to align with FAIR data principles.
The Polinsky Language Sciences Lab at Harvard University is a linguistics lab that examines questions of language structure and its effect on the ways in which people use and process language in real time. We engage in linguistic and interdisciplinary research projects ourselves; offer linguistic research capabilities for undergraduate and graduate students, faculty, and visitors; and build relationships with the linguistic communities in which we do our research. We are interested in a broad range of issues pertaining to syntax, interfaces, and cross-linguistic variation. We place a particular emphasis on novel experimental evidence that facilitates the construction of linguistic theory. We have a strong cross-linguistic focus, drawing upon English, Russian, Chinese, Korean, Mayan languages, Basque, Austronesian languages, languages of the Caucasus, and others. We believe that challenging existing theories with data from as broad a range of languages as possible is a crucial component of the successful development of linguistic theory. We investigate both fluent speakers and heritage speakers—those who grew up hearing or speaking a particular language but who are now more fluent in a different, societally dominant language. Heritage languages, a novel field of linguistic inquiry, are important because they provide new insights into processes of linguistic development and attrition in general, thus increasing our understanding of the human capacity to maintain and acquire language. Understanding language use and processing in real time and how children acquire language helps us improve language study and pedagogy, which in turn improves communication across the globe. Although our lab does not specialize in language acquisition, we have conducted some studies of acquisition of lesser-studied languages and heritage languages, with the purpose of comparing heritage speakers to adults.
The range of CIRAD's research has given rise to numerous datasets and databases associating various types of data: primary (collected), secondary (analysed, aggregated, used for scientific articles, etc), qualitative and quantitative. These "collections" of research data are used for comparisons, to study processes and analyse change. They include: genetics and genomics data, data generated by trials and measurements (using laboratory instruments), data generated by modelling (interpolations, predictive models), long-term observation data (remote sensing, observatories, etc), data from surveys, cohorts, interviews with players.
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Research Data Unipd is a data archive and supports research produced by the members of the University of Padova. The service aims to facilitate data discovery, data sharing, and reuse, as required by funding institutions (eg. European Commission). Datasets published in the archive have a set of metadata that ensure proper description and discoverability.
The ASEP Data Repository is an institutional multidisciplinary on-line repository that stores scientific outputs - bibliographic records, full texts and datasets of the institutional authors from The Czech Academy of Sciences. The repository is hosted by Library of the Czech Academy of Sciences. Data that are stored in database are accessible in the on-line catalogue. Each dataset has its own description and metadata according to international standards.