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Found 23 result(s)
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The Concordia University Dataverse is a research data repository for Concordia faculty, students, and staff. Files are held in a secure environment on Canadian servers.
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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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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Fordatis is the institutional research data repository of the Fraunhofer-Gesellschaft. Fraunhofer-Gesellschaft based in Germany is Europes largest research and technology organization. Fordatis contains research data created by researcher at Fraunhofer. These are data from the engineering, natural sciences and social sciences.
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PRISM Dataverse is the institutional data repository of the University of Calgary, which has its purpose in digital archiving and sharing of research data from researchers. PRISM Dataverse is a data repository hosted through Borealis, a service of the Ontario Council of University Libraries and supported by University of Calgary's Libraries and Cultural Resources. PRISM Dataverse enables scholars to easily deposit data, create data-specific metadata for searchability and publish their datasets.
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The Repositori Ilmiah Nasional (RIN) is a means for storing, preserving, citing, analyzing and sharing research data. RIN acts as an online media in managing, storing and sharing research data. Researchers, data writers, publishers, data distributors, and affiliated institutions all receive academic credit and web visibility. Researchers, agencies, and funders have full control over research data.
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
University of Alberta Dataverse is a service provided by the University of Albert Library to help researchers publish, analyze, distribute, and preserve data and datasets. Open for University of Alberta-affiliated researchers to deposit data.
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DataverseNO (https://dataverse.no) is a curated, FAIR-aligned national generic repository for open research data from all academic disciplines. DataverseNO commits to facilitate that published data remain accessible and (re)usable in a long-term perspective. The repository is owned and operated by UiT The Arctic University of Norway. DataverseNO accepts submissions from researchers primarily from Norwegian research institutions. Datasets in DataverseNO are grouped into institutional collections as well as special collections. The technical infrastructure of the repository is based on the open source application Dataverse (https://dataverse.org), which is developed by an international developer and user community led by Harvard University.
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.
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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.
Arca Data is Fiocruz's official repository for archiving, publishing, disseminating, preserving and sharing digital research data produced by the Fiocruz community or in partnership with other research institutes or bodies, with the aim of promoting new research, ensuring the reproducibility or replicability of existing research and promoting an Open and Citizen Science. Its objective is to stimulate the wide circulation of scientific knowledge, strengthening the institutional commitment to Open Science and free access to health information, in addition to providing transparency and fostering collaboration between researchers, educators, academics, managers and graduate students, to the advancement of knowledge and the creation of solutions that meet the demands of society.
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RODBUK Cracow Open Research Data Repository is co-created by six Cracow universities: AGH University of Science and Technology, University of Physical Education in Krakow, Cracow University of Technology, Krakow University of Economics, Jagiellonian University in Kraków, Pedagogical University of Krakow. The purpose of RODBUK is to collect, develop, archive and make available in open access all types of research data created by researchers, PhD candidates and students in the course of scientific activity. RODBUK aims to implement the Open Science policy by creating a publicly available platform for depositing research datasets enabling: getting acquainted with the research conducted in Cracow's scientific centers, storage of various types of research data obtaining a permanent Digital Object Identifier (DOI) for each dataset, standardized data citation, choosing a data usage license agreement (Creative Commons or other. RODBUK allows to collect and share open research data from various disciplines and in all file formats. RODBUK applies the FAIR Principles, which means the data is findable, accessible, interoperable, reusable.
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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.
The Tromsø Repository of Language and Linguistics (TROLLing) is a FAIR-aligned repository of linguistic data and statistical code. The archive is open access, which means that all information is available to everyone. All data are accompanied by searchable metadata that identify the researchers, the languages and linguistic phenomena involved, the statistical methods applied, and scholarly publications based on the data (where relevant). Linguists worldwide are invited to deposit data and statistical code used in their linguistic research. TROLLing is a special collection within DataverseNO (http://doi.org/10.17616/R3TV17), and C Centre within CLARIN (Common Language Resources and Technology Infrastructure, a networked federation of European data repositories; http://www.clarin.eu/), and harvested by their Virtual Language Observatory (VLO; https://vlo.clarin.eu/).
Online storage, sharing and registration of research data, during the research period and after its completion. DataverseNL is a shared service provided by participating institutions and DANS.
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The USACH research data repository provides a platform for researchers affiliated to the University to share, manage and preserve research data. So that they are accessible and detectable, both for the internal and external community, bringing the knowledge generated closer to the population.
e-cienciaDatos is a multidisciplinary data repository that houses the scientific datasets of researchers from the public universities of the Community of Madrid and the UNED, members of the Consorcio Madroño, in order to give visibility to these data, to ensure its preservation And facilitate their access and reuse. e-cienciaDatos is structured as a system constituted by different communities that collects datasets of each of the individual universities. e-cienciaDatos offers the deposit and publication of datasets, assigning a digital object identifier DOI to each of them. The association of a dataset with a DOI will facilitate data verification, dissemination, reuse, impact and long-term access. In addition, the repository provides a standardized citation for each dataset, which contains sufficient information so that it can be identified and located, including the DOI.