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Found 15 result(s)

Dalhousie University Dataverse @ Borealis

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The Dalhousie University Dataverse is a research data repository for our faculty, students, and staff. Files are held in a secure environment on Canadian servers, hosted by Borealis.

LiDA

Lietuvos humanitarinių ir socialinių mokslų duomenų archyvas

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Lithuanian Data Archive for Social Sciences and Humanities (LiDA) is a virtual digital infrastructure for SSH data and research resources acquisition, long-term preservation and dissemination. All the data and research resources are documented in both English and Lithuanian according to international standards. Access to the resources is provided via Dataverse repository. LiDA curates different types of resources and they are published into catalogues according to the type: Survey Data, Aggregated Data (including Historical Statistics), Encoded Data (including News Media Studies), and Textual Data. Also, LiDA holds collections of social sciences and humanities data deposited by Lithuanian science and higher education institutions and Lithuanian state institutions (Data of Other Institutions). LiDA is hosted by the Centre for Data Analysis and Archiving of Kaunas University of Technology (data.ktu.edu).

DataSpace@HKUST

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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.

Wilfrid Laurier University Dataverse

WLU Dataverse

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The Wilfrid Laurier University Dataverse is a research data repository for our faculty, students, and staff. Files are held in a secure environment on Canadian servers.

The Polinsky Language Sciences Lab Dataverse

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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.

IBICT Cariniana Dataverse Network

Instituto Brasileiro de Informação em Ciência e Tecnologia Cariniana Dataverse Network

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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.

Western University Dataverse

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Western University's 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.

Repositório de Dados de Pesquisa Unifesp

Unifesp Data Repository

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The Unifesp Research Data Repository is a platform for storing, preserving and accessing research data for the institution's academic community.

GlobeData

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GlobeData is a repository for archiving and publishing research data at the Leipzig Research Centre Global Dynamics (ReCentGlobe). It is furthermore open to researchers worldwide in the interdisciplinary fields of global and area studies and will engage in systematic data collection.

University of Waterloo Dataverse

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The University of Waterloo Dataverse is a data repository for research outputs of our faculty, students, and staff. Files are held in a secure environment on Canadian servers. Researchers can choose to make content available to the public, to specific individuals, or to keep it private.

TROLLing

Tromsø Repository of Language and Linguistics

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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/).

York University Dataverse

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York University Libraries makes available Borealis for despositing data . Borealis is a an instance of Dataverse hosted by The Ontario Council of University Libraries, of which York University Libraries is a member.

The Abdul Latif Jameel Poverty Action Lab

J-PAL Dataverse

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Data from selected studies from the Abdul Latif Jameel Poverty Action Lab (J-PAL), povertyactionlab.org. A number of other studies from J-PAL have data posted on the MacArthur Dataverse: http://dvn.iq.harvard.edu/dvn/dv/macarthur.

University of Manitoba Dataverse

University of Manitoba Libraries Dataverse

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UM Dataverse is part of the Dataverse Project conceived of by Harvard University. It is an open source repository to assist researchers in the creation, management and dissemination of their research data. UM Dataverse allows for the creation of multiple collaborative environments containing datasets, metadata and digital objects. UM Dataverse provides formal scholarly data citations and can help with data requirements from publishers and funders.

University of Guelph Research Data Repositories

University of Guelph Dataverse

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The University of Guelph Research Data Repositories provide long-term stewardship of research data created at or in cooperation with the University of Guelph. The Data Repositories are guided by the FAIR Guiding Principles for scientific data management and stewardship which aim to improve the Findability, Accessibility, Interoperability and Reuse of research data. The Data Repositories is composed of two main collections: the Agri-environmental Research Data collection which houses agricultural and environmental research data, and the Cross-disciplinary Research Data collection which houses all other disciplinary research data.