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Found 16 result(s)
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bonndata is the institutional, FAIR-aligned and curated, cross-disciplinary research data repository for the publication of research data for all researchers at the University of Bonn. The repository is fully embedded into the University IT and Data Center and curated by the Research Data Service Center (https://www.forschungsdaten.uni-bonn.de/en). The software that bonndata is based on is the open source software Dataverse (https://dataverse.org)
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prometheus is a digital image archive for Art and Cultural Sciences. prometheus enables the convenient search for images on a common user interface within different image archives, variable databases from institutes, research facilities and museums.
The Old Bailey Proceedings Online makes available a fully searchable, digitised collection of all surviving editions of the Old Bailey Proceedings from 1674 to 1913, and of the Ordinary of Newgate's Accounts between 1676 and 1772. It allows access to over 197,000 trials and biographical details of approximately 2,500 men and women executed at Tyburn, free of charge for non-commercial use. In addition to the text, accessible through both keyword and structured searching, this website provides digital images of all 190,000 original pages of the Proceedings, 4,000 pages of Ordinary's Accounts, advice on methods of searching this resource, information on the historical and legal background to the Old Bailey court and its Proceedings, and descriptions of published and manuscript materials relating to the trials covered. Contemporary maps, and images have also been provided.
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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.
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.
LAUDATIO has developed an open access research data repository for historical corpora. For the access and (re-)use of historical corpora, the LAUDATIO repository uses a flexible and appropriate documentation schema with a subset of TEI customized by TEI ODD. The extensive metadata schema contains information about the preparation and checking methods applied to the data, tools, formats and annotation guidelines used in the project, as well as bibliographic metadata, and information on the research context (e.g. the research project). To provide complex and comprehensive search in the annotation data, the search and visualization tool ANNIS is integrated in the LAUDATIO-Repository.
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.
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.
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.
Apollo (previously DSpace@Cambridge) is the University of Cambridge’s Institutional Repository (IR), preserving and providing access to content created by members of the University. The repository stores a range of content and provides different levels of access, but its primary focus is on providing open access to the University’s research publications.
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.