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CLARIN is a European Research Infrastructure for the Humanities and Social Sciences, focusing on language resources (data and tools). It is being implemented and constantly improved at leading institutions in a large and growing number of European countries, aiming at improving Europe's multi-linguality competence. CLARIN provides several services, such as access to language data and tools to analyze data, and offers to deposit research data, as well as direct access to knowledge about relevant topics in relation to (research on and with) language resources. The main tool is the 'Virtual Language Observatory' providing metadata and access to the different national CLARIN centers and their data.
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.
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The vocabulary of forenames is a simple, multilingual vocabulary (i.e. without hierarchies etc.) in which the forenames of the project partners’ persons and the forenames’ spelling variants, both historical and dialectal, are documented with references or passages. As a rule, each forename is assigned one or more persons bearing that name. There is a hit list of the most frequent forenames between 200 BC and AD 2016 as well as a visualisation in word clouds and the occurrences in a timeline.
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.