Appraisal and selection are key activities necessary for the responsible stewardship of research data. Not all data has long-term research value, and the increasing volume of data produced and published to meet short- and mid-term needs creates a burden on both the repositories storing and maintaining access to the resources and the researchers searching for quality data. Repository appraisal practices, often carried out as part of the curation process at the time of deposit to optimize data for sharing and reuse, need to better address the long-term sustainability of FAIR data practices. This guide is designed to be used alongside a repository’s existing acquisition, collection development, preservation, and deaccessioning policies and other high-level institutional strategy documents to help curators work with researchers and preservation specialists to evaluate research data for long-term preservation.
A guide to principles and methods for the management, archiving, sharing, and citing of linguistic research data, especially digital data. “Doing language scien
This guide provides step-by-step instructions for curating new datasets deposited in Dataverse. The guide is framed around the acronym CURATION to provide an easy reminder for curators, especially those starting out, of the main steps in the curation process. This framework is adapted from the Data Curation Network’s CURATED steps for use in a bilingual context.
There are videos and case studies associated with the book.
Focused on both primary and secondary data and packed with checklists and templates, it contains everything readers need to know for managing all types of data before, during and after the research process.
-Exigences minimales pour les plans de gestion des données
-Critères de sélection des dépôts dignes de confiance
-Conseils aux examinateurs pour évaluer des DMP
online tool which helps researchers and data managers assess how much they know about the requirements for making datasets findable, accessible, interoperable, and reusable (FAIR) before uploading them into a data repository.