This profile series seeks to support libraries that may consider unbundling from a journal package (or cancelling altogether) by sharing the increasing depth of experience that institutions have in pursuing this path.
Loren Frank’s HHMI lab at UCSF has pioneered an ambitious framework for sharing vast neuroscience datasets and complicated analysis methods, a step towards
Indigenous groups are developing data storage technology that gives users privacy and control. Could their work influence those fighting back against invasive apps?
Terrastories is a geostorytelling application built to enable indigenous and other local communities to locate and map their oral storytelling traditions.
Cette bande dessinée didactique a été produite par le Service commun de la Documentation de l'Université de Guyane. Elle s'adresse à un public de doctorants et de chercheurs dans un objectif d'accompagnement à ces nouvelles pratiques scientifiques.
Welcome to the Qualitative Data Sharing (QDS) Toolkit We believe in the benefits of data transparency. We created this toolkit to support qualitative data sharing in an ethical manner.
These cartoons were created for us as advocacy materials for the University of Cambridge Data Champions Programme. They were created by Clare Trowell and are being shared under a CC-BY-NC-ND licence. If you reuse these images please credit Clare Trowell appropriately.
the University of Sheffield Library worked with researchers in seven disciplines to develop subject-specific FAIR checklists for the use of colleagues before, during and at the end of their research project.
AthabascaU's Library and Faculty of Graduate Studies just collaborated to develop an openly available, introductory RDM course. It is intended as a professional development micro-credential for graduate students, but the content is a useful introduction to RDM for any audience looking to get started.
NIH has provided sample DMS Plans as examples of how a DMS Plan could be completed in different contexts, conforming to the elements described above. These sample DMS Plans are provided for educational purposes to assist applicants with developing Plans but are not intended to be used as templates and their use does not guarantee approval by NIH.
This is a minimal introduction to data management handling data in R compiled for the Biological Sciences BSc(Honours) class at the University of Cape Town.
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.
The data-sharing policy could set a global standard for biomedical research, scientists say, but they have questions about logistics and equity. The data-sharing policy could set a global standard for biomedical research, scientists say, but they have questions about logistics and equity.
This handbook aims to support higher education institutions with the integration of FAIR-related content in their curricula and teaching. It was written and edited by a group of about 40 collaborators in a series of six book sprint events that took place between 1 and 10 June 2021. The document provides practical material, such as competence profiles, learning outcomes and lesson plans, and supporting information. It incorporates community feedback received during the public consultation which ran from 27 July to 12 September 2021.
A guide to principles and methods for the management, archiving, sharing, and citing of linguistic research data, especially digital data. “Doing language scien
The RDM Maturity Assessment Model in Canada (MAMIC) is based on the RISE and SPARC assessment models and has been adapted to fit the Canadian institutional context. This tool is designed to help evaluate the current state of institutional RDM services and supports as part of an institutional RDM strategy development process. It focuses on four areas of service and support - Institutional Policies and Processes, IT Infrastructure, Support Services, and Financial Support - and allows users to assess the maturity and scale of these services.
This template is intended to assist research institutions in developing an institutional research data management (RDM) strategy, both to fulfil the first requirement of the Tri-Agency Research Data Management Policy and to articulate their commitment to RDM at the institutional level. It consists of suggested activities and processes in five stages to inform and shape the creation of an RDM strategy that meets local needs and resource capacities. Crucially, it is intended as a process, rather than a product template -- it provides steps for how to develop an institutional strategy, not a template outlining what an institutional strategy document itself looks like. In fact, these processes should be seen as ongoing to inform strategy updates over time and to help align institutional RDM efforts with broader institutional goals, objectives, policies, and services. While it is recommended that institutions employ each of the strategy development activities included in this template, your institution may choose to engage in each activity at a level of depth and detail appropriate to its size, research intensity, and existing RDM capacity. The institutions which will be required to create RDM strategies are postsecondary institutions and research hospitals eligible to administer Tri-Agency funds. See both the Tri-Agency RDM Policy and Statement of Principles on Digital Data Management, which outline expectations and responsibilities for RDM in the academic community. For definitions of RDM terms in this document, please refer to the CASRAI Research Data Management Glossary.
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.