From FAIR Leading Practices to FAIR Implementation and Back: An Inclusive Approach to FAIR at Leiden University Libraries
Paper describe how LU builds up its support for FAIR data before, during and after research through its involvement in leading practices, training and consultancy and end with recommendations for other universities wanting to implement the FAIR principles.
Great strides have been made to encourage researchers to archive data created by research and provide the necessary systems to support their storage. Additionally it is recognised that data are meaningless unless their provenance is preserved, through appropriate meta-data. Alongside this is a pressing need to ensure the quality and archiving of the software that generates data, through simulation, control of experiment or data-collection and that which analyses, modifies and draws value from raw data.
Data Sharing at Scale: A Heuristic for Affirming Data Cultures
Addressing the most pressing contemporary social, environmental, and technological challenges will require integrating insights and sharing data across disciplines, geographies, and cultures. Strengthening international data sharing networks will not only demand advancing technical, legal, and logistical infrastructure for publishing data in open, accessible formats; it will also require recognizing, respecting, and learning to work across diverse data cultures. This essay introduces a heuristic for pursuing richer characterizations of the “data cultures” at play in international, interdisciplinary data sharing.