Who can participate in Open Science and whose interests are served? Open Science in principle holds the potential to reduce inequality, but this is not going to happen unless it operates within a consistent framework and environment that supports this goal. 

Five Observed Misapplications.

Article: Towards Globally Unique Identification of Physical Samples: Governance and Technical Implementation of the IGSN Global Sample Number

Problems with effective research data sharing persist and these problems have been quantified by previous research as a lack of time, resources, incentives, and/or skills to share data.

This paper presents the application profile for machine-actionable data management plans that allows information from traditional data management plans to be expressed in a machine-actionable way.

A Scoping Review and Case Study

The management of research data has become an essential aspect of good scientific practice. Education in research data management is, however, scarce.

In this paper we discuss interdisciplinarity through data as a way to create research environments that are more flexible and, as a result, more amenable to change. We report our findings from facilitating and evaluating a data-oriented early-career fellowship program that was administered as part of the Research Data Alliance (RDA), a global organization that aims to enable open sharing and re-use of data. 

Article: A Review of Open Research Data Policies and Practices in China

Investments in research that produce scientific and scholarly data can be leveraged by enabling the resulting research data products and services to be used by broader communities and for new purposes.

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. 

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. 

This article discusses how data citation has evolved over the last couple of decades and highlights issues that need more research and attention.

Article: Teaching Research Data Management for Students