Rec. 31: Support data citation and next generation metrics

[sjDCC]

Systems providing citation metrics for FAIR Data Objects and other research outputs should be provided. In parallel, next generation metrics that reinforce and enrich citation-centric metrics for evaluation should be developed.

• Citation of data and other research outputs needs to be encouraged and supported, for example by including sections in publishing templates that prompt researchers to reference materials, and providing citation guidelines when data, code or other outputs are accessed. Stakeholders: Publishers; Data services; Institutions.

• The Joint Data Citation Principles should be actively endorsed and implemented in the scholarly literature for attribution and in research assessment frameworks for recognition and career advancement. Stakeholders: Publishers, Institutions, Funders.

• A broader range of metrics should be developed to recognise contributions beyond publications and citation. These should recognise and reward Open and FAIR data practices. Stakeholders: Funders; Publishers; Institutions.

[holubp]

BBMRI-ERIC Position: This should be extended beyond just data - to other research resources such as software and physical specimen (biological material in life sciences and medicine).

[katerbow]

DFG position: Comments made to Recommendation 29 are also valid to Recommendation 31. Citation metrics of any kind and for FAIR-data objectives as well are not fail-safe and prone to lead to wrong and misleading results and interpretations. The question, whether “next generation metrics” are helping to ease this effect has to be answered. The endorsement of the “Joint Declaration of Data Citation Principles” sounds also rather simple and it is already signed by many individuals, organisations and other stakeholders (mainly between the years 2014 and 2015). But it did not show much effect so far and it can be assumed that after signing such a declaration the initial intention and the spirit of the declaration does not sustain a long period of time. That recommendation should also be reconsidered or possibly deleted.

[Eefkesmit]

Contribution on behalf of the International Association of STM Publishers (STM): As mentioned under several related recommendations, we see 4 cornerstone components in a machine-actionable eco system for FAIR Data. Of these the folllowing is relevant for FAIR Data Metrics: Data Citation standards -- Promote and implement data citation rules and standards according to the recommendations of FORCE11, to provide credit for good data practice.

STM and STM Publishers offer to collaborate with the other relevant stakeholders on this.

[Drosophilic]

I'm not sure this falls within a FAIR Data management plan. There are a number of groups already devising metrics based on the FAIR principles to allow stakeholders to judge the 'FAIRness' of a dataset or digital object (e.g. fairmetrics.org). I would suggest this recommendation be re-written to take those into account, rather than to provide other metrics (unless I've misunderstood the ticket)

[pkdoorn]

Combine with Rec. #14: Recognise and reward FAIR data and data stewardship #14.

[gtoneill]

The next generation metrics proposed by the EC Expert Groups on Altmetrics and Next Generation Metrics should be further developed with all major stakeholders. Some overlap again with Recommendations 5, 6, 9, 10, 11, 14, and 29 related to FAIR Data assessment. Perhaps merge?