Analysis of online survey on incentives for FAIR and open data practices

To better understand the current attitudes and practices surrounding FAIR and open data practices, an online survey was conducted, targeting researchers in the German Earth System Sciences community. 114 completed answers were considered in the analysis of the online survey.

Current engagement in FAIR and open data practices

"Citing data, software, and samples in your publications” is the most often exercised FAIR and open data practice, consistent with the fact that citation of journal articles or books is deeply embedded in research practice since decades as part of good scientific practice. Inclusion of a data availability statements (DAS) in journal publications is the second most often exercised practice, pointing to the effectiveness of obligations in journal submission policies. “Preparing, using and updating data management plans” is the least exercised practice, although using data management plans (DMPs) are increasingly expected or mandatory demanded by research funding organisations. About half of the participants of the online survey are engaged in teaching and training activities on FAIR and open data practices. PhD students are very rarely, and professors are very often engaged in such activities.

Motivators to perform FAIR and open data practices, drivers and barriers for data sharing

Better institutional support for FAIR and open data practices as well as more scientific recognition via dataset citation metrics are the strongest motivators to perform FAIR and open data practices more often. Only few participants think that awards for these practices are strong motivators. The most important drivers for data publication are the perception that it improves science as a whole. This is contrasted by extrinsic drivers, such as requirements from publishers, funders, institutions, and data sharing norms, ranking lower. The most important reason for not sharing data is the consideration that the data are not suitable for sharing. Fear that somebody else may publish earlier than the data originator on the data is another important reason for not sharing data.

Conclusions and implications for NFDI4Earth

NFDI4Earth should strengthen motivators for FAIR & open data practices in general and, in particular, for data publication, that are of high importance of survey participants.

Barriers to data sharing of high importance to survey participants may be assessed in order to identify targeted future actions to phase out disincentivising environments and structures.

NFDI4Earth might form strategic partnerships with partners like academic societies or the FID GEO for joint projects to improve the adoption of FAIR and open data practice.

NFDI4Earth may concentrate on training and education on data sharing and the use of DMPs as well as working together with NFDI4Earth member institutions and other partners to promote the introduction of data sharing policies and to strengthen existing ones.

NFDI4Earth member institutions should take advantage of NFDI4Earth-developed instruments, e. g. the Help Desk, in providing better assistance and infrastructure to its researchers.

Development of data citation metrics and the recognition of FAIR and open data practices should be supported by NFDI4Earth to drive the much-needed cultural change.

Colleagues as role models are important: NFDI4Earth member institutions should develop programs that make researchers that engage in FAIR and open data practice more visible.