PILOT

Team Science – author contributor data (CRediT)

Status: Pilot running

 

Participating Institutions

Vrije Universiteit (VU), AmsterdamUMC, Groningen University, Maastricht University, TU Eindhoven

 

The context for this pilot

The scientific careers of researchers have been getting more diverse in recent decades. Where previously a researcher was responsible for the entire research, she or he received all the credits as the author of her/his article. Nowadays, research has become more complex with many different (and new) skills needed in a scientific team to complete the research question using modern technology and standards.

• One of the key Open Science objectives of Dutch research is to re-define the reward and recognition of all actors in academia and promote Team Science. To properly Recognize & Reward one must capture contributions – in a consistent way – to ensure that all are fairly acknowledged, and team evaluations can be supported in a transparent way.
• A NISO standard classification scheme (CRediT) has been developed describing 14 specific roles in research projects. Publishers are in the process of implementing this classification scheme in their journals, capturing the specific roles of the various contributors of the submitted papers.

 

The aim of this pilot is to assess:

• if and how contributor data can enable the use cases around team science and contributor data.
• to what extent the Dutch published papers (from Elsevier proprietary journals initially) capture the defined roles of the various authors sufficiently (high % of authors having a contributor role defined).
• what set of (reporting) data is required that will enable research intelligence teams to provide insights/answers to the various use cases around team science and contributor data (see below).

 

The Deliverables for this pilot are:

• A white paper describing how contributor data can support Team Science use cases, and what the potential pitfalls might be.
• Analyses of Contributor data from NL affiliated author in Elsevier publications. Elsevier will provide analyses at national level and will provide the participating institutions with datasets for their specific authors, for further analyses by the institutions.
• An evaluation of the pilot and recommendations for the use of CRediT data in Team science use cases and for a possible follow up from this pilot.

 

Relevant Links

• Team Science-Statement of work
• Team Science-Framework document
• Pilot analysis of CRediT data: Exploring data coverage and role attribution patterns
• Want to learn more about how the underlying data was prepared, click here
• Vanderfeesten, M., Kool, L., & Verheggen, J. (2024). EPDOS – White paper – Team Science – author contributor data (CRediT) (1.0). EPDOS.NL. https://doi.org/10.5281/zenodo.10875891 (latest)

 

Annex: use cases:

• Individual level & new career paths: on the individual level researchers can show, over time, their development as a professional researcher. This could also enable new career paths, for example for researchers primarily involved in a software application to the published research. The data can also be used to create narratives for review processes and in CVs.
• Department level: on a department or group level, PI’s or department heads will be able to plot their team members according to their most prominent role(s) and analyze the gap between the desired and current team members. They could also do this on a larger scale in a strategic personnel planning process.
• At department and institution level, CRediT data might be used to determine the key relevant publications for institutional strategic planning and review purposes.
• Faculty level: for faculties it will be possible to form a strategic policy on local support. If certain roles are overrepresented or if certain tasks which could be centrally organized are lacking in the faculty analyses, these data could be used to make a business case to set up support tasks at a faculty level rather than per research group.
• Collaborative efforts: there will be a possibility for researchers or project leaders to analyze the distribution of roles across the niche of their research topic. And look for new collaborations if a team lacks a certain role. This will be possible within an institute but also outside of the institute and thereby foster new collaborations.