6 Researcher
6.1 Researchers’ perceptions
Open Data Survey (Goodey et al., 2022)
- 75% of researchers say there is too little credit for sharing data
- main drivers:
- perceived higher citation (67%)
- increased perceived impact and visibility (61%)
6.2 Classical metrics
- Data for reuse: Additional publication (e.g., data note in F1000 Research)
- Is there higher citation?
- studies with available data: 9% more citations (Piwowar & Vision, 2013)
- studies with link to data in a repository: 25% higher citation rates (Colavizza et al., 2020)
But:
Selection bias: Willingness to share strength of evidence and quality of reporting (Wicherts et al., 2011)
But:
With higher transparency, researchers have higher trust in authors (Schneider et al., 2022)
6.3 New metrics: Get hired!
new metrics for evaluation evolving
- CoARA: “Value outputs associated with openness (FAIR data sets, […]” (CoARA, 2022, p. 21)
- signatories: DGPs, ERC, European Commission, DFG, Leibniz Association, …
- Example: DGPs recommendations on hiring and promotion (Gärtner et al., 2022; Schönbrodt et al., 2022)
(Schönbrodt et al., 2022, p. 4)
Questions to be answered at the end?
Please put them here!