A Reputation Economy: Results from an Empirical Survey on Academic Data Sharing

Academic data sharing is a way for researchers to collaborate and thereby meet the needs of an increasingly complex research landscape. It enables researchers to verify results and to pursuit new research questions with “old” data. It is therefore not surprising that data sharing is advocated by funding agencies, journals, and researchers alike. We surveyed 2661 individual academic researchers across all disciplines on their dealings with data, their publication practices, and motives for sharing or withholding research data. The results for 1564 valid responses show that researchers across disciplines recognise the benefit of secondary research data for their own work and for scientific progress as a whole-still they only practice it in moderation. An explanation for this evidence could be an academic system that is not driven by monetary incentives, nor the desire for scientific progress, but by individual reputation-expressed in (high ranked journal) publications. We label this system a Reputation Economy. This special economy explains our findings that show that researchers have a nuanced idea how to provide adequate formal recognition for making data available to others-namely data citations. We conclude that data sharing will only be widely adopted among research professionals if sharing pays in form of reputation. Thus, policy measures that intend to foster research collaboration need to understand academia as a reputation economy. Successful measures must value intermediate products, such as research data, more highly than it is the case now.

💡 Research Summary

The paper investigates why, despite widespread acknowledgment of its scientific benefits, academic data sharing remains modest in practice. The authors conducted an online survey of 2,661 researchers from all disciplines between 2022 and 2023, obtaining 1,564 valid responses. The questionnaire covered data ownership and management, frequency of sharing, perceived benefits and barriers, and attitudes toward formal recognition such as data citation.

Key findings show that a large majority (over 78%) of respondents agree that secondary use of data enhances reproducibility and spurs new research questions, indicating a strong conceptual endorsement of sharing. Nevertheless, actual sharing is limited: most participants report sharing only once or twice per year, and more than 40% state they do not share data at all. The principal obstacles identified are (1) technical readiness—datasets are often not cleaned or documented sufficiently for reuse; (2) legal and ethical constraints, including confidentiality, copyright, and IRB considerations; and (3) a perceived lack of reward. The third factor dominates the respondents’ hesitation, suggesting that the current academic incentive structure does not value data as a scholarly product.

To explain this discrepancy, the authors introduce the notion of a “Reputation Economy.” In the traditional academic system, reputation—measured by publications in high‑impact journals—drives career advancement, grant acquisition, and institutional prestige. Data, by contrast, is rarely incorporated into reputation metrics; data citations are not standardised, and they rarely contribute to tenure or promotion decisions. The survey reveals that 62% of participants would be more inclined to share if their datasets were formally cited, underscoring the importance of embedding data citation into the reputation calculus.

Disciplinary analysis shows that natural sciences and engineering report slightly higher sharing frequencies than social sciences and humanities, yet the reliance on reputation incentives is consistent across fields. This uniformity indicates that the barrier is systemic rather than domain‑specific.

Based on these insights, the authors propose three policy interventions: (1) institutionalise data citation and integrate citation counts into research evaluation frameworks; (2) expand funding and infrastructural support for data curation, storage, and metadata creation; and (3) align funder and journal data‑sharing mandates with reputation rewards, creating a “reputation‑linked” data policy. By treating data as an intermediate scholarly output that can accrue reputation, the authors argue that researchers will view sharing as a strategic career move rather than a charitable act.

In conclusion, the study posits that academic data sharing will only become widespread when it is embedded within the reputation economy that currently governs scholarly behaviour. Monetary incentives are insufficient; what matters is the conversion of data sharing into recognisable scholarly capital. Policymakers, funding agencies, and journal editors must therefore redesign evaluation criteria to value data products on par with traditional publications, thereby aligning the incentives of individual researchers with the collective goal of open, reproducible science.