Challenges of DAOs in decentralized science: a qualitative analysis of expert interviews

Introduction Decentralized autonomous organizations in decentralized science face unique organizational and scientific demands. This study examines core challenges encountered by DeSci DAOs and how these challenges affect governance and research practice. Methods Ten semi-structured interviews were conducted with co‐founders, working‐group leads, and long‐term contributors. Transcripts were analyzed using Kuckartz’s six‐phase qualitative content analysis. Categories were developed and refined to synthesize recurrent themes across interviews. Results Nineteen sub-categories clustered into six domains: governance, financials, contribution, onboarding, operations, and science. Findings highlight tensions between token‐weighted decision making and domain expertise, labor‐intensive hybrid accounting practices, persistent talent shortages, steep Web3 onboarding curves, fragmented project coordination, and science‐specific issues that include negotiations with technology transfer offices and the tokenization of research assets. The resulting category system provides a diagnostic baseline for understanding how decentralized governance intersects with scientific rigor. Discussion DeSci DAOs progress most effectively when blockchain-enabled transparency is paired with clearly defined coordination roles, structured onboarding pathways, and credible mechanisms for scientific validation. These features help balance organizational experimentation with proven practices and support more reliable scientific workflows.