Science Data Sharing: Applying a Disruptive Technology Platform Business Model

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Issue Date
2022
Authors
Edwards, Alan
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Abstract
This research investigated the potential to enhance global science data sharing through market-driven strategies utilizing technology platform-based business models compared to the existing fiat strategy characterized by government-funded programs and highly fragmented information systems. With less than 1% of science data shared globally, and some estimates of data collection time-cost valued at USD billions per year, there is significant social value to be released in addressing this issue. The purpose of this research is to identify whether a paradigm shift in business model is required to enable the release of excess value from science data gathering by facilitating data re-use; and incentivize increased market participation by currently marginalized groups that gather science data. A literature review was undertaken to understand (a) the characteristics of successful platform business models and (b) whether those lessons can be applied to science-data sharing to formulate a market-driven business model appropriate to satisfying the un-met needs of the global and frequently marginalized science community. Participation in international science industry discussions, review of science data gathering grant requirements from USA and European institutions, and extensive literature review formed the basis of a questionnaire that was distributed to CEO of citizen science (CS) organizations globally who were used as a proxy for the broader science community to undertake a survey of unmet needs in both developed and underdeveloped countries. Responses were analyzed to determine the pattern of unmet needs from both legacy business models for sharing data, and from a hypothetical platform business model that had the attributes of successful market-driven businesses. Evidence pointed towards a clear market failure to satisfy the unmet needs of a broad CS community particularly those residing in underdeveloped countries, and a significant opportunity to release excess value of global benefit. The research has recommended that a paradigm shift in business model towards that of an open platform-technology be established that rewards science data contributors based on free-market principles. i.e., centralized standards and data custodianship, but with distributed ownership, and rewards (both monetary and through recognition) based on the value that the market places on published contributions to the platform.
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Keywords
science data sharing , open platform technology , citizen science , entrepreneurial data scientists , release of excess value in science , platform technology strategy
License
Attribution-NonCommercial-NoDerivs 3.0 United States , openAccess
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