Economic valuation of open research data: A conceptual framework and methodological approach

Abstract

Abstract The economic significance of open research data is widely acknowledged, yet its quantification remains challenging. This paper presents an effective valuation instrument to help stakeholders understand and evaluate the economic benefits of open research data. By conducting a scoping review and prioritizing user engagement, this study introduces a comprehensive conceptual framework for the economic valuation of open research data. The valuation is based on economic value and willingness to pay, employing the Contingent Valuation Method (CVM). It incorporates per-use models (view, download, and request) and periodic subscription models (monthly and yearly). An empirical survey was conducted at the National Basic Science Data Center (NBSDC) in China to verify this framework. Both pricing models, comprising five distinct tactics, was supported by surveyed users. Measuring economic value by views and by year was preferred, while willingness to pay by downloads and by year was considered more reasonable. Overall, the most applicable valuation approach is on a yearly basis. Through this case study at NBSDC, specific pricing tactics were identified, and the total economic value and users’ willingness to pay were assessed. This study is arguably the first to establish a conceptual framework with pricing tactics from a user perspective. This methodological approach for economic valuation of open research data provides evidence and tools for future research, policy formulation, and resource allocation in the context of open science and innovation.