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What is the Value of Data? A Theory and Systematization

Raul Castro Fernandez · ACM / IMS Journal of Data Science · 2025

Data powers economies, shapes societies, and fuels decision-making, yet its value remains poorly understood. Despite its centrality, we lack a unified framework for defining, measuring, and reasoning about data’s worth. This article develops a theory and systematization of the value of data—explaining why, how, and when data generates value. We distinguish data from documents, separate objective value from subjective judgments, and identify key dimensions of data’s worth. Our framework reconciles disparate notions of information, knowledge, and utility, offering insights that validate known principles while uncovering new opportunities to extract value from data. More than a taxonomy, this work provides a conceptual foundation for integrating perspectives from computer science, economics, and beyond. The conceptual foundation clarifies data’s role in technology, markets, and governance, advancing our ability to systematically understand and harness its value.

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