Measuring the Value of (Research) Data

Data is a unique economic asset and information resource with special economic characteristics. Across
various industries, firms are nowadays collecting and using data to optimize their processes, create
new value propositions for their customers, or sell and exchange their data with external partners. This
whitepaper outlines how firms can measure the value of their data and data-related activities.

Three main approaches exist to measure the business value of data. First, the data value can be
determined by measuring its market prices, costs, and future income prospects (market-based
approach). Second, the data’s estimated utility in economic and public benefits may be used to quantify
its value (economic approach). Third, various data- and context-related parameters may be used to
estimate the value of data in a specific setting (dimensional approach).

We further find that data that is explicitly used for research purposes differs in these valuation
approaches. Here, the value of data is often determined by its academic impact, reuse, and contribution
to scientific breakthroughs. The FAIR principles also provide a framework for enhancing the utility and
value of research data in this setting, guiding the assessment based on findability, accessibility,
interoperability, and reusability of the data.

Nevertheless, the lack of a common conceptual framework and the difficulty of predicting data's future
applications and relevance make the value measurement of data still challenging in practice.