It is often possible to quantify the resulting benefits from data use or analysis, or the impact of technology built upon them—for example, people willing to pay $1.99 for a transit application or output improved by X percent after analysis. But data themselves do not possess inherent, measurable value—that is, you cannot “appraise” a dataset and assign monetary value based on its size or content.
Assuming that data have value leads to arguments that they should and can only be context-specific, which has historically been the case in many instances, but not in the burgeoning landscape of data-driven innovation and research. The same dataset can be used in one algorithm to predict the delay in transit traffic and in another to effectively reorganize the logistics of a complex and timedependent system. Semantic analysis of posts on Twitter can tell us about pop culture trends or the response to a particular crisis. Data are the ultimate renewable resource.