Considerable attention has been given to the measurement of “information” for the purposes of guiding investment and policy. The effort presumes that we: i) know what information is, and ii) know how to measure it. Of course, what is measured are various proxies or indicators for information, for which we aggregate statistics and then apply quantitative procedures to reach conclusions about relative “e-readiness,”“e-leadership,” or the “digital divide.” This work suffers from lack of underlying theory, and this paper proposes that it is time to reconsider and update some earlier work on the nature of “information” and the nature of “measurement” as they have evolved over time. Then we may begin to have a theoretical foundation to understand both the limits and the potential of what can be usefully said based on current models.

Initially, the paper argues that there is no single, universally applicable definition of “information.” The meaning of the word has changed over time, and it is used in so many different contexts, that no unique definition is possible–and if it were, it would be so broad as to be meaningless. It can, however, be usefully defined for a particular purpose in a particular context.