The Data-Information-Knowledge-Wisdom Hierarchy and its Antithesis

The now taken-for-granted notion that data lead to information, which leads to knowledge, which in turn leads to wisdom was first specified in detail by R. L. Ackoff in 1988. The Data-Information-KnowledgeWisdom hierarchy is based on filtration, reduction, and transformation. Besides being causal and hierarchical, the scheme is pyramidal, in that data are plentiful while wisdom is almost nonexistent. Ackoff’s formula linking these terms together this way permits us to ask what the opposite of knowledge is and whether analogous principles of hierarchy, process, and pyramiding apply to it. The inversion of the DataInformation-Knowledge-Wisdom hierarchy produces a series of opposing terms (including misinformation, error, ignorance, and stupidity) but not exactly a chain or a pyramid. Examining the connections between these phenomena contributes to our understanding of the contours and limits of knowledge. This presentation will revisit the Data-Information-Knowledge-Wisdom hierarchy linking these concepts together as stages of a single developmental process, with the aim of building a taxonomy for a postulated opposite of knowledge, which I will call ‘nonknowledge’. Concepts of data, information, knowledge, and wisdom are the building blocks of library and information science. Discussions and definitions of these terms pervade the literature from introductory textbooks to theoretical research articles (see Zins, 2007). Expressions linking some of these concepts predate the development of information science as a field of study (Sharma 2008). But the first to put all the terms into a single formula was Russell Lincoln Ackoff, in 1989. Ackoff posited a hierarchy at the top of which lay wisdom, and below that understanding, knowledge, information, and data, in that order. Furthermore, he wrote that “each of these includes the categories that fall below it,” and estimated that “on average about forty percent of the human mind consists of data, thirty percent information, twenty percent knowledge, ten percent understanding, and virtually no wisdom” (Ackoff, 1989, 3). This phraseology allows us to view his model as a pyramid, and indeed it has been likened to one ever since (Rowley, 2007; see figure 1). (‘Understanding’ is omitted, since subsequent formulations have not picked up on it.) Ackoff was a management consultant and former professor of management science at the Wharton School specializing in operations research and organizational theory. His article formulating what is now commonly called the Data-InformationKnowledge-Wisdom hierarchy (or DIKW for short) was first given in 1988 as a presidential address to the International Society for General Systems Research. This background may help explain his approach. Data in his terms are the product of observations, and are of no value until they are processed into a usable form to become information. Information is contained in answers to questions. Knowledge, the next layer, further refines information by making “possible the transformation of information into instructions. It makes control of a system possible” (Ackoff, 1989, 4), and that enables one to make it work efficiently. A managerial rather than scholarly perspective runs through Ackoff’s entire hierarchy, so that “understanding” for him