Data Is More than Knowledge: Implications of the Reversed Knowledge Hierarchy for Knowledge Management and Organizational Memory

Abstract

In knowledge management literature it is often pointed out that it is important to distinguish between data, information and knowledge. The generally accepted view sees data as simple facts that become information as data is combined into meaningful structures, which subsequently become knowledge as meaningful information is put into a context and when it can be used to make predictions. This view sees data as a prerequisite for information, and information as a prerequisite for knowledge. In this paper, I will explore the conceptual hierarchy of data, information and knowledge, showing that data emerges only after we have information, and that information emerges only after we already have knowledge. The reversed hierarchy of knowledge is shown to lead to a different approach in developing information systems that support knowledge management and organizational memory. It is also argued that this difference may have major implications for organizational flexibility and renewal.

Information: A Conceptual Investigation

“…A radically different view has been suggested by Tuomi [54,55], who proposes that data emerges as a result of adding value to information, which is knowledge that has been structured and verbalized (see also [48] on this topic). Consequently, there is no "raw" data.…”

Questioning Big Data: Crowdsourcing crisis data towards an inclusive humanitarian response

“…In this paper, we analysed the process of Big Data making through crowdsourcing and open data platforms in order to explore what barriers stand in the way of this approach enabling citizens' agency in the aftermath of a crisis. Following Tuomi (1999) we flipped the conventional view of data as the raw building blocks of knowledge, arguing instead that different sources of knowledge constitute the building blocks of data. Through a detailed analysis of two humanitarian cases we showed how Big Data making comprises transformation of information, attending to the hidden normative and power issues of Big Data making.…”

“…Explaining the transformation process: From local knowledge to Big Data Data -including Big Data -is not simply found, but constructed by people in specific contexts (Tuomi, 1999). Indeed, the creation of data to be processed by computers starts with a person's knowledge of the phenomenon or situation at hand, drawing on both tacit and explicit sources (Tuomi, 1999: 5).…”

CHANGING PROVIDER IN AN OUTSOURCED INFORMATION SYSTEM PROJECT - Good Practices for Knowledge Transfer

“…According to Ivari, Linger (1999), Tuomi (1999) and Grundstein (2009) -roughly speaking-an information receiver interpreted the information "in his own way". This is due to distinct underlying individual shared knowledge space between information emitter and information receiver.…”