DATA, INFORMATION, KNOWLEDGE: A SEMIOTIC-SYSTEM’S VIEW FOR DATABASE DESIGN

Abstract

In this paper, the concepts data, information and knowledge are examined and linked with Charles S. Peirce's semiotic categories. The overall aim of the paper is to propose a Peircean semiotic framework that can be applied to database design generally. The more specific ideas developed in the paper are discussed in relation to a database being developed in the area of weed risk assessment at the Victorian Department of Primary Industries (DPI) in Australia. The argument runs as follows: For a database to be used effectively as a learning resource by its target audience(s), a designer needs to distinguish between the concepts data, information and knowledge. These concepts, it is suggested, can be linked with Peirce’s ‘three grades of clearness’, which in turn, are derived from Peirce’s triadic categorical framework, that is, his semiotic. Following Peirce, then, it is argued that if the logical role of each categorical concept is muddied, strategic action and organisational learning by the target audience(s) will be made increasingly difficult, if not impossible. Thus, in communicational terms, the author notes first that data falls into the category of Firstness, and as such, it has no meaning at all. In terms of the application examined, weed risk assessment data must be combined with an organisational structure if it is to become information. Information is therefore linked by the author to the category of Secondness – a resisting structure is identified which defines the data’s relevance and makes it something that is useable. Along similar lines, information can be put to use where it is deemed necessary, but its strategic value is entirely uncertain. Thus, it is only at the level of knowledge, which is linked by the author to the category of Thirdness, that we can apply information strategically, that is, with a real-world outcome in mind. Thus, it is argued that while each grade of clearness is necessary to database design, it is only at the third grade of clearness, or at the knowledge stage, that a weed risk assessment database can be used effectively to construct and communicate an ongoing community of enquiry around weed risk science.