The infological equation extended: towards conceptual clarity in the relationship between data, information and knowledge

Clearly defined relationships between core concepts in our field are the bedrock for building a cumulative tradition. No concepts or relationships could be more core to the Information System (IS) field than: data, information, and knowledge. Even though several models have been developed to depict the relationship between these core concepts, none provides a completely satisfying solution to resolve problems in understanding information processing and in guiding IS research and practice. In response to the limitations in existing models, a knowledge-based theory of information is extended from Langefors’ (1973) infological equation, suggesting that information is the joint function of data and knowledge. Specifically, the proposed theory describes data as the measurement or description of states, whereas knowledge outlines the relationship between concepts underlying those states. Information, representing a status of conditional readiness for an action, is generated from the interaction between the states measured in data and their relationship with future states predicted in knowledge. Following this logic, different forms of IS are conceptualized as the embodiments of knowledge domains capable of transforming specific categories of data into information for business operations and decision-making. The proposed model helps address controversies in previous studies and provides guidance for further research.