Unleashing the power of data through organization: Structure and connections for meaning, learning, and discovery

Knowledge organization is needed everywhere. Its importance is marked by its pervasiveness. This paper will show many areas, tasks, and functions where proper use of Knowledge Organization, construed as broadly as the term implies, provides support for learning and understanding, for sensemaking and meaning making, for inference, and for discovery by people and computer programs and thereby will make the world a better place. The paper focuses not on metadata but rather on structuring and representing the actual data or knowledge itself and argues for more communication between the largely separated KO, Ontology, Data Modeling, and Semantic Web communities to address the many problems that need better solutions. In particular, the paper discusses the application of knowledge organization in Knowledge bases for question answering and cognitive systems; Knowledge bases for information extraction from text or multimedia; Linked data; Big data and data analytics; Electronic health records as one example; Influence diagrams (causal maps), dynamic system models, process diagrams, concept maps, and other node-link diagrams; Information systems in organizations; Knowledge organization for understanding and learning; and Knowledge transfer between domains. The paper argues for moving beyond triples to a more powerful representation using entities and multi-way relationships but not attributes.