
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 forquestion 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.
KOS, Knowledge Orgaization Systems, Linked data, Interoperability, Knowledge Information System, Knowledge base, Linked data,
KOS, Knowledge Orgaization Systems, Linked data, Interoperability, Knowledge Information System, Knowledge base, Linked data,
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 6 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
