Abstract: The current state of the semantic web is focused on data. This is a worthwhile progress in web content processing and interoperability. However, this does only marginally contribute to knowledge improvement and evolution. Understanding the world, and interpreting data, requires knowledge. Not knowledge cast in stone for ever, but knowledge that can seamlessly evolve; not knowledge from one single authority, but diverse knowledge sources which stimulate confrontation and robustness; not consistent knowledge at web scale, but local theories that can be combined. We discuss two different ways in which semantic web technologies can greatly contribute to the advancement of knowledge: semantic eScience and cultural knowledge evolution.
Keywords: Semantic web, linked data, big data, open data, knowledge, knowledge representation, ontology, machine learning, web of data, reproducible research, eScience, cultural evolution
DOI: 10.3233/SW-190376
Journal: Semantic Web, vol. 11, no. 1, pp. 63-68, 2020
