Big Structure: At The Nexus of Knowledge Bases, the Semantic Web and Artificial Intelligence

In Part I of this two-part series, Fred Giasson and I looked back over a decade of working within the semantic Web and found it partially successful but really the wrong question moving forward. The inadequacies of the semantic Web to date reside in its lack of attention to practical data interoperability across organizational or community boundaries. An emphasis on linked data has created an illusion that questions of data integration are being effectively addressed. Linked data is hard to publish and not the only useful form for consuming data; linked data quality is often unreliable; the linking predicates for relating disparate data sources to one another may be inadequate or wrong; and, there are no reference groundings for relating data values across datasets. Neither the semantic Web nor linked data has developed the practices, tooling or experience to actually interoperate data across the Web.