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Wednesday, February 24, 2021

On Knowledge Graphs

Great piece on a favorite topic from CACM.  Only mildly technical.  Its all about usefully and efficiently representing knowledge.  Essential for anyone considering the future of string and using knowledge.  We experimented with it in the enterprise, for both historical and operational purposes. Below quick intro, more at the link.

Key Insights:

Data was traditionally considered a material object, tied to bits, with no semantics per se. Knowledge was traditionally conceived as the immaterial object, living only in people's minds and language. The destinies of data and knowledge became bound together, becoming almost inseparable, by the emergence of digital computing in the mid-20h century.

Knowledge Graphs can be considered the coming of age of the integration of knowledge and data at large scale with heterogeneous formats.

The next generation of researchers should become aware of these developments. Both successful and not, these ideas are the basis of current technology and contain fruitful ideas to inspire future research.

Knowledge Graphs    By Claudio Gutierrez, Juan F. Sequeda

Communications of the ACM, March 2021, Vol. 64 No. 3, Pages 96-104   10.1145/3418294

The notion of Knowledge Graph stems from scientific advancements in diverse research areas such as Semantic Web, databases, knowledge representation and reasoning, NLP, and machine learning, among others. The integration of ideas and techniques from such disparate disciplines presents a challenge to practitioners and researchers to know how current advances develop from, and are rooted in, early techniques.

Understanding the historical context and background of one's research area is of utmost importance in order to understand the possible avenues of the future. Today, this is more important than ever due to the almost infinite sea of information one faces everyday. When it comes to the Knowledge Graph area, we have noticed that students and junior researchers are not completely aware of the source of the ideas, concepts, and techniques they command.

The essential elements involved in the notion of Knowledge Graphs can be traced to ancient history in the core idea of representing knowledge in a diagrammatic form. Examples include: Aristotle and visual forms of reasoning, around 350 BC; Lull and his tree of knowledge; Linnaeus and taxonomies of the natural world; and in the 19th. century, the works on formal and diagrammatic reasoning of scientists like J.J. Sylvester, Charles Peirce and Gottlob Frege. These ideas also involve several disciplines like mathematics, philosophy, linguistics, library sciences, and psychology, among others.  ... " 

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