Abstract

Knowledge Graphs can be considered the fulfilling of an early vision in Computer Science of creating intelligent systems that integrate knowledge and data at large scale. Stemming from scientific advancements in research areas of Semantic Web, Databases, Knowledge representation, NLP, Machine Learning, among others, Knowledge Graphs have rapidly gain popularity in academia and industry in the past years. The integration of such disparate disciplines and techniques give the richness to Knowledge Graphs, but also present the challenge to practitioners and theoreticians to know how current advances develop from early techniques in order, on one hand, take full advantage of them, and on the other, avoid reinventing the wheel. This tutorial will provide a historical context on the roots of Knowledge Graphs grounded in the advancements of Logic, Data and the combination thereof.

This tutorial is accompanied by the paper: A Brief History of Knowledge Graph's Main Ideas: A tutorial

Motivation

Understanding the historical context and background of one's research area is of utmost importance. An early step in the scientific method is to conduct background research in order to stand on shoulder of giants. When it comes to the Semantic Web research area, and in particular for one of its most promising development, Knowledge Graphs, we have observed that students and junior researchers are not very well aware of the history of this research area.

Throughout 2018, Juan Sequeda gave a talk titled "Integrating Semantic Web in the Real World: A journey between two cities" where he provided a brief historical overview of Logic and Data. He always asked the audience to raise their hand if they are aware of the Japanese 5th Generation Project. Throughout the fifteen times that this talk was given, each time, only a few hands were raised, usually from senior researchers attending.

Claudio Gutierrez, with similar motivations, presented in several places a short scheme of the history of Knowledge Graphs (“ A concise account of the notion of Knowledge Graph”) that sparked unpredictable interest from young researchers.

This recurring event is a motivation for this tutorial. To the best of our knowledge, we are not aware of any other tutorial that presents historical overview to the Semantic Web and Knowledge Graph research areas.

Goal

The goal of this tutorial is to provide a high level overview of the key ideas, theories and events that have occurred over the past 50 years which has lead to the development of the Semantic Web and Knowledge Graphs.

It is important to acknowledge that this is not a survey.

We will not dive into details.

We present a map and guidelines to navigate through the most important ideas, theories and events that have signaled and trigger current development, in order to understand what worked, what did not work and reflecting how it inspired the next ideas.

Description

This tutorial is organized in the following sections:

  • I. Advent of the digital age (1950s and 1960s)
  • II. Data and Knowledge Foundations (1970s)
  • III. Managing Data and Knowledge (1980s)
  • IV. Data, Knowledge and the Web (1990s)
  • V. Data and Knowledge at Large Scale (2000s)

Th tutorial has been given as A) 1 hour Invited Talk/Keynote (50 min + 10 questions) or B) half day lecture style.

The attendees of this tutorial will leave with a general historical context of Knowledge and Data, how it has been combined leading to the advent of the Semantic Web and Knowledge Graphs. Furthermore, the attendees will leave with homework, namely a list of seminal papers that they should consider reading.

There is no expected prior knowledge, except for a desire to learn and appreciate the history and background of their discipline.

Audience

The primary audience would be students and junior researchers.

The secondary expected audience would be senior researchers who would want to contribute and complement the content of the tutorial.

Events

This tutorial has been presented:

Presenters

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Claudio Gutierrez
(Universidad de Chile)

Claudio Gutierrez is full professor at the Computer Science Department, Universidad de Chile and Senior Research at the Millenium Institute for Foundation of Data. His research experiences lies in the intersection of Databases and the Semantic Web, focusing in data models and query languages for RDF layer, particularly RDF and SPARQL. Currently is interested in Open Data, Linked Data and Foundations of Data. He has published extensively in the area, edited three books and received several best paper awards at Semantic Web Conferences. Was awarded the SWSA Ten-Year Award from the International Semantic Web Conference, 2016; the Test of Time Award from the Principles of Database Systems, ACM-PODS 2014, and was International Scholar 2015-2016 for the Society for the History of Technology (SHOT). He is involved in both, Database and SW communities, where has been in PC committees of ICDT, PODS, WWW, ESWC, ISWC, RR, and several workshops.

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Juan Sequeda
(data.world)

Juan F. Sequeda is the Principal Scientist at data.world. He joined through the acquisition of Capsenta, a company he founded as a spin-off from his research. He holds a PhD in Computer Science from The University of Texas at Austin. Juan's goal is to create knowledge from inscrutable data reliably. His research interests are on the intersection of Logic and Data for (ontology-based) data integration and semantic/graph data management. Juan is the recipient of the NSF Graduate Research Fellowship, received 2nd Place in the 2013 Semantic Web Challenge for his work on ConstituteProject.org, Best Student Research Paper at the 2014 International Semantic Web Conference and the 2015 Best Transfer and Innovation Project awarded by Institute for Applied Informatics. Juan is on the Editorial Board of the Journal of Web Semantics, member of multiple program committees (ISWC, ESWC, WWW, AAAI, IJCAI). Juan has served as a bridge between academia and industry as the current chair of the Property Graph Schema Working Group, member of the Graph Query Languages task force of the Linked Data Benchmark Council (LDBC) and past invited expert member and standards editor at the World Wide Web Consortium (W3C).

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