Knowledge graphs

Knowledge graphs are collections of data representing interrelated facts. Typically they include networks of computer-readable, interlinked representations of entities, such as people, places, events, concepts, things. Knowledge graphs use graph-structured data models to integrate data. The term knowledge graph gained popularity after 2012, when Google introduced their Knowledge Graph. Researchers Lisa Ehrlinger and Wolfram Wöß refer to the term as a buzzword adopted by business and academia alike to describe different knowledge representation applications. Building a knowledge graph might or might not involve the use of Semantic Web technologies in the process of knowledge creation, knowledge hosting, knowledge curation, and knowledge deployment (processes defined in Fensel, D. et al. (2020). How to Build a Knowledge Graph. In: Knowledge Graphs. Springer, Cham. https://doi.org/10.1007/978-3-030-37439-6_2).

 “Knowledge graphs are critical to many enterprises today: They provide the structured data and factual knowledge that drive many products and make them more intelligent and “magical.” Inddustry-scale knowledge graphs: lessons and challenges

A collective of researchers distinguished two types of knowledge graphs in practice: open knowledge graphs and enterprise knowledge graphs.

Open knowledge graphs

Open knowledge graphs are published under the Open Data philosophy, where open means anyone can freely access, use, modify, and share for any purpose. Open knowledge graphs include DBpedia, Freebase, Wikidata, YAGO.

Enterprise knowledge graphs

Knowledge graphs are used by software companies such as Google, Microsoft and Amazon in the development of smart technologies, in the creation of dialog systems, personal assistants and artificial intelligence. Knowledge graphs are also supported by large organizations such as IBM, Samsung, Ebay, Bloomberg, NY Times, Twitter. Among other known enterprise knowledge graphs are Bing, Google, Airbnb, Amazon, eBay, Uber, LinkedIn, Accenture, Bloomberg, Capital One. For a detailed review, enjoy this lovely book available online: Knowledge Graphs.

Personal Knowledge Graphs

Along with the concepts of open and enterprise knowledge graphs, there is an emerging concept looking to point to the representation of structured information about entities that are personally important to a given user and with which they interact on a daily basis. Such entities are traditionally siloed in documents, notes, app data etc tools we use everyday.  Personal knowledge graphs are also very much like personal  data spaces (I am intentionally linking this concept here and reserving the right to make granular connections between the  two concepts) and are conceptually close to what Time Berners-Lee envisions in his project Solid. The concept of personal knowledge graphs is well presented by Ivo Velitchkov in his presentation (itself a knowledge graph of sorts) Personal Knowledge Graphs Why, what, and where to? Also researchers from Google have put a research agenda in their paper: Personal Knowledge Graphs: A Research Agenda. Very recently, in april 2023, researchers from University of Stavanger, Norway, presented the current state of PKG and the challenges that need to be addressed before they achieve widespread adoption in their paper An Ecosystem for Personal Knowledge Graphs: A Survey and Research Roadmap.

[Personal knowledge graphs] are a key enabler of secure and sophisticated personal data management and personalized services. cit. An Ecosystem for Personal Knowledge Graphs: A Survey and Research Roadmap 

A Non-technical Perspective Towards Knowledge Graphs

Technicalities aside, knowledge graphs are assemblages connected data that can hold the space for interconnected communication, exchange and knowledge discovery processes. Below I have added my perspective on knowledge graphs, holding the space for smarter marketing, as this definition serves the hypotheses I present in my book Being Dialogic. *assemblage: An assemblage is comprised of objects and their connections, which combine to make up interconnected arrangements with their own functional properties and capacities. Key to an assemblage is its co-functioning; that an object’s capacities only become realised in relation to other objects. See more in: Welcome to the Machine: Rethinking Technology and Society through Assemblage Theory. Atanas Kiryakov’s way of explaining knowledge graphs is also worth considering, as it touches on the archetypal nature of knowledge graphs as a phenomenon:

Knowledge graphs are the most advanced knowledge representation paradigm. With over 25 experience in AI, I can tell humanity never had an instrument like this. They combine the best we had with taxonomies (380 BC), semantic networks (1956), network model databases (1971), knowledge bases (1980s), ontologies (early 1990s), semantic dictionaries (late 1990s) and linked data (2000s). And all this at a scale, which reveals new qualities. The Knowledge Graph Cookbook

Knowledge Graphs From the Vantage Point of Marketing

In the information-intensive environment of the Web, marketing communications compete with all kinds of content – content generated by users, content often from the communication strategies of other organizations, content resulting from individual and organizational communication. Given this environment saturated with messages, the paradigms of marketing communications, their strategies and structures are evolving so that knowledge becomes a competitive advantage. Online marketing communications are highly dependent on knowledge-based interaction – knowledge of products, services, market environment, consumer context. In the conditions of huge data sets, hundreds of platforms and ways of connecting, however, the accumulation, storage and easy access to this knowledge is impossible without the help of a system that can serve as a system for managing the artifacts of this knowledge, namely the marketing content, user interaction history and data related to both. Knowledge graphs could function as such a system, similar to what Rashi Glaser theoretically describes as a knowledge base, and have the potential to be a means of creating a continuum of interactions in an information-intensive environment. I have explored that topic in my research (a summary here) and this is a birds-eye view of how central a knowledge graph can be for marketing communication.

Knowledge Graphs in 10 minutes by prof. Elena Simperl of Kings College London

Selected resources on knowledge graphs

Explore: Linked Jazz NOW (News On the Web) Papers:

• Knowledge Graphs
• Knowledge Graphs and Knowledge Networks: The Story in Brief
• A Brief History of Knowledge Graph’s Main Ideas: A tutorial 
• Knowledge Graphs and their Role in the Knowledge Engineering of the 21st Century (Report from Dagstuhl Seminar 22372)

Books:

• Introduction: What Is a Knowledge Graph?
• PAN, Jeff Z. et al. Exploiting Linked Data and Knowledge Graphs in Large Organisations. Springer International Publishing, 2017.
• FENSEL, Anna et al. Knowledge graphs for online marketing and sales of touristic services, Information, 11, 2020
• FENSEL, Dieter et al. Knowledge Graphs: Methodology, Tools and Selected Use Cases. Cham: Springer. 2020.
• Image source