Building Knowledge Graphs: A Practitioner's Guide

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Hoffart, J., Suchanek, F.M., Berberich, K., Weikum, G.: YAGO2: a spatially and temporally enhanced knowledge base from Wikipedia. Artif. Intell. J. (2012) PDF / EPUB File Name: Building_Knowledge_Graphs_-_Jesus_Barrasa.pdf, Building_Knowledge_Graphs_-_Jesus_Barrasa.epub R. Angles, C. Gutiérrez, Querying RDF data from a graph database perspective, in Proceedings of the 2nd European Semantic Web Conference (ESWC2005), Heraklion, Greece, 29 May–1 June 2005. Springer LNCS, vol. 3532 Business logic normally lives in the applications that make use of the data, doesn’t it? Correct, but that’s not necessarily a good thing for a number of reasons: the logic needs to be replicated across applications with significant duplication of effort and with a risk of inconsistency. Schultz, A., et al.: LDIF-linked data integration framework. In: Proceedings of the Second International Conference on Consuming Linked Data, vol. 782. CEUR-WS.org (2011)

Knowledge graphs are connected to a long history of research in an area of artificial intelligence called knowledge representation. The idea behind it is to combine data and business logic together in a common representation that enables the automation of complex tasks. While there are several small-sized and domain-specific KGs, on the other hand, we also have many huge-sized and domain-agnostic KG that contains facts of all types and forms. Some of the famous open-source knowledge graphs are, M. Croitoru, P. Marquis, S. Rudolph, G. Stapleton (eds.), Proceedings of the 5th International Workshop on Graph Structures for Knowledge Representation and Reasoning (GKR2017): Revised Selected Papers, Melbourne, 21 August 2017. Springer LNCS, vol. 10775 (2018) How to apply knowledge graphs in real-world scenarios and explore practical applications in various industries to drive innovation and success.Vrandečić, D., Krötzsch, M.: Wikidata: a free collaborative knowledgebase. Commun. ACM 57(10), 78–85 (2014) C. d’Amato, M. Theobald (eds.), Proceedings of the 14th International Summer School 2018: Reasoning Web. Learning, Uncertainty, Streaming, and Scalability: Tutorial Lectures, Esch-sur-Alzette, Luxembourg, 22–26 September 2018. Springer LNCS, vol. 11078 J. De Bruijn, R. Lara, A. Polleres, D. Fensel, OWL DL vs. OWL flight: conceptual modeling and reasoning for the Semantic Web, in Proceedings of the 14th International World Wide Web Conference (ISWC2005), 10–14 May 2005 (ACM, Chiba, Japan)

Author’s note: This article is also present as a chapter in my book on data science (WIP) — A Lazy Guide to Data Science . It is a weak transcription of the first part of guest lectures I gave at the University of Tartu for the Computational Social Science Group. Reference Which molecules are they developing on their own, and which molecules are they developing in collaboration with others? Freebase: a massive, collaboratively edited database of cross-linked data. Touted as “an openly shared database of the world’s knowledge”. It was bought by Google and used to power its own KG. In 2015, it was finally discontinued.

Dr. Jim Webber

Heterogenous data: supports different types of entities (person, date, painting, etc) and relations (likes, born on, etc). D. Fensel, F. van Harmelen, Unifying reasoning and search to web scale. IEEE Internet Comput. 11(2), 94–96 (2007) The syntax is not important for now. The important bit is that when your data and knowledge are managed in the form of a graph, pretty sophisticated logic can be expressed in a concise way. And equally important, evaluated efficiently at scale over large volumes of data. But we will talk about this in more detail in future posts. For now, just keep this intuition of inference as navigating up and down the data and semantic layers in a knowledge graph.

Bob: as it belongs to the Sci-fi genre same as Interstellar and Inception (which is already watched by Bob) Remember, the above representations are just for nomenclature sake, hence you may come across people referring to the fact either way. Let’s follow the HRT representation for this article. So either way, facts contain 3 elements (hence facts are also called triplets) that can help with the intuitive representation of KG as a graph, P. Hayes, The Logic of Frames, Readings in Artificial Intelligence (Morgan Kaufmann, Los Altos, CA, 1981) DBpedia: is a crowd-sourced community-based effort to extract structured content from the information present in various Wikimedia projects.This graph model (see graph on the bottom right on the image above) shows a basic network, where a company designs a molecule that acts on a molecular target, and other companies work on a different molecule but act on the same molecular target. It’s the start of a network, but it’s not the end of it. This wide-ranging guide covers everything from the basics to advanced approaches, equipping you with the knowledge and technical skills to employ this groundbreaking technology in your projects.