Knowledge Graphs
Morgan & Claypool Publishers (Verlag)
978-1-63639-237-0 (ISBN)
This book provides a comprehensive and accessible introduction to knowledge graphs, which have recently garnered notable attention from both industry and academia. Knowledge graphs are founded on the principle of applying a graph-based abstraction to data, and are now broadly deployed in scenarios that require integrating and extracting value from multiple, diverse sources of data at large scale.
The book defines knowledge graphs and provides a high-level overview of how they are used. It presents and contrasts popular graph models that are commonly used to represent data as graphs, and the languages by which they can be queried before describing how the resulting data graph can be enhanced with notions of schema, identity, and context. The book discusses how ontologies and rules can be used to encode knowledge as well as how inductive techniques—based on statistics, graph analytics, machine learning, etc.—can be used to encode and extract knowledge. It covers techniques for the creation, enrichment, assessment, and refinement of knowledge graphs and surveys recent open and enterprise knowledge graphs and the industries or applications within which they have been most widely adopted. The book closes by discussing the current limitations and future directions along which knowledge graphs are likely to evolve.
This book is aimed at students, researchers, and practitioners who wish to learn more about knowledge graphs and how they facilitate extracting value from diverse data at large scale. To make the book accessible for newcomers, running examples and graphical notation are used throughout. Formal definitions and extensive references are also provided for those who opt to delve more deeply into specific topics.
Aidan Hogan is an Associate Professor at the Department of Computer Science, Universidad de Chile, where he also holds the position of Associate Researcher in the Millennium Institute for Foundational Research on Data (IMFD). He received a B.Eng. and Ph.D. from the National University of Ireland, Galway, in 2006 and 2011, respectively. His primary research interests center on the Semantic Web and Knowledge Graphs. He is the author of over 100 research publications on these topics, including 2 other books: Reasoning Techniques for the Web of Data and The Web of Data. Eva Blomqvist is an Associate Professor at the Department of Computer and Information Science, Linköping University. She received a Ph.D. from Linköping University, Sweden, in 2009, in the area of Ontology Learning for the Semantic Web. After a postdoc at ISTC-CNR in Rome, Italy, she has been a member of the Semantic Web group at Linköping University since 2011. Her primary research interests include the Semantic Web and Knowledge Graphs, more specifically the development and use of ontologies as schemas for Knowledge Graphs. She is the author of over 50 research publications in the area, and has served as scientific program chair of several of the top conferences in the field. Michael Cochez is an Assistant Professor in the Knowledge Representation and Reasoning Group at the Computer Science department of the Vrije Universiteit, Amsterdam. He received his B.Sc. from the University of Antwerp, Belgium and his M.Sc. and Ph.D. degrees from the University of Jyväskylä, Finland. His research interests are in the intersection of Machine Learning and Knowledge Graphs. Claudia d'Amato is an Associate Professor at the Department of Computer Science, University of Bari, Italy and a member of the Knowledge Acquisition and Machine Learning Lab. She also holds a habilitation as Full Professor for the scientific sectors: INF/01 and ING-INF/05. She received her Master's Degree and Ph.D. from the University of Bari, Italy, in 2003 and 2007, respectively. Over the years, she has also spent several invited-researcher stays in different international universities and research institutes. Her primary research interests center on Machine Learning for the Semantic Web and Knowledge Graphs. She is the author of over 100 research publications on these topics. Gerard de Melo is a Full Professor at the Hasso Plattner Institute for Digital Engineering and at the University of Potsdam, where he holds the Chair for Artificial Intelligence and Intelligent Systems and heads the corresponding research group. Previously, he was a faculty member at Rutgers University in New Jersey and at Tsinghua University in Beijing, and a Post-Doctoral Research Scholar at ICSI/UC Berkeley. He has published over 150 papers on Natural Language Processing, Knowledge Graphs, and AI, and received a number of best paper awards. Claudio Gutierrez is Full Professor at the Department of Computer Science, Universidad de Chile. He is also a Senior Researcher in the Millennium Institute for Foundational Research on Data (IMFD). His main research interests are the computational foundations of data and knowledge. He has worked and published extensively in the areas of the Semantic Web and Databases, fields in which he received test of time awards (ISWC and PODS). He also devotes time to research in the field of the History of Science and Technology. Sabrina Kirrane is an Assistant Professor at the Vienna University of Economics and Business Institute for Information Systems and New Media, where she is also a member of the Research Institute for Cryptoeconomics and the Sustainable Computing Lab. Her research interests include Security, Privacy, and Policy aspects of the Next Generation Internet (NGI), Distributed and Decentralised Systems, Big Data, and Data Science, with a particular focus on policy representation and reasoning (e.g., access constraints, usage policies, regulatory obligations, societal norms, business processes), and the development of transparency and trust techniques for the Web. Jose Emilio Labra Gayo is an Associate Professor at the University of Oviedo, Spain. He founded the WESO (Web Semantics Oviedo) research group in 2004, whose main goal is to apply semantic technologies to solve practical problems. He was a member of the W3C Data Shapes working group and is a member of the W3C Community Groups: Shape Expressions and SHACL. He is coauthor of the Validating RDF Data book and maintains the ShEx and SHACL library SHaclEX as well as the online tools RDFShape and Wikishape. Previously, he was coordinator of the Master in Web Engineering and Dean of the School of Computer Science Engineering at the University of Oviedo (2004–2012). Roberto Navigli is a Full Professor of Computer Science at the Sapienza University of Rome, where he leads the Sapienza NLP Group. His research is focused on multilingual Natural Language Understanding, a field in which he received two grants of the European Research Council. In 2015, he received the META prize for groundbreaking work in overcoming language barriers with the BabelNet lexical-semantic knowledge graph, a project also highlighted in The Guardian and Time magazine, and winner of the Artificial Intelligence Journal prominent paper award 2017. He is the co-founder of Babelscape, a successful company which enables Natural Language Understanding in dozens of languages. Sebastian Neumaier is a researcher in the Data Intelligence group at the St. Poelten University of Applied Sciences, Austria. He received an M.Sc. and Ph.D. from the Vienna University of Technology, in 2015 and 2019, respectively. His Ph.D. thesis is centered around methods to facilitate the integration and semantic enrichment of Open Data sources using Knowledge Graph technologies. His current research focuses on different aspects of semantic data management. Axel-Cyrille Ngonga Ngomo is a Full Professor for Data Science at Paderborn University. He obtained his M.Sc., Ph.D., and habilitation from the University of Leipzig, where he also led the Agile Knowledge Engineering and Semantic Web Group. His research focuses on the automation of the lifecycle of knowledge graphs. Thus, his works include the development of approaches for the extraction, integration, fusion, storage, analysis, and exploitation of knowledge graphs. Axel Polleres heads the Institute for Data, Process, and Knowledge Management of Vienna University of Economics and Business (WU Wien), which he joined in September 2013 as a Full Professor in the area of "Data and Knowledge Engineering". He is also a faculty member of the Complexity Science Hub Vienna and was a visiting professor at Stanford University in 2018. He obtained his Ph.D. and habilitation from Vienna University of Technology. His research focuses on ontologies, query languages, logic programming, configuration technologies, Artificial Intelligence, Semantic Web, Linked Open Data, Knowledge Graphs, and their applications for Knowledge Management. Moreover, he actively contributed to international standardization efforts within the World Wide Web Consortium (W3C) where he co-chaired the W3C SPARQL working group. Sabbir M. Rashid is a Ph.D. candidate at Rensselaer Polytechnic Institute (RPI) working with Deborah L. McGuinness on research related to data annotation and harmonization, ontology engineering, knowledge representation, and various forms of reasoning. Prior to RPI, Sabbir completed a double major at Worcester Polytechnic Institute, where he received B.Sc. degrees in both Physics and Electrical & Computer Engineering. Much of his graduate studies at RPI have involved research related to data annotation and transformation using Semantic Data Dictionaries. His current work includes the applicationof deductive and abductive inference techniques over Linked Health Data, such as in the context of chronic diseases like diabetes. Anisa Rula has been an Assistant Professor in Computer Science at the Department of Information Engineering, University of Brescia since January 2021 and a researcher at the University of Bonn in the SDA group since January 2017. She obtained her doctoral degree in Computer Science from the University of Milano-Bicocca in 2014. Her research interests are in the intersection of semantic knowledge technologies and data quality with a particular focus on data integration. She is researching new solutions to data integration with respect to the quality of data modeling and efficient solutions for largescale data sources. Recently, she has been working on data understanding for large and complex datasets, on knowledge extraction, and on semantic data enrichment and refinement. Juan 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. His academic and industry work has been on designing and building Knowledge Graph for enterprise data integration where he has researched and developed technologies for semantic and graph data virtualization, ontology and graph data modeling and schema mapping, and data integration methodologies. Juan holds a Ph.D. in Computer Science from the University of Texas at Austin. He 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 International Semantic Web Conference 2014, and the 2015 Best Transfer and Innovation Project awarded by the Institute for Applied Informatics. Juan bridges academia and industry through standardization committees, being a co-chair of the Property Graph Schema Working Group, as well as a past invited expert member and standards editor at the World Wide Web Consortium (W3C). Lukas Schmelzeisen is a Ph.D. candidate working with Steffen Staab in the Analytic Computing group at the University of Stuttgart, Germany. He holds a B.Sc. in Computer Science, which he received in 2015 at University of Koblenz–Landau. His main research interests are continuous representations of both natural language corpora and knowledge graphs. In particular, his current focus is on how such representations can be updated over time. Steffen Staab holds a Cyber Valley endowed chair for Analytic Computing at the University of Stuttgart, Germany, and a chair for Web and Computer Science at the University of Southampton, UK. Steffen is a fellow of the European Association for Artificial Intelligence. His research interests range from knowledge graphs and machine learning to the semantics of human–computer interaction. He is co-director of the Interchange Forum for Reflecting on Intelligent Systems (IRIS) at the University of Stuttgart. Antoine Zimmermann is an Associate Professor at Mines Saint-Étienne in France. He received M.Sc. and Ph.D. degrees from the University of Grenoble, France in 2004 and 2008, respectively. He spent two years at the Digital Enterprise Research Institute in Galway, Ireland, from 2009 to 2010, then one year at INSA Lyon, France, before getting a position at Mines Saint-Étienne, where he has been a permanent researcher since 2012. In 2021, he received his habilitation from Université Jean Monnet, Saint-Étienne. His research interests are related to the Semantic Web, more specifically on knowledge representation, knowledge engineering, reasoning, data management, and context on the Web.
Preface
Acknowledgments
Introduction
Data Graphs
Schema, Identity, and Context
Deductive Knowledge
Inductive Knowledge
Creation and Enrichment
Quality Assessment
Refinement
Publication
Knowledge Graphs in Practice
Conclusions
Bibliography
Authors' Biographies
| Erscheinungsdatum | 01.12.2021 |
|---|---|
| Reihe/Serie | Synthesis Lectures on Data, Semantics, and Knowledge |
| Verlagsort | San Rafael |
| Sprache | englisch |
| Maße | 152 x 229 mm |
| Gewicht | 333 g |
| Themenwelt | Informatik ► Datenbanken ► Data Warehouse / Data Mining |
| Mathematik / Informatik ► Informatik ► Theorie / Studium | |
| ISBN-10 | 1-63639-237-7 / 1636392377 |
| ISBN-13 | 978-1-63639-237-0 / 9781636392370 |
| Zustand | Neuware |
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