Querying Graphs

Erscheinungsjahr 2018
ISBN: 978-1-68173-432-3
Verlag: Morgan & Claypool Publishers

Buch, Englisch, 184 Seiten, Hardback, Format (B × H): 190 mm x 235 mm

Reihe: Synthesis Lectures on Data Management

Graph data modeling and querying arises in many practical application domains such as social and biological networks where the primary focus is on concepts and their relationships and the rich patterns in these complex webs of interconnectivity. In this book, we present a concise unified view on the basic challenges which arise over the complete life cycle of formulating and processing queries on graph databases. To that purpose, we present all major concepts relevant to this life cycle, formulated in terms of a common and unifying ground: the property graph data model—the pre-dominant data model adopted by modern graph database systems.

We aim especially to give a coherent and in-depth perspective on current graph querying and an outlook for future developments. Our presentation is self-contained, covering the relevant topics from: graph data models, graph query languages and graph query specification, graph constraints, and graph query processing. We conclude by indicating major open research challenges towards the next generation of graph data management systems.

Autoren/Hrsg.

Fachgebiete

• Mathematik | Informatik EDV | Informatik EDV & Informatik Allgemein
• Mathematik | Informatik EDV | Informatik Informatik
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Automatische Datenerfassung, Datenanalyse

Inhaltsverzeichnis

- Foreword
- Acknowledgments
- Introduction
- Data Models
- Query Languages
- Constraints
- Query Specification
- Data Structures and Indexes
- Query Processing
- Physical Operators
- Research Challenges
- Bibliography
- Authors' Biographies

Über Autor(innen)

Angela Bonifati is a full professor of computer science at Université Claude Bernard Lyon 1 and affiliated with the CNRS Liris research lab. She received her Ph.D. from Politecnico di Milano in 2002 and right after she was a postdoctoral researcher at INRIA Roquencourt. Her current research interests are on the interplay of relational and graph-shaped data paradigms, particularly on schema mapping and data exchange, query processing, and learning for these data models. She was Vice Chair of ICDE 2018 for the information extraction, data cleaning, and curation track and Vice Chair of ICDE 2011 for the semi-structured data track. She is Associate Editor of the VLDB Journal, ACM TODS, and Distributed and Parallel Databases. She is a member-at-large of the ICDT council and serving on the program committees of SIGMOD, PODS, PVLDB, ICDE, and EDBT.

George Fletcher is an associate professor of computer science at Technische Universiteit Eindhoven where he is chair of the Database Group. He defended a Ph.D. at Indiana University Bloomington in 2007. His research interests span query language design and engineering, foundations of databases, and data integration. His current focus is on management of massive graphs such as social networks and linked open data. He was a co-organizer of the EDBT Summer School on Graph Data Management (2015) and is currently a member of the LDBC Graph Query Language Standardization Task Force. His other recent activities include co-organizing an NII Shonan seminar on Graph Database Systems (2018) and serving on the program committees of SIGMOD, VLDB, ISWC, ICDE, EDBT, and IJCAI.

Hannes Voigt is a software engineer at Neo4j since June 2018, where he is part of the Query Languages, Standards, and Research team. Before that he was a post-doctoral researcher at the Dresden Database Systems Group, Technische Universität Dresden and obtained his Ph.D. from the same university in 2014. As a researcher, he worked on various database topics such as declarative graph query languages, database evolution and versioning, management of schemaflexible data, and self-adapting indexes. He is member of the LDBC Graph Query Language Standardization Task Force. Other recent activities include co-editing the section on graph analytics in the Encyclopedia of Big Data Technologies, co-presenting a tutorial on graph query processing at EDBT 2017, and serving on the program committees of VLDB, ICDE, and CIKM.

Nikolay Yakovets is an assistant professor of computer science at Technische Universiteit Eindhoven. He obtained his Ph.D. from Lassonde School of Engineering at York University in 2017. He worked on various database topics at IBM CAS Canada and Empress Software Canada. His current focus is on design and implementation of core database technologies, management of massive graph data, and efficient processing of queries on graphs. His recent activities include co-presenting a tutorial on graph query processing at EDBT 2017, co-organizing the 2017 edition of the Dutch-Belgian Database Day, and serving on a program committee of ICDE.

H. V. Jagadish is Bernard A Galler Collegiate Professor of Electrical Engineering and Computer Science, and Distinguished Scientist at the Institute for Data Science, at the University of Michigan in Ann Arbor. Prior to 1999, he was Head of the Database Research Department at AT&T Labs, Florham Park, NJ. Professor Jagadish is well known for his broad-ranging research on information management, and has approximately 200 major papers and 37 patents. He is a fellow of the ACM, ""The First Society in Computing,"" (since 2003) and serves on the board of the Computing Research Association (since 2009). He has been an Associate Editor for the ACM Transactions on Database Systems (1992-1995), Program Chair of the ACM SIGMOD annual conference (1996), Program Chair of the ISMB conference (2005), a trustee of the VLDB (Very Large DataBase) foundation (2004-2009), Founding Editor-in-Chief of the Proceedings of the VLDB Endowment (2008-2014), and Program Chair of the VLDB Conference (2014). Among his many awards, he won the ACM SIGMOD Contributions Award in 2013 and the David E Liddle Research Excellence Award (at the University of Michigan) in 2008.