Querying Graphs (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 indicatingmajor open research challenges towards the next generation of graph data management systems.

Angela Bonifati is a full professor of computer science at Universite 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.