This book details recent developments in the emerging area of plug-and-play (PnP) visual subgraph query interfaces (VQI). These PnP interfaces are grounded in the principles of human-computer interaction (HCI) and cognitive psychology to address long-standing limitations to bottom-up search capabilities in graph databases using traditional graph query languages, which often require domain experts and specialist programmers. This book explains how PnP interfaces go against the traditional mantra of VQI construction by taking a data-driven approach and giving end users the freedom to easily and quickly construct and maintain a VQI for any data sources without resorting to coding. The book walks readers through the intuitive PnP interface that uses templates where the underlying graph repository represents the socket and user-specified requirements represent the plug. Hence, a PnP interface enables an end user to change the socket (i.e., graph repository) or the plug (i.e., requirements) as necessary to automatically and effortlessly generate VQIs. The book argues that such a data-driven paradigm creates several benefits, including superior support for visual subgraph query construction, significant reduction in the manual cost of constructing and maintaining a VQI for any graph data source, and portability of the interface across diverse sources and querying applications. This book provides a comprehensive introduction to the notion of PnP interfaces, compares it to its classical manual counterpart, and reviews techniques for automatic construction and maintenance of these new interfaces. In synthesizing current research on plug-and-play visual subgraph query interface management, this book gives readers a snapshot of the state of the art in this topic as well as future research directions.
Sourav S Bhowmick
Sourav S. Bhowmick is an Associate Professor in the School of Computer Science and Engineering (SCSE) at Nanyang Technological University, Singapore. His core research expertise is in data management, human-data interaction, and data analytics. His research has appeared in premium venues such as ACM SIGMOD, VLDB, ACM WWW, ACM MM, ACM SIGIR,
The VLDB Journal,
Bioinformatics, and
Biophysical Journal. He is co-recipient of Best Paper Awards in ACM CIKM 2004, ACM BCB 2011, and VLDB 2021 for work on mining structural evolution of tree-structured data, generating functional summaries, and scalable attributed network embedding, respectively. He is a co-recipient of 2021 ACM SIGMOD Research Highlights Award. Sourav serves as a member of the SIGMOD Executive Committee, is a regular member of the PVLDB Advisory Board, and co-leads the committee for Diversity and Inclusion in Database Conference Venues. In 2018, he was a co-recipient of theVLDB Service Award from the VLDB Endowment. He was inducted into Distinguished Members of the ACM in 2020.
Byron Choi
Byron Choi is the Associate Head and an Associate Professor at the Department of Computer Science at Hong Kong Baptist University (HKBU). His research interests include graph-structured databases, database usability, database security, and time series analysis. Byron’s publications have appeared in premium venues such as TKDE, VLDBJ, SIGMOD, PVLDB/VLDB, and ICDE. He has served as a program committee member or reviewer of premium conferences and journals, including PVLDB, VLDBJ, ICDE, IEEE TKDE, and ACM TOIS. He was recognized as a distinguished program committee (PC) member by ACM SIGMOD 2021 and received a best reviewer award from ACM CIKM 2021 and distinguished reviewer award from PVLDB 2019. He served as the director of a Croucher Foundation Advanced Study Institute (ASI) program titled “Frontiers in Big Data Graph Research”in 2015 and was a recipient of the HKBU President’s Award for Outstanding Young Researcher in 2016.
