Data-driven Visual Query Interfaces for Graphs: Past, Present, and (Near) Future

Sourav S. Bhowmick, Byron Koon Kau Choi

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

10 Citations (Scopus)

Abstract

Visual graph query interfaces (VQI) widen the reach of graph querying frameworks across a variety of end users by enabling non-programmers to use them. Several industrial and academic frameworks for querying graphs expose such visual interfaces. In this tutorial, we survey recent developments in the emerging area of data-driven visual query interface that is grounded on the principles of human-computer interaction (HCI) and cognitive psychology to enhance usability of graph querying frameworks. A data-driven VQI has many benefits such as reducing the cost in constructing and maintaining an interface, superior support for query formulation, and increased portability of the interface. We discuss the notion of making VQIs data-driven and compare it with its classical manual counterpart, and review techniques for automatic construction and maintenance of these interfaces. In addition, the tutorial suggests open problems and new research directions. In summary, in this tutorial, we review and summarize the research thus far into data-driven visual graph query interface management, giving researchers a snapshot of the current state of the art in this topic, and future research directions.

Original languageEnglish
Title of host publicationSIGMOD '22: Proceedings of the 2022 International Conference on Management of Data
PublisherAssociation for Computing Machinery (ACM)
Pages2441-2447
Number of pages7
ISBN (Print)9781450392495
DOIs
Publication statusPublished - 11 Jun 2022
EventACM SIGMOD International Conference on Management of Data, SIGMOD 2022 - Virtual, Online, Philadelphia, United States
Duration: 12 Jun 202217 Jun 2022
https://2022.sigmod.org/
https://dl.acm.org/doi/proceedings/10.1145/3514221

Publication series

NameProceedings of the ACM SIGMOD International Conference on Management of Data
ISSN (Print)0730-8078

Conference

ConferenceACM SIGMOD International Conference on Management of Data, SIGMOD 2022
Country/TerritoryUnited States
CityPhiladelphia
Period12/06/2217/06/22
Internet address

Scopus Subject Areas

  • Software
  • Information Systems

User-Defined Keywords

  • cognitive load
  • data-driven
  • graph search
  • visual query interface

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