DB ⋈ HCI: Towards Bridging the Chasm between Graph Data Management and HCI

Visual query interfaces enable users to construct queries without special training in the syntax and semantics of a query language. Traditionally, efforts toward such interface design and devising efficient query processing techniques are independent to each other. This is primarily due to the chasm between hci and data management fields as since their inception, rarely any systematic effort is made to leverage techniques and principles from each other for superior user experience. In this paper, we lay down the vision of bridging this chasm in the context of visual graph query formulation and processing. Specifically, we present the architecture and novel research challenges of a framework for querying graph data visually where the visual interface management is data-driven and query processing and performance benchmarking are hci -driven.

[1]  Jianzhong Li,et al.  Efficient Subgraph Matching on Billion Node Graphs , 2012, Proc. VLDB Endow..

[2]  Shuigeng Zhou,et al.  VOGUE: Towards A Visual Interaction-aware Graph Query Processing Framework , 2013, CIDR.

[3]  Shuigeng Zhou,et al.  PRAGUE: A Practical Framework for Blending Visual Subgraph Query Formulation and Query Processing , 2013 .

[4]  Brian P. Bailey,et al.  On the need for attention-aware systems: Measuring effects of interruption on task performance, error rate, and affective state , 2006, Comput. Hum. Behav..

[5]  Jiawei Han,et al.  gSpan: graph-based substructure pattern mining , 2002, 2002 IEEE International Conference on Data Mining, 2002. Proceedings..

[6]  Jennifer Widom,et al.  The Lowell database research self-assessment , 2003, CACM.

[7]  Ernesto Damiani,et al.  Computing graphical queries over XML data , 2001, TOIS.

[8]  Sourav S. Bhowmick,et al.  MustBlend: Blending Visual Multi-Source Twig Query Formulation and Query Processing in RDBMS , 2013, International Conference on Database Systems for Advanced Applications.

[9]  Christos Faloutsos,et al.  GRAPHITE: A Visual Query System for Large Graphs , 2008, 2008 IEEE International Conference on Data Mining Workshops.

[10]  Mary Czerwinski,et al.  Notification, Disruption, and Memory: Effects of Messaging Interruptions on Memory and Performance , 2001, INTERACT.

[11]  David Ahlström,et al.  Modeling and improving selection in cascading pull-down menus using Fitts' law, the steering law and force fields , 2005, CHI.

[12]  Shuigeng Zhou,et al.  PRAGUE: Towards Blending Practical Visual Subgraph Query Formulation and Query Processing , 2012, 2012 IEEE 28th International Conference on Data Engineering.

[13]  Letizia Tanca,et al.  A Schema-Based Approach to Modeling and Querying WWW Data , 1998, FQAS.

[14]  Tiziana Catarci,et al.  QBD*: A Graphical Query Language with Recursion , 1989, IEEE Trans. Software Eng..

[15]  Neil Immerman,et al.  A Visual Language for Querying and Updating Graphs , 2002 .

[16]  Sourav S. Bhowmick,et al.  GBLENDER: towards blending visual query formulation and query processing in graph databases , 2010, SIGMOD Conference.

[17]  P. Cochat,et al.  Et al , 2008, Archives de pediatrie : organe officiel de la Societe francaise de pediatrie.

[18]  Brian P. Bailey,et al.  Understanding and developing models for detecting and differentiating breakpoints during interactive tasks , 2007, CHI.

[19]  Qing Liu,et al.  A Partition-Based Approach to Structure Similarity Search , 2013, Proc. VLDB Endow..

[20]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[21]  Jignesh M. Patel,et al.  Efficient aggregation for graph summarization , 2008, SIGMOD Conference.

[22]  Christopher A. Monk,et al.  The Attentional Costs of Interrupting Task Performance at Various Stages , 2002 .

[23]  Moshé M. Zloof Query-by-Example: A Data Base Language , 1977, IBM Syst. J..

[24]  Shuigeng Zhou,et al.  QUBLE: towards blending interactive visual subgraph search queries on large networks , 2014, The VLDB Journal.

[25]  Laura M. Haas,et al.  PESTO : An Integrated Query/Browser for Object Databases , 1996, VLDB.

[26]  Yannis Papakonstantinou,et al.  QURSED: querying and reporting semistructured data , 2002, SIGMOD '02.

[27]  DANIELE BRAGA,et al.  XQBE (XQuery By Example): A visual interface to the standard XML query language , 2005, TODS.

[28]  Sourav S. Bhowmick,et al.  XBLEND: Visual XML Query Formulation Meets Query Processing , 2009, 2009 IEEE 25th International Conference on Data Engineering.

[29]  Shumin Zhai,et al.  Refining Fitts' law models for bivariate pointing , 2003, CHI '03.

[30]  Brian P. Bailey,et al.  Effects of intelligent notification management on users and their tasks , 2008, CHI.

[31]  Alberto O. Mendelzon,et al.  A graphical query language supporting recursion , 1987, SIGMOD '87.

[32]  Paolo Merialdo,et al.  To Weave the Web , 1997, VLDB.