research-article

MCquery: interactive visual query of relational data with coordinating context displays

Authors:

Phi Giang Pham,

Mao Lin HuangAuthors Info & Claims

ACSW '16: Proceedings of the Australasian Computer Science Week Multiconference

Article No.: 47, Pages 1 - 9

https://doi.org/10.1145/2843043.2843369

Published: 01 February 2016 Publication History

Abstract

The use of visual queries for relational data retrieval is a well-known approach. Various advanced visualization methods have been proposed to improve the quality of such queries. However, most of current methods focus on constructing queries in a single visualization context that increases user's efforts significantly in visually matching the details with their contexts. The single visualization causes the isolation of data models and query results which could be displayed on a single screen. The challenge is how to visually and synchronously represent all data models, queries and query results in a single screen that will make much convenient for users to interact with the visualization. For dealing with the challenge, this paper proposes a novel method called MCquery. This method allows query specification in the coordinating visual contexts of data models and query results by interaction on node-link graphs of relational data representations. MCquery enables relational data to be analyzed with concrete and relative results from the incremental exploration of data models, queries and query results. The demonstration based on a typical case study shows that MCquery is useful for exploring relational data in a single screen with synchronous visual integration of data models, queries and query results.

References

[1]

Abouzied, A., Hellerstein, J., and Silberschatz, A. 2012. Dataplay: interactive tweaking and example-driven correction of graphical database queries. In Proceedings of the 25th Annual ACM Symposium on User Interface Software and Technology, 207--218. DOI = http://dx.doi.org/10.1145/2380116.2380144

Digital Library

[2]

Auber, D., Archambault, D., Bourqui, R., Lambert, A., Mathiaut, M., Mary, P., Delest, M., Dubois, J., and Mélançon, G. 2012. The tulip 3 framework: A scalable software library for information visualization applications based on relational data. Research Report -7860, 31. <hal-00659880>.

[3]

Blau, H. 2001. A visual query language for relational knowledge discovery. ScholarWorks@UMass Amherst Computer Science Department Faculty Publication Series, 105.

[4]

Danaparamita, J., and Gatterbauer, W. 2011. QueryViz: Helping users understand SQL queries and their patterns. In Proceedings of the 14th International Conference on Extending Database Technology, 558--61. ACM. DOI= http://dx.doi.org/10.1145/1951365.1951440

Digital Library

[5]

Dastani, M. 2002. The role of visual perception in data visualization. Journal of Visual Languages & Computing, 13, 6, 601--622. DOI= http://dx.doi.org/10.1006/jvlc.2002.0235

[6]

D3.js. http://d3js.org/.

[7]

Van Ham, F., and Perer, A. 2009. "Search, Show Context, Expand on Demand": Supporting large graph exploration with Degree-of-Interest. In IEEE Transactions on Visualization and Computer Graphics, 15, 6, 953--960. DOI= http://dx.doi.org/10.1109/TVCG.2009.108

Digital Library

[8]

Heer, J., Card, S. K., and Landay, J. A. 2005. Prefuse: a toolkit for interactive information visualization. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 421--430. ACM. DOI= http://dx.doi.org/10.1145/1054972.1055031

Digital Library

[9]

Deer, J., and Perer, A. 2011. Orion: A system for modeling, transformation and visualization of multidimensional heterogeneous networks. In IEEE Conference on Visual Analytics Science and Technology (VAST), 51--60. DOI= http://dx.doi.org/10.1109/VAST.2011.6102441

[10]

Hoeber, O., Yang, X.-D., and Yao, Y. 2005. Visualization support for interactive query refinement. In Proceedings of The 2005 IEEE/WIC/ACM International Conference on Web Intelligence, 657--665. IEEE. DOI= http://dx.doi.org/10.1109/WI.2005.158

Digital Library

[11]

Huang, M. L. 2001. Information visualization of attributed relational data. In Proceedings of the 2001 Asia-Pacific Symposium on Information Visualisation, 9, 143--149. Australian Computer Society, Inc.

Digital Library

[12]

IBM. http://www-03.ibm.com/software/products/en/ratirosefami.

[13]

Kang, H., Getoor, L., Shneiderman, B., Bilgic, M., and Licamele, L. 2008. Interactive entity resolution in relational data: A visual analytic tool and its evaluation. IEEE Transactions on Visualization and Computer Graphics, 14, 5, 999--1014. DOI= http://dx.doi.org/10.1109/TVCG.2008.55

Digital Library

[14]

Lima, D. M. d., Rodrigues, J. F., and Traina, A. J. M. 2013. Graph-based relational data visualization. In 17th International Conference on Information Visualisation (IV), 201--219. IEEE. DOI= http://dx.doi.org/10.1109/IV.2013.28

Digital Library

[15]

Liu, Z., Navathe, S. B., and Stasko, J. T. 2001. Network-based visual analysis of tabular data. In IEEE Conference on Visual Analytics Science and Technology (VAST), 41--50. DOI= http://dx.doi.org/10.1109/VAST.2011.6102440

[16]

Microsoft. http://office.microsoft.com/en-001/access/.

[17]

Oracle. http://www.mysql.com/.

[18]

Polyviou, S., Samaras, G., and Evripidou, P. 2005. A relationally complete visual query language for heterogeneous data sources and pervasive querying. In Proceedings of 21st International Conference on Data Engineering, 471--482. IEEE. DOI= http://dx.doi.org/10.1109/ICDE.2005.12

Digital Library

[19]

Russell, A., Smart, P. R., Braines, D., and Shadbolt, N. R. 2008. NITELIGHT: A graphical tool for semantic query construction. Semantic Web User, 1--10.

[20]

Seifert, I. 2001. A pool of queries: Interactive multidimensional query visualization for information seeking in digital libraries. Information Visualization, 10, 2, 97--106. DOI= http://dx.doi.org/10.1057/ivs.2011.1

[21]

Stolte, C., Tang, D., and Hanrahan, P. 2002. Polaris: A system for query, analysis, and visualization of multidimensional relational databases. In IEEE Transactions on Visualization and Computer Graphics, 8, 1, 52--65. DOI= http://dx.doi.org/10.1109/2945.981851

Digital Library

[22]

Stolte, C., Tang, D., and Hanrahan, P. 2003. Multiscale visualization using data cubes. In IEEE Transactions on Visualization and Computer Graphics, 9, 2, 176--187. DOI= http://dx.doi.org/10.1109/INFVIS.2002.1173141

Digital Library

[23]

Sybase.http://www.sybase.com/products/modelingdevelopment/powerdesigner.

[24]

Tanin, E., Shneiderman, B., and Xie, H. 2007. Browsing large online data tables using generalized query previews. Information Systems, 32, 3, 402--423. DOI= http://dx.doi.org/10.1016/j.is.2005.12.006

Digital Library

[25]

Tu, Y., and Shen, H. -W. 2013. GraphCharter: Combining browsing with query to explore large semantic graphs. In Proceedings of IEEE Pacific Visualization Conference (PacificVis' 2013), 49--56. DOI= http://dx.doi.org/10.1109/PacificVis.2013.6596127

Cited By

Pham PHuang MNguyen Q(2017)Interactive Data Exploration through Multiple Visual Contexts with Different Data Models and Dimensions2017 21st International Conference Information Visualisation (IV)10.1109/iV.2017.53(84-89)Online publication date: Jul-2017
https://doi.org/10.1109/iV.2017.53

Recommendations

KMVQL: a visual query interface based on Karnaugh map
AVI '08: Proceedings of the working conference on Advanced visual interfaces

Extracting information from data is an interactive process. Visualization plays an important role, particularly during data inspection. Querying is also important, allowing the user to isolate promising portions of the data. As a result, data ...
Dynamic query tools for time series data sets: timebox widgets for interactive exploration

Timeboxes are rectangular widgets that can be used in direct-manipulation graphical user interfaces (GUIs) to specify query constraints on time series data sets. Timeboxes are used to specify simultaneously two sets of constraints: given a set of N time ...
Facilitating visual queries in the treemap using distortion techniques
Proceedings of the 2007 conference on Human interface: Part I

TreeMap is one a common space-filling visualization technique to display large hierarchies in a limited display space. In TreeMaps, highlighting techniques are widely used to depict search results from visual queries. To improve visualizing the queries ...

Comments

Information & Contributors

Information

Published In

cover image ACM Other conferences

ACSW '16: Proceedings of the Australasian Computer Science Week Multiconference

February 2016

654 pages

ISBN:9781450340427

DOI:10.1145/2843043

Copyright © 2016 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 February 2016

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Conference

ACSW '16

ACSW '16: Australasian Computer Science Week

February 1 - 5, 2016

Canberra, Australia

Acceptance Rates

ACSW '16 Paper Acceptance Rate 77 of 172 submissions, 45%;

Overall Acceptance Rate 204 of 424 submissions, 48%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

1
Total Citations
View Citations
84
Total Downloads

Downloads (Last 12 months)1
Downloads (Last 6 weeks)0

Reflects downloads up to 16 Oct 2024

Other Metrics

View Author Metrics

Citations

Cited By

Pham PHuang MNguyen Q(2017)Interactive Data Exploration through Multiple Visual Contexts with Different Data Models and Dimensions2017 21st International Conference Information Visualisation (IV)10.1109/iV.2017.53(84-89)Online publication date: Jul-2017
https://doi.org/10.1109/iV.2017.53

View Options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents