skip to main content
10.1145/2500410.2500417acmotherconferencesArticle/Chapter ViewAbstractPublication PageswodConference Proceedingsconference-collections
research-article

Visualizing a large collection of open datasets: an experiment with proximity graphs

Published: 03 June 2013 Publication History

Abstract

We deal in this paper with the problem of creating an interactive and visual map for a large collection of Open datasets. We first describe how to define a representation space for such data, using text mining techniques to create features. Then, with a similarity measure between Open datasets, we use the K-nearest neighbors method for building a proximity graph between datasets. We use a force-directed layout method to visualize the graph (Tulip Software). We present the results with a collection of 300,000 datasets from the French Open data web site, in which the display of the graph is limited to 150,000 datasets. We study the discovered clusters and we show how they can be used to browse this large collection.

References

[1]
M. W. Berry and M. Castellanos. Survey of Text Mining II: Clustering, Classification, and Retrieval. 1 edition.
[2]
P. Bose, V. Dujmovic, F. Hurtado, J. Iacono, S. Langerman, H. Meijer, V. S. Adinolfi, M. Saumell, and D. R. Wood. Proximity graphs: E, Δ, Δ, χ and ω. Int. J. Comput. Geometry Appl., 22(5):439--470, 2012.
[3]
D. Eppstein, M. S. Paterson, and F. F. Yao. On nearest neighbor graphs. Discrete & Computational Geometry, 17(3):263--282, April 1997.
[4]
Y. Frishman and A. Tal. Multi-level graph layout on the gpu. IEEE Transactions on Visualization and Computer Graphics, 13(6):1310--1319, Nov. 2007.
[5]
S. Hachul and M. JÃijnger. Large-graph layout algorithms at work: An experimental study. Journal of Graph Algorithms and Applications, 11(2):345--369, 2007.
[6]
S. Hachul and M. Jünger. Large-graph layout with the fast multipole multilevel method. Technical report, 2005.
[7]
I. Herman, G. Melancon, and M. S. Marshall. Graph visualization and navigation in information visualization: A survey. IEEE Transactions on Visualization and Computer Graphics, 6(1):24--43, 2000.
[8]
B. Shneiderman. The eyes have it: A task by data type taxonomy for information visualizations. In Proceedings of the 1996 IEEE Symposium on Visual Languages, VL '96, pages 336--343, Washington, DC, USA, 1996. IEEE Computer Society.

Cited By

View all

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Other conferences
WOD '13: Proceedings of the 2nd International Workshop on Open Data
June 2013
42 pages
ISBN:9781450320207
DOI:10.1145/2500410
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]

Sponsors

  • BNF: Bibliothèque Nationale de France
  • PATRIMA: PATRIMA: Foundation for Cultural Heritage Sciences
  • ETIS: ETIS, Information Processing and Systems Lab
  • University of Cergy-Pontoise

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 03 June 2013

Permissions

Request permissions for this article.

Check for updates

Qualifiers

  • Research-article

Conference

WOD '13
Sponsor:
  • BNF
  • PATRIMA
  • ETIS

Acceptance Rates

WOD '13 Paper Acceptance Rate 3 of 13 submissions, 23%;
Overall Acceptance Rate 3 of 13 submissions, 23%

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)1
  • Downloads (Last 6 weeks)0
Reflects downloads up to 17 Feb 2025

Other Metrics

Citations

Cited By

View all

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media