Kojaph: Visual Definition and Exploration of Patterns in Graph Databases

Didimo, Walter and Giacchè, Francesco and Montecchiani, Fabrizio (2015) Kojaph: Visual Definition and Exploration of Patterns in Graph Databases. In: Graph Drawing and Network Visualization: 23rd International Symposium, GD 2015, September 24-26, 2015, Los Angeles, CA, USA , pp. 272-278 (Official URL: http://dx.doi.org/10.1007/978-3-319-27261-0_23).

Full text not available from this repository.


We present Kojaph, a new system for the visual definition and exploration of patterns in graph databases. It offers an expressive visual language integrated in a simple user interface, to define complex patterns as a combination of topological properties and node/edge attribute properties. Users can also interact with the query results and visually explore the graph incrementally, starting from such results. From the application perspective, Kojaph has been designed to run on top of every desired graph database management system (GDBMS). As a proof of concept, we integrated it with Neo4J, the most popular GDBMS.

Item Type:Conference Paper
Classifications:J Applications > J.999 Others
S Software and Systems > S.120 Visualization
ID Code:1495

Repository Staff Only: item control page


Angles, R., Gutiérrez, C.: Survey of graph database models. ACM Comput. Surv. 40(1), 1–39 (2008)

Bhowmick, S.S., Choi, B., Zhou, S.: VOGUE: towards A visual interaction-aware graph query processing framework. In: CIDR 2013 (2013)

Blau, H., Immerman, N., Jensen, D.: A visual language for querying and updating graphs. Technical report UM-CS-2002-037, University of Massachusetts Amherst, Computer Science Department

Chau, D.H., Faloutsos, C., Tong, H., Hong, J.I., Gallagher, B., Eliassi-Rad, T.: GRAPHITE: a visual query system for large graphs. In: ICDM 2008, pp. 963–966. IEEE (2008)

Dominguez-Sal, D., et al.: Survey of graph database performance on the HPC scalable graph analysis benchmark. In: Shen, H.T., et al. (eds.) WAIM 2010. LNCS, vol. 6185, pp. 37–48. Springer, Heidelberg (2010)

Gallagher, B.: Matching structure and semantics: a survey on graph-based pattern matching. Artif. Intell. 6, 45–53 (2006)

Hung, H.H., Bhowmick, S.S., Truong, B.Q., Choi, B., Zhou, S.: QUBLE: towards blending interactive visual subgraph search queries on large networks. VLDB J. 23(3), 401–426 (2014)

Liu, Z., Jiang, B., Heer, J.: imMens: Real-time visual querying of big data. Comput. Graph. Forum 32(3), 421–430 (2013)

Stolte, C., Tang, D., Hanrahan, P.: Polaris: a system for query, analysis, and visualization of multidimensional databases. Commun. ACM 51(11), 75–84 (2008)

Wood, P.T.: Query languages for graph databases. SIGMOD Record 41(1), 50–60 (2012)