Abstract
Linked Data is an increasingly important source of information and contextual knowledge in Data Science, and its appropriate visualization is key to effectively exploit them. This work presents an ontology to generate graph-based visualizations of Linked Data in a flexible and efficient way. The ontology has been used to successfully visualize DrugBank and DBPedia datasets in a large visualization environment.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Bikakis, N., Papastefanatos, G., Skourla, M., Sellis, T.: A hierarchical aggregation framework for efficient multilevel visual exploration and analysis. Semant. Web 8(1), 139–179 (2017)
Bikakis, N., Sellis, T.K.: Exploration and visualization in the web of big linked data: a survey of the state of the art. In: Proceedings of the Workshops of the EDBT/ICDT 2016 Joint Conference, EDBT/ICDT Workshops (2016)
Brandes, U., Eiglsperger, M., Lerner, J., Pich, C.: Graph markup language (GraphML). In: Handbook of Graph Drawing and Visualization, pp. 517–541. CRC Press (2013)
Callahan, A., Cruz-Toledo, J., Dumontier, M.: Ontology-based querying with Bio2RDF’s linked open data. J. Biomed. Semant. 4(1), S1 (2013)
Dudáš, M., Zamazal, O., Svátek, V.: Roadmapping and navigating in the ontology visualization landscape. In: Janowicz, K., Schlobach, S., Lambrix, P., Hyvönen, E. (eds.) EKAW 2014. LNCS (LNAI), vol. 8876, pp. 137–152. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-13704-9_11
Falconer, S.: OntoGraf (2016). http://protegewiki.stanford.edu/wiki/OntoGraf
Fayyad, U., Grinstein, G.G., Wierse, A. (eds.): Information Visualization in Data Mining and Knowledge Discovery. Morgan Kaufmann, San Francisco (2002)
Febretti, A., et al.: CAVE2: a hybrid reality environment for immersive simulation and information analysis. In: Proceedings of the IS&T/SPIE Electronic Imaging, the Engineering Reality of Virtual Reality 2013, San Francisco, USA (2013)
Ghorbel, F., Hamdi, F., Ellouze, N., Métais, E., Gargouri, F.: Visualizing large-scale linked data with memo graph. Procedia Comput. Sci. 112, 854–863 (2017)
Gómez-Romero, J., Molina-Solana, M., Oehmichen, A., Guo, Y.: Visualizing large knowledge graphs: a performance analysis. Future Gener. Comput. Syst. 89, 224–238 (2018)
Haag, F., Lohmann, S., Negru, S., Ertl, T.: OntoViBe 2: advancing the ontology visualization benchmark. In: Lambrix, P. (ed.) EKAW 2014. LNCS (LNAI), vol. 8982, pp. 83–98. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-17966-7_9
Hinge, A., Auber, D.: Distributed graph layout with spark. In: Proceedings of the IEEE 19th International Conference on Information Visualisation (iV 2015), pp. 271–276 (2015)
Hitzler, P., Krótzsch, M., Parsia, B., Patel-Schneider, P.F., Rudolph, S.: OWL2 Web Ontology Language Primer, 2nd edn. (2012). https://www.w3.org/TR/owl2-primer/
Horridge, M.: OWLViz (2013). http://protegewiki.stanford.edu/wiki/OWLViz
Hussain, A., Latif, K., Rextin, A.T., Hayat, A., Alam, M.: Scalable visualization of semantic nets using power-law graphs. Appl. Math. Inf. Sci. 8(1), 355–367 (2014)
Jacomy, M., Venturini, T., Heymann, S., Bastian, M.: ForceAtlas2, a continuous graph layout algorithm for handy network visualization designed for the Gephi software. PLoS ONE 9(6), 1–12 (2014)
Krivov, S., Williams, R., Villa, F.: GrOWL: a tool for visualization and editing of OWL ontologies. J. Web Semant. 5(2), 54–57 (2007)
Lehmann, J., et al.: DBpedia - a large-scale, multilingual knowledge base extracted from Wikipedia. Semant. Web 6(2), 167–195 (2015)
Leigh, J., et al.: Scalable resolution display walls. Proc. IEEE 101(1), 115–129 (2013)
Liepinš, R., Grasmanis, M., Bojārs, U.: OWLGrEd ontology visualizer. In: Proceedings of the International Semantic Web Conference Workshop ISWC-DEV, vol. 1268, pp. 37–42 (2014)
Lohmann, S., Negru, S., Haag, F., Ertl, T.: Visualizing ontologies with VOWL. Semant. Web 7(4), 399–419 (2016)
Mai, G., Janowicz, K., Hu, Y., McKenzie, G.: A linked data driven visual interface for the multi-perspective exploration of data across repositories. In: Proceedings of the 2nd International Workshop on Visualization and Interaction for Ontologies and Linked Data (VOILA2016), pp. 93–101 (2016)
Martin, M., Abicht, K., Stadler, C., Ngonga Ngomo, A.C., Soru, T., Auer, S.: CubeViz - exploration and visualization of statistical linked data. In: Proceedings of the 24th International Conference on World Wide Web (WWW 2015), pp. 219–222 (2015)
McCormick, B.H.: Visualization in scientific computing. ACM SIGBIO Newslett. 10(1), 15–21 (1988)
McGinn, D., Birch, D., Akroyd, D., Molina-Solana, M., Guo, Y., Knottenbelt, W.J.: Visualizing dynamic bitcoin transaction patterns. Big Data 4(2), 109–119 (2016)
Musen, M.A.: The Protégé project: a look back and a look forward. AI Matters 1(4), 4–12 (2015)
Newman, D., et al.: Visualizing search results and document collections using topic maps. J. Web Semant. 8(2–3), 169–175 (2010)
Nikolaou, C., et al.: Sextant: visualizing time-evolving linked geospatial data. J. Web Semant. 35, 35–52 (2015)
Pienta, R., Abello, J., Kahng, M., Chau, D.H.: Scalable graph exploration and visualization: sensemaking challenges and opportunities. In: Proceedings of the 2015 International Conference on Big Data and Smart Computing (BIGCOMP), pp. 271–278, Februrary 2015
Ristoski, P., Paulheim, H.: Semantic web in data mining and knowledge discovery: a comprehensive survey. J. Web Semant. 36, 1–22 (2016)
Rodriguez, M.A.: The Gremlin graph traversal machine and language. In: Proceedings of the 15th ACM Symposium on Database Programming Languages (DBLP 2015), pp. 1–10 (2015)
Schreiber, G., Raimond, Y.: RDF 1.1 Primer (2014). https://www.w3.org/TR/rdf11-primer/
Sintek, M.: OntoViz (2007). http://protegewiki.stanford.edu/wiki/OntoViz
Smoot, M.E., Ono, K., Ruscheinski, J., Wang, P.L., Ideker, T.: Cytoscape 2.8: new features for data integration and network visualization. Bioinformatics 27(3), 431–432 (2011)
Sowa, J.F.: Conceptual graphs. In: van Harmelen, F., Porter, B., Lifschitz, V. (eds.) Handbook of Knowledge Representation, vol. 3, pp. 213–237. Elsevier, Amsterdam (2008). Chap. 5
Storey, M.A., Noy, N.F., Musen, M., Best, C., Fergerson, R., Ernst, N.: Jambalaya: an interactive environment for exploring ontologies. In: Proceedings of the 7th International Conference on Intelligent User Interfaces, p. 239 (2002)
TopQuadrant Inc.: TopBraid Composer (2016). http://www.topquadrant.com/tools/IDE-topbraid-composer-maestro-edition/
Von Landesberger, T., et al.: Visual analysis of large graphs: state-of-the-art and future research challenges. Comput. Graph. Forum 30(6), 1719–1749 (2011)
Wachsmann, L.: OWLPropViz (2008). http://protegewiki.stanford.edu/wiki/OWLPropViz
Xin, R.S., Crankshaw, D., Dave, A., Gonzalez, J.E., Franklin, M.J., Stoica, I.: GraphX: unifying data-parallel and graph-parallel analytics. In: Proceedings of the USENIX Symposium on Operating Systems Design and Implementation (OSDI 2014) (2014)
Zaharia, M., Chowdhury, M., Franklin, M.J., Shenker, S., Stoica, I.: Spark: cluster computing with working sets. In: Proceedings of the 2nd USENIX Conference on Hot topics in cloud computing (HotCloud) (2010)
Acknowledgements
Juan Gómez-Romero is supported by Universidad de Granada under the Young Researchers Fellowship Programme, and the Spanish Ministry of Education, Culture and Sport under the José Castillejo Research Stays Programme. Miguel Molina-Solana is supported by the EU’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 743623.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Switzerland AG
About this paper
Cite this paper
Gómez-Romero, J., Molina-Solana, M. (2018). GraphDL: An Ontology for Linked Data Visualization. In: Herrera, F., et al. Advances in Artificial Intelligence. CAEPIA 2018. Lecture Notes in Computer Science(), vol 11160. Springer, Cham. https://doi.org/10.1007/978-3-030-00374-6_33
Download citation
DOI: https://doi.org/10.1007/978-3-030-00374-6_33
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-00373-9
Online ISBN: 978-3-030-00374-6
eBook Packages: Computer ScienceComputer Science (R0)