OQT/OQUI Systematic Literature Review Results

We conducted an adapted version of the SLR process as we focused on the content of the key papers (see process steps below).

1. Define goal of the SLR. The goal of the SLR is (a) to collect candidates for relevant OQT classification criteria for an OQT analysis framework and (b) to identify the reports on OQTs, which are candidates for the tool evaluation. This SLR is an initial work, and will be further extended in the future work.

2. Scope of the SLR to identify and select primary studies. The scope of SLR sources for the primary studies should cover the conference proceedings and journals most relevant for the OQT scientific community. Therefore, we included the proceedings of six conferences and four journals that can be considered as most relevant in the semantic web field. The SLR covers 1204 papers from the last 5 years, i.e., papers published in 2008 to 2013 and fitting the following keywords: query OR sparql OR user OR interface OR visual OR interactive OR graphic. We are searching for primary studies in the selected conferences and journals manually from DBLP and the official website of conferences and journals in February 2013, which resulted in 78 papers.

3. Inclusion and exclusion criteria. In order to select the most relevant papers from the results of the previous step, we used the following inclusion and exclusion criteria. Inclusion Criteria: Full papers that provide an approach or survey or classification framework regarding ontology querying tools and/or relevant ontology tools (e.g., ontology visualization tools and ontology query user interface). Exclusion Criteria: Papers that do not introduce tools or interfaces related to ontology querying and/or relevant ontology tools. The process of applying these inclusion and exclusion criteria to the full papers reduced the number of papers finally to 24 papers, which were used for the extraction of candidate for criteria and tools (see Sections 7.1 and 8.1).

Here we provide the complete citation lists of the papers:

[1] P. Smart, A. Russell, and D. Braines, “A visual approach to semantic query design using a web-based graphical query designer,” Knowledge Engineering: Practice and Patterns, pp. 275–291, 2008.
[2] V. Tablan, D. Damljanovic, and K. Bontcheva, “A natural language query interface to structured information,” The Semantic Web: Research and Applications, pp. 361–375, 2008.
[3] H. Wang, K. Zhang, Q. Liu, T. Tran, and Y. Yu, “Q2semantic: A lightweight keyword interface to semantic search,” The Semantic Web: Research and Applications, pp. 584–598, 2008.
[4] D. F. Huynh, R. C. Miller, and D. R. Karger, “Potluck: Data mash-up tool for casual users,” Web Semantics: Science, Services and Agents on the World Wide Web, vol. 6, no. 4, pp. 274–282, 2008.
[5] A. Averbakh, D. Krause, and D. Skoutas, “Exploiting user feedback to improve semantic web service discovery,” The Semantic Web-ISWC 2009, pp. 33–48, 2009.
[6] D. Petrelli, S. Mazumdar, A. S. Dadzie, and F. Ciravegna, “Multi visualization and dynamic query for effective exploration of semantic data,” The Semantic Web-ISWC 2009, pp. 505–520, 2009.
[7] G. Zenz, X. Zhou, E. Minack, W. Siberski, and W. Nejdl, “From keywords to semantic queries—Incremental query construction on the Semantic Web,” Web Semantics: Science, Services and Agents on the World Wide Web, vol. 7, no. 3, pp. 166–176, 2009.
[8] S. Schenk, C. Saathoff, S. Staab, and A. Scherp, “SemaPlorer—interactive semantic exploration of data and media based on a federated cloud infrastructure,” Web Semantics: Science, Services and Agents on the World Wide Web, vol. 7, no. 4, pp. 298–304, 2009.
[9] S. Batsakis and E. Petrakis, “SOWL: spatio-temporal representation, reasoning and querying over the semantic web,” in I-SEMANTICS ’10 Proceedings of the 6th International Conference on Semantic Systems, 2010, p. 15.
[10] H. Paulheim and F. Probst, “Ontology-enhanced user interfaces: A survey,” International Journal on Semantic Web and Information Systems (IJSWIS), vol. 6, no. 2, pp. 36–59, 2010.
[11] G. Ladwig and T. Tran, “Combining query translation with query answering for efficient keyword search,” The Semantic Web: Research and Applications, pp. 288–303, 2010.
[12] S. Araujo, G. J. Houben, D. Schwabe, and J. Hidders, “Fusion–Visually Exploring and Eliciting Relationships in Linked Data,” The Semantic Web: Research and Applications, pp. 1–15, 2010.
[13] P. Heim, S. Lohmann, and T. Stegemann, “Interactive relationship discovery via the semantic web,” The Semantic Web: Research and Applications, pp. 303–317, 2010.
[14] D. Damljanovic, M. Agatonovic, and H. Cunningham, “Natural language interfaces to ontologies: Combining syntactic analysis and ontology-based lookup through the user interaction,” The Semantic Web: Research and Applications, pp. 106–120, 2010.
[15] T. Tran, T. Mathäß, and P. Haase, “Usability of keyword-driven schema-agnostic search,” The Semantic Web: Research and Applications, pp. 349–364, 2010.
[16] A. Harth, “VisiNav: A system for visual search and navigation on web data,” Web Semantics: Science, Services and Agents on the World Wide Web, vol. 8, no. 4, pp. 348–354, 2010.
[17] A. S. Dadzie and M. Rowe, “Approaches to visualising Linked Data: A survey,” Semantic Web, vol. 2, no. 2, pp. 89–124, 2011.
[18] E. Motta, P. Mulholland, S. Peroni, M. d’Aquin, J. Gomez-Perez, V. Mendez, and F. Zablith, “A novel approach to visualizing and navigating ontologies,” The Semantic Web–ISWC 2011, pp. 470–486, 2011.
[19] I. Popov, M. Schraefel, W. Hall, and N. Shadbolt, “Connecting the dots: a multi-pivot approach to data exploration,” The Semantic Web–ISWC 2011, pp. 553–568, 2011.
[20] D. Koutsomitropoulos, R. Borillo Domenech, and G. Solomou, “A structured semantic query interface for reasoning-based search and retrieval,” The Semantic Web: Research and Applications, pp. 17–31, 2011.
[21] J. Lehmann and L. Bühmann, “AutoSPARQL: Let users query your knowledge base,” The Semantic Web: Research and Applications, pp. 63–79, 2011.
[22] E. Kaufmann and A. Bernstein, “Evaluating the Usability of Natural Language Query Languages and Interfaces to Semantic Web Knowledge Bases,” Web Semantics: Science, Services and Agents on the World Wide Web, vol. 8, no. 4, 2011.
[23] C. Pradel, “Allowing End Users to Query Graph-Based Knowledge Bases,” Knowledge Engineering and Knowledge Management, pp. 8–15, 2012.
[24] V. Lopez, M. Fernández, E. Motta, and N. Stieler, “PowerAqua: Supporting users in querying and exploring the Semantic Web,” Semantic Web, vol. 3, no. 3, pp. 249–265, 2012.

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