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Ontology-based end-user visual query formulation: Why, what, who, how, and which?

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Abstract

Value creation in an organisation is a time-sensitive and data-intensive process, yet it is often delayed and bounded by the reliance on IT experts extracting data for domain experts. Hence, there is a need for providing people who are not professional developers with the flexibility to pose relatively complex and ad hoc queries in an easy and intuitive way. In this respect, visual methods for query formulation undertake the challenge of making querying independent of users’ technical skills and the knowledge of the underlying textual query language and the structure of data. An ontology is more promising than the logical schema of the underlying data for guiding users in formulating queries, since it provides a richer vocabulary closer to the users’ understanding. However, on the one hand, today the most of world’s enterprise data reside in relational databases rather than triple stores, and on the other, visual query formulation has become more compelling due to ever-increasing data size and complexity—known as Big Data. This article presents and argues for ontology-based visual query formulation for end-users; discusses its feasibility in terms of ontology-based data access, which virtualises legacy relational databases as RDF, and the dimensions of Big Data; presents key conceptual aspects and dimensions, challenges, and requirements; and reviews, categorises, and discusses notable approaches and systems.

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Notes

  1. http://www.hibernate.org.

  2. http://www.mybatis.org.

  3. http://flamenco.berkeley.edu.

  4. http://www.ahmetsoylu.com/pubshare/icae2011/.

  5. http://rhizomik.net/html/rhizomer/.

  6. http://www.visualdataweb.org/tfacet.php.

  7. http://www.visualdataweb.org/gfacet.php.

  8. http://www.w3.org/TR/widgets/.

References

  1. OpenLink iSPARQL. http://dbpedia.org/isparql/

  2. Ahlberg, C., Shneiderman, B.: Visual information seeking: tight coupling of dynamic query filters with starfield displays. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI 1994), pp. 313–317. ACM (1994). doi:10.1145/191666.191775

  3. Allen, G., Parsons, J.: Is query reuse potentially harmful? Anchoring and adjustment in adapting existing database queries. Inf. Syst. Res. 21(1), 56–77 (2010). doi:10.1287/isre.1080.0189

    Article  Google Scholar 

  4. Angelaccioa, M., Catarci, T., Santucci, G.: Query by diagram: a fully visual query system. J. Vis. Lang. Comput. 1(3), 255–273 (1990). doi:10.1016/S1045-926X(05)80009-6

    Article  Google Scholar 

  5. Angles, R., Gutierrez, C.: The expressive power of SPARQL. In: Proceedings of the 7th International Conference on the Semantic Web (ISWC 2008), LNCS, vol. 5318, pp. 114–129. Springer, Berlin (2008). doi:10.1007/978-3-540-88564-1_8

  6. Assmann, U., Zschaler, S.: Ontologies, meta-models, and the model-driven paradigm. In: Calero, C., Ruiz, F., Piattini, M. (eds.) Ontologies for Software Engineering and Software Technology, pp. 249–273. Springer, Berlin (2006). doi:10.1007/3-540-34518-3_9

  7. Athanasis, N., Christophides, V., Kotzinos, D.: Generating on the fly queries for the semantic web: the ICS-FORTH graphical RQL interface (GRQL). In: Proceedings of the 3rd International Semantic Web Conference (ISWC 2004), LNCS, vol. 3298, pp. 486–501. Springer, Berlin (2004). doi:10.1007/978-3-540-30475-3_34

  8. Baeza-Yates, R., Ribeiro-Neto, B.: Modern Information Retrieval. Addison Wesley, Boston (1999)

    Google Scholar 

  9. Balkir, N.H., Ozsoyoglu, G., Ozsoyoglu, Z.M.: A graphical query language: VISUAL and its query processing. IEEE Trans. Knowl. Data Eng. 14(5), 955–978 (2002). doi:10.1109/TKDE.2002.1033767

    Article  Google Scholar 

  10. Barzdins, G., Liepins, E., Veilande, M., Zviedris, M.: Ontology enabled graphical database query tool for end-users. In: Proceedings of the 8th International Baltic Conference on Databases and Information Systems (DB&IS 2008), Frontiers in Artificial Intelligence and Applications, vol. 187, pp. 105–116. IOS Press, Amsterdam (2009). doi:10.3233/978-1-58603-939-4-105

  11. Barzdins, G., Rikacovs, S., Zviedris, M.: Graphical query language as SPARQL frontend. In: Proceedings of the 13th East-European Conference (ADBIS 2009), pp. 93–107 (2009)

  12. Batini, C., Catarci, T., Costabile, M.F., Levialdi, S.: Visual query systems: a taxonomy. In: Proceedings of the IFIP TC2/WG 2.6 2nd Working Conference on Visual Database Systems II, pp. 153–168. North-Holland Publishing Co., Amsterdam (1992)

  13. Bechhofer, S., Horrocks, I.: Driving user interfaces from FaCT. In: Proceedings of the International Workshop on Description Logics (DL 2000), CEUR Workshop Proceedings, vol. 33, pp. 45–54. http://CEUR-WS.org (2000)

  14. Bechhofer, S., Stevens, R., Ng, G., Jacoby, A., Goble, C.: Guiding the user: an ontology driven interface. In: Proceedings of the User Interfaces to Data Intensive Systems, pp. 158–161. IEEE Computer Society (1999). doi:10.1109/UIDIS.1999.791472

  15. Benzi, F., Maio, D., Rizzi, S.: VISIONARY: a viewpoint-based visual language for querying relational databases. J. Vis. Lang. Comput. 10(2), 117–145 (1999). doi:10.1006/jvlc.1998.0102

    Article  Google Scholar 

  16. Berners-Lee, T., Chen, Y., Chilton, L., Connolly, D., Dhanaraj, R., Hollenbach, J., Lerer, A., Sheets, D.: Tabulator: exploring and analyzing linked data on the semantic web. In: Proceedings of the 3rd International Semantic Web User Interaction Workshop (SWUI 2006) (2006)

  17. Berners-Lee, T., Hendler, J., Lassila, O.: The Semantic Web—a new form of Web content that is meaningful to computers will unleash a revolution of new possibilities. Sci. Am. 284(5), 34–43 (2001)

    Article  Google Scholar 

  18. Beshers, C., Feiner, S.: Auto visual: rule-based design of interactive multivariate visualizations. IEEE Comput. Graph. Appl. 13(4), 41–49 (1993). doi:10.1109/38.219450

    Article  Google Scholar 

  19. Besnard, P., Cordier, M.O., Moinard, Y.: Ontology-based inference for causal explanation. Integr. Comput. Aided Eng. 15(4), 351–367 (2008)

    Google Scholar 

  20. Bettini, C., Brdiczka, O., Henricksen, K., Indulska, J., Nicklas, D., Ranganathan, A., Riboni, D.: A survey of context modelling and reasoning techniques. Pervasive Mob. Comput. 6(2), 161–180 (2010). doi:10.1016/j.pmcj.2009.06.002

    Article  Google Scholar 

  21. Bevan, N., Macleod, M.: Usability measurement in context. Behav. Inf. Technol. 13(1–2), 132–145 (1994). doi:10.1080/01449299408914592

    Article  Google Scholar 

  22. Bizer, C., Heath, T., Berners-Lee, T.: Linked data—the story so far. Int. J. Semant. Web Inf. Syst. 5(3), 1–22 (2009). doi:10.4018/jswis.2009081901

    Article  Google Scholar 

  23. Bobed, C., Esteban, G., Mena, E.: Enabling keyword search on linked data repositories: an ontology-based approach. Int. J. Knowl. Based Intell. Eng. Syst. 17(1), 67–77 (2013). doi:10.3233/KES-130255

    Article  Google Scholar 

  24. Boley, H., Kifer, M., Pătrânjan, P.L., Polleres, A.: Rule interchange on the Web. In: Proceedings of the 3rd International Summer School Conference on Reasoning Web (RW 2007), LNCS, vol. 4636, pp. 269–309. Springer, Berlin (2007). doi:10.1007/978-3-540-74615-7_5

  25. Borst, W.N.: Construction of Engineering Ontologies. Ph.D. thesis, University of Twente, Enschede (1997)

  26. Braga, D., Campi, A., Ceri, S.: XQBE (XQuery By Example): a visual interface to the standard XML query language. ACM Trans. Database Syst. 30(2), 398–443 (2005). doi:10.1145/1071610.1071613

    Article  Google Scholar 

  27. Brunetti, J.M., Garcia, R., Auer, S.: From overview to facets and pivoting for interactive exploration of semantic web data. Int. J. Semant. Web Inf. Syst. 9(1), 1–20 (2013). doi:10.4018/jswis.2013010101

    Article  Google Scholar 

  28. Brunk, S., Heim, P.: tFacet: hierarchical faceted exploration of semantic data using well-known interaction concepts. In: Proceedings of the International Workshop on Data-Centric Interactions on the Web (DCI 2011), CEUR Workshop Proceedings, vol. 817, pp. 31–36. http://CEUR-WS.org (2011)

  29. Brusilovsky, P., Kobsa, A., Nejdl, W. (eds.): The Adaptive Web: Methods and Strategies of Web Personalization. Springer, Berlin (2007)

    Google Scholar 

  30. Bruza, P.D., van der Weide, T.P.: Stratified hypermedia structures for information disclosure. Comput. J. 35(3), 208–220 (1992). doi:10.1093/comjnl/35.3.208

    Article  MATH  Google Scholar 

  31. Burnett, M.M.: Visual programming. In: Webster, J.G. (ed.) Wiley Encyclopedia of Electrical and Electronics Engineering. Wiley, New York (1999). doi:10.1002/047134608X.W1707

  32. Burnett, M.M., Baker, M.J.: A classification system for visual programming languages. J. Vis. Lang. Comput. 5(3), 287–300 (1994). doi:10.1006/jvlc.1994.1015

    Article  Google Scholar 

  33. Cali, A., Gottlob, G., Lukasiewicz, T.: A general datalog-based framework for tractable query answering over ontologies. Web Semant. Sci. Serv. Agents World Wide Web 14, 57–83 (2012). doi:10.1016/j.websem.2012.03.001

    Article  Google Scholar 

  34. Campbell, L.J., Halpin, T.A., Proper, H.A.: Conceptual schemas with abstractions making flat conceptual schemas more comprehensible. Data Knowl. Eng. 20(1), 39–85 (1996). doi:10.1016/0169-023X(96)00005-5

    Article  MATH  Google Scholar 

  35. Cassino, R., Tucci, M.: Developing usable web interfaces with the aid of automatic verification of their formal specification. J. Vis. Lang. Comput. 22(2), 140–149 (2011). doi:10.1016/j.jvlc.2010.12.001

    Article  Google Scholar 

  36. Catarci, T.: What happened when database researchers met usability. Inf. Syst. 25(3), 177–212 (2000). doi:10.1016/S0306-4379(00)00015-6

    Article  Google Scholar 

  37. Catarci, T., Costabile, M.F., Levialdi, S., Batini, C.: Visual query systems for databases: a survey. J. Vis. Lang. Comput. 8(2), 215–260 (1997). doi:10.1006/jvlc.1997.0037

    Article  Google Scholar 

  38. Catarci, T., Dongilli, P., Di Mascio, T., Franconi, E., Santucci, G., Tessaris, S.: An ontology based visual tool for query formulation support. In: Proceedings of the 16th Eureopean Conference on Artificial Intelligence (ECAI 2004), Frontiers in Artificial Intelligence and Applications, vol. 110, pp. 308–312. IOS Press, Amsterdam (2004)

  39. Certo, L., Galvao, T., Borges, J.: Time automaton: a visual mechanism for temporal querying. J. Vis. Lang. Comput. 24(1), 24–36 (2013). doi:10.1016/j.jvlc.2012.10.001

    Article  Google Scholar 

  40. Chandra, A.K., Merlin, P.M.: Optimal implementation of conjunctive queries in relational data bases. In: Proceedings of the 9th annual ACM symposium on theory of computing (STOC 1977), pp. 77–90. ACM (1977). doi:10.1145/800105.803397

  41. Chen, P.K., Chen, G.D., Liu, B.J.: HVQS: the hierarchical visual query system for databases. J. Vis. Lang. Comput. 11(1), 1–26 (2000). doi:10.1006/jvlc.1999.0140

    Article  Google Scholar 

  42. Chin, J.P., Diehl, V.A., Norman, K.L.: Development of an instrument measuring user satisfaction of the human–computer interface. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI 1988), pp. 213–218. ACM, New York (1988). doi:10.1145/57167.57203

  43. Cinque, L., Levialdi, S., Ferloni, F.: An expert visual query system. J. Vis. Lang. Comput. 2(2), 101–113 (1991). doi:10.1016/S1045-926X(05)80025-4

    Article  Google Scholar 

  44. Civili, C., Console, M., De Giacomo, G., Lembo, D., Lenzerini, M., Lepore, L., Mancini, R., Poggi, A., Rosati, R., Ruzzi, M., Santarelli, V., Savo, D.F.: Mastro studio: managing ontology-based data access applications. Proc. VLDB Endow. 6(12), 1314–1317 (2013)

    Article  Google Scholar 

  45. Claussen, J., Kemper, A., Moerkotte, G., Peithner, K., Steinbrunn, M.: Optimization and evaluation of disjunctive queries. IEEE Trans. Knowl. Data Eng. 12(2), 238–260 (2000). doi:10.1109/69.842265

    Article  Google Scholar 

  46. Codd, E.F.: A relational model of data for large shared databanks. Commun. ACM 13(6), 377–387 (1970). doi:10.1145/362384.362685

    Article  MATH  Google Scholar 

  47. Codd, E.F.: Relational completeness of data base sublanguages. In: Randall, J. (ed.) Data Base Systems, Courant Computer Science Symposia Series, vol. 6, pp. 65–98. Prentice-Hall, Englewood Cliffs (1972)

    Google Scholar 

  48. Codd, E.F.: Extending the database relational model to capture more meaning. ACM Trans. Database Syst. 4(4), 397–434 (1979). doi:10.1145/320107.320109

    Article  Google Scholar 

  49. Coutaz, J., Crowley, J.L., Dobson, S., Garlan, D.: Context is key. Commun. ACM 48(3), 49–53 (2005). doi:10.1145/1047671.1047703

    Article  Google Scholar 

  50. Cuff, R.N.: On casual users. Int. J. Man Mach. Stud. 12(2), 163–187 (1980). doi:10.1016/S0020-7373(80)80016-2

    Article  Google Scholar 

  51. Dadzie, A.S., Rowe, M.: Approaches to visualising linked data: a survey. Semant. Web 2(2), 89–124 (2011). doi:10.3233/SW-2011-0037

    Google Scholar 

  52. Damljanovic, D., Agatonovic, M., Cunningham, H., Bontcheva, K.: Improving habitability of natural language interfaces for querying ontologies with feedback and clarification dialogues. Web Semant. Sci. Serv. Agents World Wide Web 19, 1–21 (2013). doi:10.1016/j.websem.2013.02.002

    Article  Google Scholar 

  53. Deutsch, A., Marcus, M., Sui, L., Vianu, V., Zhou, D.: A verifier for interactive, data-driven web applications. In: Proceedings of the 2005 ACM SIGMOD International Conference on Management of Data (SIGMOD 2005), pp. 539–550. ACM, New York (2005). doi:10.1145/1066157.1066219

  54. Dey, A.K.: Understanding and using context. Pers. Ubiquit. Comput. 5(1), 4–7 (2001). doi:10.1007/s007790170019

    Article  Google Scholar 

  55. Dividino, R., Groner, G.: Which of the following SPARQL queries are similar? Why? In: Linked Data for Information Extraction (LD4IE 2013), CEUR Workshop Proceedings, vol. 1057. http://CEUR-WS.org (2013)

  56. Doan, K., Plaisant, C., Shneiderman, B.: Query previews in networked information systems. In: Proceedings of the 3rd International Forum on Research and Technology Advances in Digital Libraries (ADL 1996), pp. 120–129. IEEE Computer Society (1996)

  57. D’Ulizia, A., Ferri, F., Grifoni, P.: Moving GeoPQL: a pictorial language towards spatio-temporal queries. Geoinformatica 16(2), 357–389 (2012). doi:10.1007/s10707-011-0135-6

    Article  Google Scholar 

  58. Eiter, T., Ianni, G., Lukasiewicz, T., Schindlauer, R., Tompits, H.: Combining answer set programming with description logics for the Semantic Web. Artif. Intell. 172(12–13), 1495–1539 (2008). doi:10.1016/j.artint.2008.04.002

    Article  MathSciNet  MATH  Google Scholar 

  59. Elmasri, R., Navathe, S.B.: Database Systems: Models, Languages, Design and Application Programming, 6th edn. Pearson Global Edition (2011)

  60. Endres-Niggemeyer, B.: The mashup ecosystem. In: Endres-Niggemeyer, B. (ed.) Semantic mashups, pp. 1–50. Springer (2013). doi:10.1007/978-3-642-36403-7_1

  61. Epstein, R.G.: The TableTalk query language. J. Vis. Lang. Comput. 2, 115–141 (1991). doi:10.1016/S1045-926X(05)80026-6

    Article  Google Scholar 

  62. Erwig, M.: Xing: a visual XML query language. J. Vis. Lang. Comput. 14(1), 5–45 (2003). doi:10.1016/S1045-926X(02)00074-5

    Article  Google Scholar 

  63. Fadhil, A., Haarslev, V.: GLOO: a graphical query language for OWL ontologies. In: Proceedings of the OWL: Experiences and Directions (OWLED 2006), CEUR Workshop Proceedings, vol. 216. http://CEUR-WS.org (2006)

  64. Fonseca, F., Martin, J.: Learning the differences between ontologies and conceptual schemas through ontology-driven information systems. J. Assoc. Inf. Syst. 8(2), 129–142 (2007)

    Google Scholar 

  65. Friedhoff, R.M., Benzon, W.: Visualization: The Second Computer Revolution. Harry N. Abrahams Inc, New York (1989)

    Google Scholar 

  66. Gaines, B.R.: Designing visual languages for description logics. J. Logic Lang. Inform. 18(2), 217–250 (2009). doi:10.1007/s10849-008-9078-1

    Article  Google Scholar 

  67. Gallud, J.A., Lozano, M.D., Vanderdonckt, J.: Distributed user interfaces: usability and collaboration. Int. J. Hum. Comput Stud. 72(1), 44 (2014). doi:10.1016/j.ijhcs.2013.10.006

    Article  Google Scholar 

  68. Gersh, J., Lewis, B., Montemayor, J., Piatko, C., Turner, R.: Supporting insight-based information exploration in intelligence analysis. Commun. ACM 49(4), 63–68 (2006). doi:10.1145/1121949.1121984

    Article  Google Scholar 

  69. Giese, M., Calvanese, D., Horrocks, I., Ioannidis, Y., Klappi, H., Koubarakis, M., Lenzerini, M., Moller, R., Ozcep, O., Rodriguez Muro, M., Rosati, R., Schlatte, R., Soylu, A., Waaler, A.: Scalable end-user access to big data. In: Rajendra, A. (ed.) Big Data Computing. Chapman and Hall/CRC, London (2013)

  70. Giese, M., Soylu, A., Vega-Gorgojo, G., Waaler, A., Haase, P., Jimenez-Ruiz, E., Lanti, D., Rezk, M., Xiao, G., Ozcep, O., Rosati, R.: Optique: zooming in on big data. Computer 48(3), 60–67 (2015). doi:10.1109/MC.2015.82

    Article  Google Scholar 

  71. Glimm, B., Horrocks, I., Lutz, C., Sattler, U.: Conjunctive query answering for the description logic SHIQ. J. Artif. Intell. Res. 31(1), 157–204 (2008)

    MathSciNet  MATH  Google Scholar 

  72. Gomez-Perez, A., Fernandez-Lopez, M., Corcho, O.: Ontological Engineering. Advanced Information and Knowledge Processing. Springer, Berlin (2004)

    Google Scholar 

  73. Grau, B.C., Horrocks, I., Motik, B., Parsia, B., Patel-Schneider, P., Sattler, U.: Services and agents on the world wide web. Web Semant. Sci. Serv. Agents World Wide Web 6(4), 309–322 (2008). doi:10.1016/j.websem.2008.05.001

    Article  Google Scholar 

  74. Gruber, T.R.: A translation approach to portable ontology specifications. Knowl. Acquis. 5(2), 199–221 (1993). doi:10.1006/knac.1993.1008

    Article  Google Scholar 

  75. Guarino, N.: Formal ontology and information systems. In: Proceedings of the 1st International Conference on Formal Ontology in Information Systems (FOIS 1998). IOS Press, Amsterdam (1998)

  76. Haag, F., Lohmann, S., Siek, S., Ertl, T.: QueryVOWL: a visual query notation for linked data. In: The Semantic Web: ESWC 2015 Satellite Events, LNCS, vol. 9341, pp. 387–402. Springer, Berlin (2015). doi:10.1007/978-3-319-25639-9_51

  77. Halpin, T., Morgan, T.: Information Modeling and Relational Databases, 2nd edn. Morgan Kaufmann, San Francisco (2008)

    Google Scholar 

  78. van Ham, F., van Wijk, J.J.: Beamtrees: compact visualization of large hierarchies. Information Visualization 2(1), 31–39 (2003). doi:10.1057/palgrave.ivs.9500036

    Article  Google Scholar 

  79. Harth, A.: VisiNav: a system for visual search and navigation on web data. Web Semant. Sci. Serv. Agents World Wide Web 8(4), 348–354 (2010). doi:10.1016/j.websem.2010.08.001

    Article  Google Scholar 

  80. Harth, A., Kruk, S.R., Decker, S.: Graphical representation of RDF queries. In: Proceedings of the 15th International Conference on World Wide Web (WWW 2006), pp. 859–860. ACM, New York (2006). doi:10.1145/1135777.1135914

  81. Hearst, M.A.: Search User Interfaces. Cambridge University Press, Cambridge (2009)

    Book  Google Scholar 

  82. Heim, P., Ziegler, J.: Faceted visual exploration of semantic data. In: Proceedings of the 2nd IFIP WG 13.7 Conference on Human-computer Interaction and Visualization (HCIV 2009), LNCS, vol. 6431, pp. 58–75. Springer, Berlin (2011). doi:10.1007/978-3-642-19641-6_5

  83. Henderson-Sellers, B.: Bridging metamodels and ontologies in software engineering. J. Syst. Softw. 84(2), 301–313 (2011). doi:10.1016/j.jss.2010.10.025

    Article  Google Scholar 

  84. Hogenboom, F., Milea, V., Frasincar, F., Kaymak, U.: RDF-GL: A SPARQL-based graphical query language for RDF. In: Chbeir, R., Badr, Y., Abraham, A., Hassanien, A.E. (eds.) Emergent Web Intelligence: Advanced Information Retrieval, Advanced Information and Knowledge Processing, pp. 87–116. Springer, Berlin (2010). doi:10.1007/978-1-84996-074-8_4

  85. Howe, D., Costanzo, M., Fey, P., Gojobori, T., Hannick, L., Hide, W., Hill, D.P., Kania, R., Schaeffer, M., St Pierre, S., Twigger, S., White, O., Rhee, S.Y.: Big data: the future of biocuration. Nature 455(7209), 47–50 (2008). doi:10.1038/455047a

    Article  Google Scholar 

  86. Huynh, D.F., Karger, D.R.: Parallax and companion: set-based browsing for the data web (2009). http://davidhuynh.net/media/papers/2009/www2009-parallax.pdf

  87. Huynh, D.F., Karger, D.R., Miller, R.C.: Exhibit: lightweight structured data publishing. In: Proceedings of the 16th International Conference on World Wide Web (WWW 2007), pp. 737–746. ACM, New York (2007). doi:10.1145/1242572.1242672

  88. Ingwersen, P., Järvelin, K.: The Turn: Integration of Information Seeking and Retrieval in Context. Springer, New York (2005)

    MATH  Google Scholar 

  89. Jagadish, H.V., Chapman, A., Elkiss, A., Jayapandian, M., Li, Y., Nandi, A., Yu, C.: Making database systems usable. In: Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD 2007), pp. 13–24. ACM, New York (2007). doi:10.1145/1247480.1247483

  90. Jimenez-Ruiz, E., Grau, B.C., Sattler, U., Schneider, T., Berlanga, R.: Safe and economic re-use of ontologies: a logic-based methodology and tool support. In: Proceedings of the 5th European Semantic Web Conference (ESWC 2008), LNCS, vol. 5021, pp. 185–199. Springer, New York (2008). doi:10.1007/978-3-540-68234-9_16

  91. Jimeno-Yepes, A., Jiménez-Ruiz, E., Berlanga-Llavori, R., Rebholz-Schuhmann, D.: Reuse of terminological resources for efficient ontological engineering in life sciences. BMC Bioinform. 10(10), 1–13 (2009). doi:10.1186/1471-2105-10-S10-S4

    Google Scholar 

  92. Kapetanios, E., Baer, D., Groenewoud, P.: Simplifying syntactic and semantic parsing of NL-based queries in advanced application domains. Data Knowl. Eng. 55(1), 38–58 (2005). doi:10.1016/j.datak.2004.11.008

    Article  Google Scholar 

  93. Katifori, A., Halatsis, C., Lepouras, G., Vassilakis, C., Giannopoulou, E.: Ontology visualization methods—a survey. ACM Comput. Surv. 39(4), 10:1–10:43 (2007). doi:10.1145/1287620.1287621

    Article  Google Scholar 

  94. Kaufmann, E., Bernstein, A.: Evaluating the usability of natural language query languages and interfaces to Semantic Web knowledge bases. Web Semant. Sci. Serv. Agents World Wide Web 8(4), 377–393 (2010). doi:10.1016/j.websem.2010.06.001

    Article  Google Scholar 

  95. Kawash, J.: Complex quantification in structured query language (SQL): a tutorial using relational calculus. J. Comput. Math. Sci. Teach. 23(2), 169–190 (2004)

    Google Scholar 

  96. Kharlamov, E., Jiménez-Ruiz, E., Zheleznyakov, D., Bilidas, D., Giese, M., Haase, P., Horrocks, I., Kllapi, H., Koubarakis, M., Özçep, O., Rodríguez-Muro, M., Rosati, R., Schmidt, M., Schlatte, R., Soylu, A., Waaler, A.: Optique: towards OBDA systems for industry. In: Proceedings of the Semantic Web: ESWC 2013 Satellite Events, LNCS, vol. 7955, pp. 125–140. Springer, New York (2013). doi:10.1007/978-3-642-41242-4_11

  97. Khoussainova, N., Kwon, Y., Liao, W.T., Balazinska, M., Gatterbauer, W., Suciu, D.: Session-based browsing for more effective query reuse. In: Proceedings of the 23rd International Conference on Scientific and Statistical Database Management (SSDBM 2011), LNCS, vol. 6809, pp. 583–585. Springer (2011). doi:10.1007/978-3-642-22351-8_47

  98. Kifer, M., Lausen, G., Wu, J.: Logical foundations of object-oriented and frame-based languages. J. ACM 42(4), 741–843 (1995). doi:10.1145/210332.210335

    Article  MathSciNet  MATH  Google Scholar 

  99. Knublauch, H., Fergerson, R.W., Noy, N.F., Musen, M.A.: The Protégé OWL plugin: an open development environment for Semantic Web applications. In: The Proceedings of the 3rd International Semantic Web Conference (ISWC 2004), LNCS, vol. 3298, pp. 229–243. Springer, New York (2004). doi:10.1007/978-3-540-30475-3_17

  100. Kobilarov, G., Dickinson, I.: Humboldt: exploring linked data. In: Proceedings of the Linked Data on the Web Workshop (2008)

  101. Kogalovsky, M.R.: Ontology-based data access systems. Program. Comput. Softw. 38(4), 167–182 (2012). doi:10.1134/S0361768812040032

    Article  MathSciNet  Google Scholar 

  102. Kolomiyets, O., Moens, M.F.: A survey on question answering technology from an information retrieval perspective. Inf. Sci. 181(24), 5412–5434 (2011). doi:10.1016/j.ins.2011.07.047

    Article  MathSciNet  Google Scholar 

  103. Kondylakis, H., Plexousakis, D.: Ontology evolution without tears. Web Semant. Sci. Serv. Agents World Wide Web 19, 42–58 (2013). doi:10.1016/j.websem.2013.01.001

    Article  Google Scholar 

  104. Konstan, J.A., Riedl, J.: Recommender systems: from algorithms to user experience. User Model. User Adapt. Interact. 22(1–2), 101–123 (2012). doi:10.1007/s11257-011-9112-x

    Article  Google Scholar 

  105. Koutrika, G., Zadeh, Z.M., Garcia-Molina, H.: Data clouds: summarizing keyword search results over structured data. In: Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology (EDBT 2009), pp. 391–402. ACM, New York (2009). doi:10.1145/1516360.1516406

  106. Krivov, S., Williams, R., Villa, F.: GrOWL: a tool for visualization and editing of OWL ontologies. Web Semant. Sci. Serv. Agents World Wide Web 5(2), 54–57 (2007). doi:10.1016/j.websem.2007.03.005

    Article  Google Scholar 

  107. Laney, D.: 3D Data Management: Controlling Data Volume. Velocity and Variety. Tech. rep, META Group (2001)

  108. Latapy, M., Magnienb, C., Del Vecchioc, N.: Basic notions for the analysis of large two-mode networks. Soc. Netw. 30(1), 31–48 (2008). doi:10.1016/j.socnet.2007.04.006

    Article  Google Scholar 

  109. Lederman, S., Klatzky, R.: Haptic perception: a tutorial. Atten. Percept. Psychophys. 71(7), 1439–1459 (2009). doi:10.3758/APP.71.7.1439

    Article  Google Scholar 

  110. Leone, S., Geel, M., Mueller, C., Norrie, M.C.: Exploiting tag clouds for database browsing and querying. In: Proceedings of the Information Systems Evolution—CAiSE Forum 2010, LNBIP, vol. 72, pp. 15–28. Springer, New York (2011). doi:10.1007/978-3-642-17722-4_2

  111. Levesque, H.J., Brachman, R.J.: A fundamental tradeoff in knowledge representation and reasoning. In: Brachman, R.J., Levesque, H.J. (eds.) Readings in Knowledge Representation, pp. 41–70. Morgan Kaufmann, Los Altos (1985)

    Google Scholar 

  112. Lieberman, H., Paterno, F., Wulf, V. (eds.): End User Development, Human-Computer Interaction Series, vol. 9. Springer, New York (2006)

  113. Lindgaard, G., Dudek, C.: What is this evasive beast we call user satisfaction? Interact. Comput. 15(3), 429–452 (2003). doi:10.1016/S0953-5438(02)00063-2

    Article  Google Scholar 

  114. Lohse, G.L., Biolsi, K., Walker, N., Rueter, H.H.: A classification of visual representations. Commun. ACM 37(12), 36–49 (1994). doi:10.1145/198366.198376

    Article  Google Scholar 

  115. Lopez, V., Unger, C., Cimiano, P., Motta, E.: Evaluating question answering over linked data. Web Semant. Sci. Serv. Agents World Wide Web 21, 3–13 (2013)

    Article  Google Scholar 

  116. Mackinlay, J.: Automating the design of graphical presentations of relational information. ACM Trans. Graph. 5(2), 110–141 (1986). doi:10.1145/22949.22950

    Article  Google Scholar 

  117. Madden, S.: From databases to big data. IEEE Internet Comput. 16(3), 4–6 (2012). doi:10.1109/MIC.2012.50

    Article  Google Scholar 

  118. Marchionini, G.: Exploratory search: from finding to understanding. Commun. ACM 49(4), 41–46 (2006). doi:10.1145/1121949.1121979

    Article  Google Scholar 

  119. Marchionini, G., White, R.: Find what you need, understand what you find. Int. J. Hum. Comput. Interact. 23(3), 205–237 (2007). doi:10.1080/10447310701702352

    Article  Google Scholar 

  120. Martinez-Cruz, C., Blanco, I.J., Amparo Vila, M.: Ontologies versus relational databases: are they so different? A comparison. Artif. Intell. Rev. 38(4), 271–290 (2012). doi:10.1007/s10462-011-9251-9

    Article  Google Scholar 

  121. McAfee, A., Brynjolfsson, E.: Big data: the management revolution. Harvard Bus. Rev. 90(10), 60–68 (2012)

    Google Scholar 

  122. Mendes, P.N., Mcknight, B., Sheth, A.P., Kissinger, J.C.: TcruziKB: enabling complex queries for genomic data exploration. In: Proceedings of the IEEE International Conference on Semantic Computing, pp. 432–439. IEEE (2008). doi:10.1109/ICSC.2008.93

  123. Minker, J.: Logic and databases—fast, present, and future. AI Mag. 18(3), 21–47 (1997)

    Google Scholar 

  124. Motik, B., Grau, B.C., Horrocks, I., Wu, Z., Fokoue, A., Lutz, C.: OWL 2 Web ontology language profiles. W3C Recommendation, W3C (2009). http://www.w3.org/TR/owl-profiles/

  125. Motik, B., Rosati, R.: Reconciling description logics and rules. J. ACM 57(5), 30:1–30:62 (2008). doi:10.1145/1754399.1754403

  126. Munir, K., Odeh, M., McClatchey, R.: Ontology-driven relational query formulation using the semantic and assertional capabilities of OWL-DL. Knowl. Based Syst. 35, 144–159 (2012). doi:10.1016/j.knosys.2012.04.020

    Article  Google Scholar 

  127. Nandi, A., Jagadish, H.V.: Assisted querying using instant–response interfaces. In: Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD 2007), pp. 1156–1158. ACM, New York (2007). doi:10.1145/1247480.1247640

  128. Nielsen, J.: Usability Engineering. Morgan Kaufmann, San Francisco (1993)

    MATH  Google Scholar 

  129. Nielsen, J.: Guerrilla HCI: using discount usability engineering to penetrate the intimidation barrier. In: Bias, R.G., Mayhew, D.J. (eds.) Cost-Justifying Usability, pp. 245–272. Academic Press Inc., Orlando (1994)

    Google Scholar 

  130. Norman, D.A., Draper, S.W. (eds.): User Centered System Design: New Perspectives on Human–Computer Interaction. L. Erlbaum Associates Inc., Hillsdale (1986)

    Google Scholar 

  131. Noy, N.F., McGuinness, D.L.: Ontology development 101: a guide to creating your first ontology. Technical Report SMI-2001-0880, Stanford Medical Informatics (2001)

  132. Nunamaker, J.F., Briggs, R.O., de Vreede, G.J.: From information technology to value creation technology. In: Information Technology and the Future Enterprise: New Models for Managers, pp. 102–124. Prentice-Hall, New York (2001)

  133. Philippi, S.: Model driven generation and testing of object-relational mappings. J. Syst. Softw. 77(2), 193–207 (2005). doi:10.1016/j.jss.2004.07.252

    Article  Google Scholar 

  134. Pirolli, P., Stuart, C.: The sensemaking process and leverage points for analyst technology as identified through cognitive task analysis. In: Proceedings of the 2005 International Conference on Intelligence Analysis (2005)

  135. Plaisant, C., Grosjean, J., Bederson, B.B.: SpaceTree: supporting exploration in large node link tree, design evolution and empirical evaluation. In: Proceedings of the IEEE Symposium on Information Visualization (InfoVis 2002), pp. 57–64. IEEE Computer Society (2002). doi:10.1109/INFVIS.2002.1173148

  136. Pollitt, A.S., Smith, M.P., Treglown, M., Braekevelt, P.: View-based searching systems—progress towards effective disintermediation. In: The Proceedings of the Online Information, pp. 433–441 (1996)

  137. Popov, I.O., Schraefel, M.C., Hall, W., Shadbolt, N.: Connecting the dots: a multi-pivot approach to data exploration. In: Proceedings of the 10th International Semantic Web Conference (ISWC 2011), LNCS, vol. 7031, pp. 553–568. Springer, New York (2011). doi:10.1007/978-3-642-25073-6_35

  138. Priyatna, F., Corcho, O., Sequeda, J.: Formalisation and Experiences of R2RML-based SPARQL to SQL query translation using Morph. In: Proceedings of the 23rd International Conference on World Wide Web Conference (WWW 2014) (2014)

  139. van Rijsbergen, C.J.: Information Retrieval, 2 edn. Butterworth-Heinemann (1979)

  140. Robertson, P.K.: A methodology for choosing data representations. IEEE Comput. Graph. Appl. 11(3), 56–67 (1991). doi:10.1109/38.79454

    Article  Google Scholar 

  141. Rodriguez-Muro, M., Calvanese, D.: High performance query answering over DL-lite ontologies. In: Proceedings of the Principles of Knowledge Representation and Reasoning (KR 2012), pp. 308–318. AAAI Press, Palo Alto (2012)

  142. Rodriguez-Muro, M., Calvanese, D.: Quest, a system for ontology based data access. In: Proceedings of the 9th OWL: Experiences and Directions Workshop (OWLED 2012), CEUR Workshop Proceedings, vol. 849. http://CEUR-WS.org (2012)

  143. Rodriguez-Muro, M., Kontchakov, R., Zakharyaschev, M.: Ontology-based data access: ontop of databases. In: Proceedings of the 12th International Semantic Web Conference (ISWC 2013), LNCS, vol. 8218, pp. 558–573. Springer, New York (2013). doi:10.1007/978-3-642-41335-3_35

  144. Rodriguez-Muro, M., Lubyte, L., Calvanese, D.: Realizing ontology based data access: a plug-in for Protégé. In: Proceedings of the IEEE 24th International Conference on Data Engineering Workshop (ICDEW 2008), pp. 353–356. IEEE (2008). doi:10.1109/ICDEW.2008.4498333

  145. Ruiz, F., Hilera, J.R.: Using ontologies in software engineering and technology. In: Calero, C., Ruiz, F., Piattini, M. (eds.) Ontologies for Software Engineering and Software Technology, pp. 49–102. Springer, New York (2006). doi:10.1007/3-540-34518-3_2

  146. Salehie, M., Tahvildari, L.: Self-adaptive software: landscape and research challenges. ACM Trans. Auton. Adapt. Syst. 4(2), 14:1–14:42 (2009). doi:10.1145/1516533.1516538

    Article  Google Scholar 

  147. Schraefel, M.C., Wilson, M., Russell, A., Smith, D.A.: mSpace: improving information access to multimedia domains with multimodal exploratory search. Commun. ACM 49(4), 47–49 (2006). doi:10.1145/1121949.1121980

    Article  Google Scholar 

  148. Segev, A., Sheng, Q.Z.: Bootstrapping ontologies for web services. IEEE Trans. Serv. Comput. 5(1), 33–44 (2012). doi:10.1109/TSC.2010.51

    Article  Google Scholar 

  149. Sequeda, J.F., Miranker, D.P.: Ultrawrap: SPARQL execution on relational data. Web Semant. Sci. Serv. Agents World Wide Web 22, 19–39 (2013). doi:10.1016/j.websem.2013.08.002

    Article  Google Scholar 

  150. Shneiderman, B.: Direct manipulation: a step beyond programming languages. Computer 16(8), 57–69 (1983). doi:10.1109/MC.1983.1654471

    Article  Google Scholar 

  151. Shneiderman, B.: Dynamic queries for visual information seeking. IEEE Softw. 11(6), 70–77 (1994). doi:10.1109/52.329404

    Article  Google Scholar 

  152. Shneiderman, B.: The eyes have it: a task by data type taxonomy for information visualizations. In: Proceedings of the IEEE Symposium on Visual Languages (VL 1996), pp. 336–343. IEEE Computer Society (1996). doi:10.1109/VL.1996.545307

  153. Siau, K.: A visual object-relationship query language for user–database interaction. Telemat. Inform. 15(1–2), 103–119 (1998)

    Article  Google Scholar 

  154. Siau, K.L., Chan, H.C., Wei, K.K.: Effects of query complexity and learning on novice user query performance with conceptual and logical database interfaces. IEEE Trans. Syst. Man Cybern. Part A Syst. Hum. 34(2), 276–281 (2004). doi:10.1109/TSMCA.2003.820581

    Article  Google Scholar 

  155. Smart, P.R., Russell, A., Braines, D., Kalfoglou, Y., Bao, J., Shadbolt, N.: A visual approach to semantic query design using a web-based graphical query designer. In: Proceedings of the 16th International Conference on Knowledge Engineering: Practice and Patterns (EKAW 2008), LNCS, vol. 5268, pp. 275–291. Springer, New York (2008). doi:10.1007/978-3-540-87696-0_25

  156. Soylu, A., De Causmaecker, P., Desmet, P.: Context and adaptivity in pervasive computing environments: links with software engineering and ontological engineering. J. Softw. 4(9), 992–1013 (2009). doi:10.4304/jsw.4.9.992-1013

    Article  Google Scholar 

  157. Soylu, A., De Causmaecker, P., Preuveneers, D., Berbers, Y., Desmet, P.: Formal modelling, knowledge representation and reasoning for design and development of user-centric pervasive software: a meta-review. Int. J. Metadata Semant. Ontol. 6(2), 96–125 (2011). doi:10.1504/IJMSO.2011.046595

    Article  Google Scholar 

  158. Soylu, A., Giese, M.: Qualifying ontology-based visual query formulation. In: Proceedings of the Flexible Query Answering Systems (FQAS 2015), Advances in Intelligent Systems and Computing, vol. 400, pp. 243–255. Springer, New York (2015). doi:10.1007/978-3-319-26154-6_19

  159. Soylu, A., Giese, M., Jimenez-Ruiz, E., Kharlamov, E., Zheleznyakov, D., Horrocks, I.: Towards exploiting query history for adaptive ontology-based visual query formulation. In: Proceedings of the 8th Metadata and Semantics Research Conference (MTSR 2014), CCIS, pp. 107–119. Springer, New York (2014). doi:10.1007/978-3-319-13674-5_11

  160. Soylu, A., Giese, M., Jimenez-Ruiz, E., Vega-Gorgojo, G., Horrocks, I.: Experiencing OptiqueVQS: a multi-paradigm and ontology-based visual query system for end users. Univ. Access Inf. Soc. 15(1), 129–152 (2016). doi:10.1007/s10209-015-0404-5

    Article  Google Scholar 

  161. Soylu, A., Kharlamov, E., Zheleznyakov, D., Jimenez-Ruiz, E., Giese, M., Horrocks, I.: Ontology-based visual query formulation: an industry experience. In: Proceedings of the 11th International Symposium on Visual Computing (ISVC 2015), LNCS, vol. 9474, pp. 842–854. Springer, New York (2015). doi:10.1007/978-3-319-27857-5_75

  162. Soylu, A., Modritscher, F., De Causmaecker, P.: Ubiquitous web navigation through harvesting embedded semantic data: a mobile scenario. Integr. Comput. Aided Eng. 19(1), 93–109 (2012). doi:10.3233/ICA-2012-0393

    Google Scholar 

  163. Soylu, A., Moedritscher, F., Wild, F., De Causmaecker, P., Desmet, P.: Mashups by orchestration and widget-based personal environments: key challenges, solution strategies, and an application. Program Electron. Libr. Inf. Syst. 46(4), 383–428 (2012). doi:10.1109/ICC.2010.5502398

    Article  Google Scholar 

  164. Spanos, D.E., Stavrou, P., Mitrou, N.: Bringing relational databases into the Semantic Web: a survey. Semant. Web 3(2), 169–209 (2012). doi:10.3233/SW-2011-0055

    Google Scholar 

  165. Spiekermann, S.: User Control in Ubiquitous Computing: Design Alternatives and User Acceptance. Shaker Verlag, Aachen (2008)

    Google Scholar 

  166. Staab, S., Studer, R. (eds.): Handbook on Ontologies. International Handbooks on Information Systems. Springer, Berlin (2009)

    Google Scholar 

  167. Stevens, R., Baker, P., Bechhofer, S., Ng, G., Jacoby, A., Paton, N.W., Goble, C.A., Brass, A.: TAMBIS: transparent access to multiple bioinformatics information sources. Bioinformatics 16(2), 184–186 (2000). doi:10.1093/bioinformatics/16.2.184

    Article  Google Scholar 

  168. Storrle, H.: VMQL: a visual language for ad-hoc model querying. J. Vis. Lang. Comput. 22(1), 3–29 (2011). doi:10.1016/j.jvlc.2010.11.004

    Article  Google Scholar 

  169. Studer, R., Benjamins, V.R., Fensel, D.: Knowledge engineering: principles and methods. Data Knowl. Eng. 25(1–2), 161–197 (1998). doi:10.1016/S0169-023X(97)00056-6

    Article  MATH  Google Scholar 

  170. Suh, B., Bederson, B.B.: OZONE: a zoomable interface for navigating ontology information. In: Proceedings of the Working Conference on Advanced Visual Interfaces (AVI 2002), pp. 139–143. ACM, New York (2002). doi:10.1145/1556262.1556284

  171. Ter Hofstede, A.H.M., Proper, H.A., Van Der Weide, T.P.: Query formulation as an information retrieval problem. Comput. J. 39(4), 255–274 (1996). doi:10.1093/comjnl/39.4.255

    Article  Google Scholar 

  172. Thompson, C.W., Ross, K.M., Tennant, H.R., Saenz, R.M.: Building usable menu-based natural language interfaces to databases. In: Proceedings of the 9th International Conference on Very Large Data Bases (VLDB 1983), pp. 43–55. Morgan Kaufmann Publishers Inc., Burlington (1983)

  173. Tran, T., Herzig, D.M., Ladwig, G.: SemSearchPro—using semantics throughout the search process. Web Semant. Sci. Serv. Agents World Wide Web 9(4), 349–364 (2011). doi:10.1016/j.websem.2011.08.004

    Article  Google Scholar 

  174. Tummarello, G., Cyganiak, R., Catasta, M., Danielczyk, S., Delbru, R., Decker, S.: Sig.ma: live views on the Web of Data. Web Semant. Sci. Serv. Agents World Wide Web 8(4), 355–364 (2010). doi:10.1016/j.websem.2010.08.003

    Article  Google Scholar 

  175. Tunkelang, D., Marchionini, G.: Faceted Search. Retrieval, and Services. Morgan and Claypool Publishers, Synthesis Lectures on Information Concepts (2009)

  176. Turk, M., Robertson, G.: Perceptual user interfaces (introduction). Commun. ACM 43(3), 32–34 (2000). doi:10.1145/330534.330535

    Article  Google Scholar 

  177. Uren, V., Lei, Y., Lopez, V., Liu, H., Motta, E., Giordanino, M.: The usability of semantic search tools: a review. Knowl. Eng. Rev. 22(4), 361–377 (2007). doi:10.1017/S0269888907001233

    Article  Google Scholar 

  178. Warschauer, M., Ahumada Newhart, V.: Broadening our concepts of universal access. Universal Access in the Information Society (to appear). doi:10.1007/s10209-015-0417-0

  179. Whang, K.Y., Ammann, A., Bolmarcich, A., Hanrahan, M., Hochgesang, G., Huang, K.T., Khorasani, A., Krishnamurthy, R., Sockut, G., Sweeney, P., Waddle, V., Zloof, M.: Office-by-example: an integrated office system and database manager. ACM Trans. Inf. Syst. 5(4), 393–427 (1987). doi:10.1145/42196.42200

    Article  Google Scholar 

  180. White, R.W., Kules, B., Drucker, S.M., Schraefel, M.C.: Supporting exploratory search. Commun. ACM 49(4), 37–39 (2006). doi:10.1145/1121949.1121978

    Article  Google Scholar 

  181. Wilson, M.L., Schraefel, M.C.: mSpace: what do numbers and totals mean in a flexible semantic browser. In: Proceedings of the 3rd International Semantic Web User Interaction Workshop (SWUI 2006) (2006)

  182. Wilson, M.L., Schraefel, M.C., White, R.W.: Evaluating advanced search interfaces using established information-seeking models. J. Am. Soc. Inf. Sci. Technol. 60(7), 1407–1422 (2009). doi:10.1002/asi.21080

    Article  Google Scholar 

  183. Yang, Y., Wu, X., Zhu, X.: Combining proactive and reactive predictions for data streams. In: Proceedings of the 11th ACM SIGKDD International Conference on Knowledge Discovery in Data Mining (KD 2005), pp. 710–715. ACM, New York (2005). doi:10.1145/1081870.1081961

  184. Yee, K.P., Swearingen, K., Li, K., Hearst, M.: Faceted metadata for image search and browsing. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI 2003), pp. 401–408. ACM, New York (2003). doi:10.1145/642611.642681

  185. Yen, M.Y.M., Scamell, R.W.: A human factors experimental comparison of SQL and QBE. IEEE Trans. Softw. Eng. 19(4), 390–409 (1993). doi:10.1109/32.223806

    Article  Google Scholar 

  186. Yu, C., Jagadish, H.V.: Schema summarization. In: Proceedings of the 32nd International Conference on Very Large Data Bases (VLDB 2006), pp. 319–330. VLDB Endowment (2006)

  187. Zhang, J., Marchionini, G.: Evaluation and evolution of a browse and search interface: relation Browser++. In: Proceedings of the 2005 National Conference on Digital Government Research (dg.o 2005), pp. 179–188. Digital Government Society of North America (2005)

  188. Zheng, K., Mei, Q., Hanauer, D.A.: Collaborative search in electronic health records. J. Am. Med. Inf. Assoc. 18(3), 282–291 (2011). doi:10.1136/amiajnl-2011-000009

    Article  Google Scholar 

  189. Zloof, M.M.: Query-by-example: a database language. IBM Syst. J. 16(4), 324–343 (1997). doi:10.1147/sj.164.0324

    Article  Google Scholar 

  190. Zviedris, M., Barzdins, G.: ViziQuer: a tool to explore and query SPARQL endpoints. In: Proceedings of the 8th Extended Semantic Web Conference (ESWC 2011), LNCS, vol. 6644, pp. 441–445. Springer, New York (2011). doi:10.1007/978-3-642-21064-8_31

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This research is funded by the Seventh Framework Program (FP7) of the European Commission under Grant Agreement 318338, “Optique”.

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Soylu, A., Giese, M., Jimenez-Ruiz, E. et al. Ontology-based end-user visual query formulation: Why, what, who, how, and which?. Univ Access Inf Soc 16, 435–467 (2017). https://doi.org/10.1007/s10209-016-0465-0

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