Skip to main content
SpringerLink
Log in

A Jigsaw-Based End-User Tool for the Development of Ontology-Based Knowledge Bases

  • Conference paper
  • First Online:
End-User Development (IS-EUD 2021)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 12724))

Included in the following conference series:

Abstract

Knowledge bases are used to store and centralize information on certain topics in a domain. Using a well-structured and machine-readable format is a prerequisite for any AI-based processing or reasoning. The use of semantic technologies (e.g., RDF, OWL) has the advantage that it allows to define the semantics of the information and supports advanced querying. However, using such technologies is a challenging task for subject matter experts from a domain such as life science who are, in general, not trained for this. This means that they need to rely on semantic technology experts to create their knowledge bases. However, these experts are usually IT-experts and they are, in turn, not trained in the subject matter, while knowledge of the domain is essential for the construction of a high-quality knowledge base. In this paper, we present an end-user development (EUD) tool that supports subject matter experts in the construction of ontology–based knowledge bases. The tool is using the jigsaw metaphor for hiding the technicalities of the semantic technology, as well as to guide the users in the process of creating a knowledge base. The approach and the tool is demonstrated for building a knowledge base in the toxicology domain. The tool has been evaluated by means of a preliminary user study with nine subject matter experts from this domain. All participants state that with a little practice they could become productive with our tool and actually use it to represent and manage their knowledge. The results of the evaluation resulted in valuable suggestions for improving the tool and highlighted the importance of well adapting the terminology to the target audience.

Financially supported by Vrije Universiteit Brussel and Cosmetics Europe and the European Chemical Industry Council (CEFIC).

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    https://developers.google.com/blockly.

  2. 2.

    Example Safety Evaluation Opinion: https://ec.europa.eu/health/scientific_commit- tees/consumer_safety/docs/sccs_o_199.pdf.

  3. 3.

    https://github.com/DataSciBurgoon/aop-ontology.

  4. 4.

    Due to the COVID-19 restrictions it was not possible to be physically present while the participant was performing the tasks.

  5. 5.

    https://uiuxtrend.com/pssuq-post-study-system-usability-questionnaire.

References

  1. Alobaidi, M., Malik, K.M., Hussain, M.: Automated ontology generation framework powered by linked biomedical ontologies for disease-drug domain. Comput. Methods Programs Biomed. 165, 117–128 (2018). https://doi.org/10.1016/j.cmpb.2018.08.010

    Article  Google Scholar 

  2. Antoniou, G., van Harmelen, F.: Web ontology language: OWL. In: Staab, S., Studer, R. (eds.) Handbook on Ontologies. International Handbooks on Information Systems, pp. 67–92. Springer, Heidelberg (2004). https://doi.org/10.1007/978-3-540-24750-0_4

    Chapter  Google Scholar 

  3. Baškarada, S.: How spreadsheet applications affect information quality. J. Comput. Inf. Syst. 51(3), 77–84 (2011)

    Google Scholar 

  4. Belghiat, A., Bourahla, M.: An approach based AToM3 for the generation of OWL ontologies from UML diagrams. Int. J. Comput. Appl. 41(3), 41–48 (2012)

    Google Scholar 

  5. Bernstein, A., Kaufmann, E.: GINO – a guided input natural language ontology editor. In: Cruz, I., et al. (eds.) ISWC 2006. LNCS, vol. 4273, pp. 144–157. Springer, Heidelberg (2006). https://doi.org/10.1007/11926078_11

    Chapter  Google Scholar 

  6. Bottoni, P., Ceriani, M.: SPARQL playground: a block programming tool to experiment with SPARQL. In: Proceedings of ISWC 2015, International Workshop on Visualizations and User Interfaces for Ontologies and Linked Data. Bethlehem, USA, October 2015

    Google Scholar 

  7. Boyles, R.R., Thessen, A.E., Waldrop, A., Haendel, M.A.: Ontology-based data integration for advancing toxicological knowledge. Curr. Opin. Toxicol. 16, 67–74 (2019). https://doi.org/10.1016/j.cotox.2019.05.005

    Article  Google Scholar 

  8. Brilhante, V.V.B.B., Macedo, G.T., Macedo, S.F.: Heuristic transformation of well-constructed conceptual maps into owl preliminary domain ontologies. In: Proceedings of IBERAMIA-SBIA-SBRN 2006, Workshop on Ontologies and Their Applications. Ribeirao Preto, Brazil, October 2006

    Google Scholar 

  9. Bruhn, J.G.: Beyond discipline: creating a culture for interdisciplinary research. Integr. Physiol. Behav. Sci. 30(4), 331–341 (1995). https://doi.org/10.1007/BF02691605

    Article  Google Scholar 

  10. Cahyani, D.E., Wasito, I.: Automatic ontology construction using text corpora and ontology design patterns (ODPs) in alzheimer’s disease. Jurnal Ilmu Komputer dan Informasi 10(2), 59–66 (2017). https://doi.org/10.21609/jiki.v10i2.374

    Article  Google Scholar 

  11. Chasseray, Y., Barthe-Delanoë, A.M., Négny, S., Le Lann, J.M.: A generic metamodel for data extraction and generic ontology population. J. Inf. Sci. (2021). https://doi.org/10.1177/0165551521989641

  12. Cimiano, P., Völker, J.: A framework for ontology learning and data-driven change discovery. In: Proceedings of NLDB 2005, International Conference on Applications of Natural Language to Information Systems, Alicante, Spain, June 2005. https://doi.org/10.1007/11428817_21

  13. Consortium, W.W.W., et al.: Resource Description Framework (RDF) http://www.w3.org.RDF/. Accessed 4 June 2008

  14. Corno, F., De. Russis, L., Monge Roffarello, A.: My IoT puzzle: debugging IF-THEN rules through the jigsaw metaphor. In: Malizia, A., Valtolina, S., Morch, A., Serrano, A., Stratton, A. (eds.) IS-EUD 2019. LNCS, vol. 11553, pp. 18–33. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-24781-2_2

    Chapter  Google Scholar 

  15. Danado, J., Paternò, F.: Puzzle: a mobile application development environment using a jigsaw metaphor. J. Vis. Lang. Comput. 25(4), 297–315 (2014). https://doi.org/10.1016/j.jvlc.2014.03.005

    Article  Google Scholar 

  16. Debruyne, C., Riggio, J., Gustafson, E., O’Sullivan, D., Vinken, M., Vanhaecke, T., De Troyer, O.: Facilitating data curation: a solution developed in the toxicology domain. In: Proceedings of ICSC 2020, International Conference on Semantic Computing, pp. 315–320, January 2020

    Google Scholar 

  17. Dobing, B., Parsons, J.: How UML is used. Commun. ACM 49(5), 109–113 (2006)

    Article  Google Scholar 

  18. Funk, A., Tablan, V., Bontcheva, K., Cunningham, H., Davis, B., Handschuh, S.: CLOnE: controlled language for ontology editing. In: Aberer, K., et al. (eds.) ASWC/ISWC -2007. LNCS, vol. 4825, pp. 142–155. Springer, Heidelberg (2007). https://doi.org/10.1007/978-3-540-76298-0_11

    Chapter  Google Scholar 

  19. Gozzi, R.: The Jigsaw puzzle as a metaphor for knowledge. ETC Rev. Gen. Seman. 53(4), 447–451 (1996)

    Google Scholar 

  20. Gustafson, E., Debruyne, C., De Troyer, O., Rogiers, V., Vinken, M., Vanhaecke, T.: Screening of repeated dose toxicity data in safety evaluation reports of cosmetic ingredients issued by the scientific committee on consumer safety between 2009 and 2019. Arch. Toxicol. 94(11), 3723–3735 (2020)

    Google Scholar 

  21. Hart, G., Johnson, M., Dolbear, C.: Rabbit: developing a control natural language for authoring ontologies. In: Bechhofer, S., Hauswirth, M., Hoffmann, J., Koubarakis, M. (eds.) ESWC 2008. LNCS, vol. 5021, pp. 348–360. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-68234-9_27

    Chapter  Google Scholar 

  22. Hessel, E.V., Staal, Y.C., Piersma, A.H.: Design and validation of an ontology-driven animal-free testing strategy for developmental neurotoxicity testing. Toxicol. Appl. Pharmacol. 354, 136–152 (2018). https://doi.org/10.1016/j.taap.2018.03.013

    Article  Google Scholar 

  23. Humble, J., et al.: “Playing with the bits’’ user-configuration of ubiquitous domestic environments. In: Dey, A.K., Schmidt, A., McCarthy, J.F. (eds.) UbiComp 2003. LNCS, vol. 2864, pp. 256–263. Springer, Heidelberg (2003). https://doi.org/10.1007/978-3-540-39653-6_20

    Chapter  Google Scholar 

  24. Ives, C., Campia, I., Wang, R.L., Wittwehr, C., Edwards, S.: Creating a structured adverse outcome pathway knowledgebase via ontology-based annotations. Appl. Vitro Toxicol. 3(4), 298–311 (2017). https://doi.org/10.1089/aivt.2017.0017

    Article  Google Scholar 

  25. Junior, A.C., Debruyne, C., Longo, L., O’Sullivan, D.: On the mental workload assessment of uplift mapping representations in linked data. In: Longo, L., Leva, M.C. (eds.) H-WORKLOAD 2018. CCIS, vol. 1012, pp. 160–179. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-14273-5_10

    Chapter  Google Scholar 

  26. Junior, A.C., Debruyne, C., O’Sullivan, D.: Juma Uplift: Using a Block Metaphor for Representing Uplift Mappings, January - February 2018. https://doi.org/10.1109/ICSC.2018.00037

  27. Kertcher, Z.: Gaps and bridges in interdisciplinary knowledge integration. In: Anandarajan, M., Anandarajan, M. (eds.) e-Research Collaboration, pp. 49–54. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-12257-6_4

    Chapter  Google Scholar 

  28. Maynard, D., Funk, A., Peters, W.: Using Lexico-syntactic ontology design patterns for ontology creation and population. In: Proceedings of ISWC 2009, Workshop on Ontology Patterns, Washington, USA, October 2009

    Google Scholar 

  29. Noy, N.F., McGuinness, D.L.: Ontology Development 101: A Guide to Creating Your First Ontology. Technical report, Standford Knowldge Systems, AI Lab (2001). https://corais.org/sites/default/files/ontology_development_101_aguide_to_creating_your_first_ontology.pdf

  30. Noy, N.F., et al.: Protégé-2000: an open-source ontology-development and knowledge-acquisition environment: AMIA 2003 Open Source Expo. In: Proceedings of AMIA 2003, Annual Symposium on American Medical Informatics. Washington, USA, November 2003

    Google Scholar 

  31. Öztürk, Ö., Özacar, T.: A case study for block-based linked data generation: recipes as jigsaw puzzles. J. Inf. Sci. 46(3), 419–433 (2020). https://doi.org/10.1177/0165551519849518

    Article  Google Scholar 

  32. Resnick, M., et al.: Scratch: programming for all. Commun. ACM 52(11), 60–67 (2009). https://doi.org/10.1145/1592761.1592779

    Article  Google Scholar 

  33. Sauro, J., Lewis, J.R.: Quantifying the User Experience: Practical Statistics for User Research, 2nd edn. Morgan Kaufmann, Cambridge (2016)

    Google Scholar 

  34. Siedlok, F., Hibbert, P.: The organization of interdisciplinary research: modes, drivers and barriers. Int. J. Manange. Rev. 16(3), 194–210 (2014)

    Article  Google Scholar 

  35. Slimani, T.: Ontology development: a comparing study on tools, languages and formalisms. Indian J. Sci. Technol. 8(24), 1–12 (2015). https://doi.org/10.17485/ijst/2015/v8i1/54249

    Article  Google Scholar 

  36. Sure, Y., Erdmann, M., Angele, J., Staab, S., Studer, R., Wenke, D.: OntoEdit: collaborative ontology development for the semantic web. In: Horrocks, I., Hendler, J. (eds.) ISWC 2002. LNCS, vol. 2342, pp. 221–235. Springer, Heidelberg (2002). https://doi.org/10.1007/3-540-48005-6_18

    Chapter  MATH  Google Scholar 

  37. Vinken, M., Pauwels, M., Ates, G., Vivier, M., Vanhaecke, T., Rogiers, V.: Screening of repeated dose toxicity data present in SCC (NF) P/SCCS safety evaluations of cosmetic ingredients. Arch. Toxicol. 86(3), 405–412 (2012). https://doi.org/10.1007/s00204-011-0769-z

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. WISE Lab, Vrije Universiteit Brussel, Brussels, Belgium

    Audrey Sanctorum, Jonathan Riggio & Olga De Troyer

  2. Research Group of In Vitro Toxicology and Dermato-Cosmetology (IVTD), Vrije Universiteit Brussel, Brussels, Belgium

    Sara Sepehri, Emma Arnesdotter & Tamara Vanhaecke

Authors
  1. Audrey Sanctorum
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jonathan Riggio
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sara Sepehri
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Emma Arnesdotter
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Tamara Vanhaecke
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Olga De Troyer
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Audrey Sanctorum .

Editor information

Editors and Affiliations

  1. Ingegneria dell'Informazione, Univ degli Studi di Brescia, Brescia, Italy

    Daniela Fogli

  2. Eindhoven University of Technology, Eindhoven, The Netherlands

    Daniel Tetteroo

  3. University of Brescia, Brescia, Italy

    Barbara Rita Barricelli

  4. University of Twente, Enschede, The Netherlands

    Simone Borsci

  5. Department of Industrial Design, Eindhoven University of Technology, Eindhoven, The Netherlands

    Panos Markopoulos

  6. University of Cyprus, Nicosia, Cyprus

    George A. Papadopoulos

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Sanctorum, A., Riggio, J., Sepehri, S., Arnesdotter, E., Vanhaecke, T., De Troyer, O. (2021). A Jigsaw-Based End-User Tool for the Development of Ontology-Based Knowledge Bases. In: Fogli, D., Tetteroo, D., Barricelli, B.R., Borsci, S., Markopoulos, P., Papadopoulos, G.A. (eds) End-User Development. IS-EUD 2021. Lecture Notes in Computer Science(), vol 12724. Springer, Cham. https://doi.org/10.1007/978-3-030-79840-6_11

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-79840-6_11

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-79839-0

  • Online ISBN: 978-3-030-79840-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation