AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
Powered by AMiner. Clicking this button will take you away from SciOpen.
Home International Journal of Crowd Science Article
PDF (972.4 KB)
Cite
EndNote(RIS) BibTeX
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Research paper | Open Access

Ontology enhancement using crowdsourcing: a conceptual architecture

School of Computing and Informatics, College of Biological and Physical Sciences, University of Nairobi, Nairobi, Kenya
Show Author Information

Abstract

Purpose

This paper aims to investigate the use of crowdsourcing in the enhancement of an ontology of taxonomic knowledge. The paper proposes a conceptual architecture for the incorporation of crowdsourcing into the creation of ontologies.

Design/methodology/approach

The research adopted the design science research approach characterised by cycles of “build” and “evaluate” until a refined artefact was established.

Findings

Data from a case of a fruit fly platform demonstrates that online crowds can contribute to ontology enhancement if engaged in a structured manner that feeds into a defined ontology model.

Research limitations/implications

The research contributes an architecture to the crowdsourcing body knowledge. The research also makes a methodological contribution for the development of ontologies using crowdsourcing.

Practical implications

Creating ontologies is a demanding task and most ontologies are not exhaustive on the targeted domain knowledge. The proposed architecture provides a guiding structure for the engagement of online crowds in the creation and enhancement of domain ontologies. The research uses a case of taxonomic knowledge ontology.

Originality/value

Crowdsourcing for creation and enhancement of ontologies by non-experts is novel and presents opportunity to build and refine ontologies for different domains by engaging online crowds. The process of ontology creation is also prone to errors and engaging crowds presents opportunity for corrections and enhancements.

Keywords

CrowdsourcingCitizen scienceBiodiversity informaticsOntology developmentOntology enhancement

References

 
Baclawski, K., Bennett, M., Dean, M., Denny, M., Gruninger, M., Hashemi, A., Longstreth, T., (2013), Communique. Towards Ontology Evaluation across the Life Cycle, in Neuhaus, F. and Vizedom, A. (Eds), Ontology Summit, p. 14.
 

Benbasat, I. and Zmud, R.W. (1999), “Empirical research in information systems: the practice of relevance”, MIS Quarterly, Vol. 23 No. 1, pp. 3-16.
Crossref Google Scholar
 

Canhos, V.P., de Souza, S., Giovanni, R.D. and Canhos, D.A.L. (2004), “Global biodiversity informatics: setting the scene for a ‘new world’ of ecological forecasting”, Biodiversity Informatics, Vol. 1, doi: 10.17161/bi.v1i0.3.
Crossref Google Scholar
 
Chen, M., Zheng, A. and Weinberger, K. (2013), “Fast image tagging”, Proceedings of the 30th International Conference on Machine Learning, pp. 1274-1282.
 
Chilton, L.B., Little, G., Edge, D., Weld, D.S. and Landay, J.A. (2013), “Cascade: crowdsourcing taxonomy creation”, Conference on Human Factors in Computing Systems – Proceedings, pp. 1999-2008.https://doi.org/10.1145/2470654.2466265
Crossref
 

Clark, B.R., Godfray, H.C.J., Kitching, I.J., Mayo, S.J. and Scoble, M.J. (2009), “Taxonomy as an eScience”, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, Vol. 367 No. 1890, pp. 953-966.
Crossref Google Scholar
 

Dar, G.H., Khuroo, A., Reddy, C.S. and Malik, A. (2012), “Impediment to taxonomy and its impact on biodiversity science: an Indian perspective”, Proceedings of the National Academy of Sciences, India Section B: Biological Sciences, Vol. 82 No. 2, pp. 235-240.
Crossref Google Scholar
 
Corcho, O., Fernández-López, M. and Gómez-Pérez, A. (2016), “Ontological engineering: principles, methods, tools and languages”, in Calero, C., Ruiz, F. and Piattini, M. (Eds), Ontologies for Software Engineering and Software Technology, Springer Berlin Heidelberg, Heidelberg, pp. 1-48.https://doi.org/10.1007/3-540-34518-3_1
Crossref
 

Doan, A., Ramakrishnan, R. and Halevy, A.Y. (2011), “Crowdsourcing systems on the World-Wide Web”, Communications of the Acm, Vol. 54 No. 4, doi: 10.1145/1924421.1924442.
Crossref Google Scholar
 
Fernández-López, M. (1999), “Overview of methodologies for building ontologies”, Proceedings of the IJCAI99 Workshop on Ontologies and Problem Solving Methods Lessons Learned and Future Trends, CEUR Publications, available at: http://oa.upm.es/5480/
 
Gerber, A., Eardley, C. and Morar, N. (2014), “An ontology-based taxonomic key for Afrotropical bees”, in Garbacz, P. and Kutz, O. (Eds), Proceedings of Frontiers in Artificial Intelligence and Applications (FOIS), IOS Press, pp. 277-288.
 

Godfray, H.C.J. (2002), “Challenges for taxonomy”, Nature, Vol. 417 No. 6884, pp. 17-19.
Crossref Google Scholar
 

Good, B.M. and Su, A.I. (2013), “Crowdsourcing for bioinformatics”, Bioinformatics (Oxford, England), Vol. 29 No. 16, pp. 1925-1933.
Crossref Google Scholar
 

Gruber, T.R. (1993), “A translation approach to portable ontology specifications”, Knowledge Acquisition, Vol. 5 No. 2, pp. 199-220.
Crossref Google Scholar
 
Grüninger, M. and Fox, M.S. (1995), “Methodology for the design and evaluation of ontologies”, Workshop on Basic and Ontological Issues in Knowledge Sharing, Citeseer, Montreal.
 
Guarino, N., Oberle, D. and Staab, S. (2009), “What is an Ontology?”, Handbook on Ontologies, Springer, pp. 1-17.https://doi.org/10.1007/978-3-540-92673-3_0
Crossref
 

Hardisty, A. and Roberts, D. (2013), “A decadal view of biodiversity informatics: challenges and priorities”, BMC Ecology, Vol. 13 No. 1, p. 16.
Crossref Google Scholar
 

Hevner, A.R. (2007), “A three cycle view of design science research”, Scandinavian Journal of Information Systems, Vol. 19 No. 2, pp. 4.
Google Scholar
 

Hevner, A.R., March, S., Park, J. and Ram, S. (2004), “Design science research in information systems”, MIS Quarterly, Vol. 28 No. 1, pp. 75-105.
Crossref Google Scholar
 
Horridge, M., Jupp, S., Moulton, G., Rector, A., Stevens, R. and Wroe, C. (2009), A Practical Guide to Building OWL Ontologies Using Prot{é}g{é} 4 and CO-ODE Tools Edition1. 2, The University of Manchester.
 
Horridge, M. Knublauch, H. Rector, A. Stevens, R. Wroe, C. Jupp, S. Moulton, G. et al. (2011),. “A practical guide to building OWL ontologies using protégè 4 and CO-ODE tools edition 1.3”, available at: http://owl.cs.manchester.ac.uk/tutorials/protegeowltutorial/resources/ProtegeOWLTutorialP4_v1_3.pdf
 
Hosseini, M., Phalp, K., Taylor, J. and Ali, R. (2014), “The four pillars of crowdsourcing: a reference model”, Proceedings – International Conference on Research Challenges in Information Science, IEEE Computer Society, doi: 10.1109/RCIS.2014.6861072.https://doi.org/10.1109/RCIS.2014.6861072
Crossref
 
Hung, N.Q.V., Tam, N.T., Tran, L.N. and Aberer, K. (2013), “An evaluation of aggregation techniques in crowdsourcing”, Web Information Systems Engineering – WISE, 2013, Springer, pp. 1-15.https://doi.org/10.1007/978-3-642-41154-0_1
Crossref
 
Ipeirotis, P.G., Provost, F. and Wang, J. (2010), “Quality management on Amazon mechanical turk”, Proceedings of the ACM SIGKDD Workshop on Human Computation, pp. 64-67.https://doi.org/10.1145/1837885.1837906
Crossref
 

Karger, D.R., Oh, S. and Shah, D. (2011), “Iterative learning for reliable crowdsourcing systems”, Advances in Neural Information Processing Systems, pp. 1953-1961.
Google Scholar
 
Khattak, F. and Salleb-Aouissi, A. (2011), “Quality control of crowd labeling through expert evaluation”, Proceedings of the NIPS 2nd Workshop on Computational Social Science and the Wisdom of Crowds, pp. 1-5.
 

Kim, K.C. and Byrne, L.B. (2006), “Biodiversity loss and the taxonomic bottleneck: emerging biodiversity science”, Ecological Research, Vol. 21 No. 6, pp. 794-810.
Crossref Google Scholar
 

Kiptoo, C.C., Gerber, A. and Van der Merwe, A. (2016b), “Towards citizen-expert knowledge exchange for biodiversity informatics: a conceptual architecture”, The African Journal of Information and Communication (AJIC).
Google Scholar
 
Kiptoo, C.C. (2017), “An ontology and crowd computing model for expert-citizen knowledge transfer in biodiversity management. Study leaders: Aurona G., van de Merwe A”, PhD Thesis., University of Pretoria, available at: https://repository.up.ac.za/handle/2263/62776
 
Kiptoo, C.C. Gerber, A. and van der Merwe, A. (2016a), “The ontological modelling of fruit fly control and management knowledge”, Fruit Fly Research and Development in Africa – Towards a Sustainable Management Strategy to Improve Horticulture, available at: https://doi.org/10.1007/978-3-319-43226-7_11
Crossref
 

Kuechler, W.L. and Vaishnavi, V.K. (2012), “A framework for theory development in design science research: multiple perspectives”, Journal of the Association for Information Systems, Vol. 13 No. 6, pp. 395-423.
Crossref Google Scholar
 

Kuechler, W.L.J. and Vaishnavi, V.K. (2008), “On theory development in design science research: anatomy of a research project”, European Journal of Information Systems, Vol. 17 No. 5, pp. 489-504.
Crossref Google Scholar
 

Kuncheva, L.I., Whitaker, C.J., Shipp, C.A. and Duin, R.P.W. (2003), “Limits on the majority vote accuracy in classifier fusion”,Pattern Analysis and Applications, Vol. 6 No. 1, pp. 22-31.
Crossref Google Scholar
 
Lee, K., Caverlee, J. and Webb, S. (2010), “The social honeypot project: protecting online communities from spammers”, Proceedings of the 19th International Conference on World Wide Web, pp. 1139-1140.https://doi.org/10.1145/1772690.1772843
Crossref
 

March, S.T. and Smith, G.F. (1995), “Design and natural science research on information technology”, Decision Support Systems, Vol. 15 No. 4, pp. 251-266.
Crossref Google Scholar
 

Mavandadi, S., Dimitrov, S., Feng, S., Yu, F., Sikora, U., Yaglidere, O., Padmanabhan, S., et al. (2012), “Distributed medical image analysis and diagnosis through crowd- sourced games: a malaria case study”,PLoS One, Vol. 7 No. 5, p. e37245.
Crossref Google Scholar
 

Niederman, F. and March, S.T. (2012), “Design science and the accumulation of knowledge in the information systems discipline”, ACM Transactions on Management Information Systems, Vol. 3 No. 1, pp. 1-15.
Crossref Google Scholar
 
Noy, N.F. and McGuinness, D.L. (2001), “Ontology development 101: a guide to creating your first ontology”, Stanford Knowledge Systems Laboratory, Stanford knowledge systems laboratory technical report KSL-01-05 and Stanford medical informatics technical report SMI-2001-0880.
 

Owen, C. (1998), “Design research: building the knowledge base”, Design Studies, Vol. 19 No. 1, pp. 9-20.
Crossref Google Scholar
 

Park, C.A., Bello, S.M., Smith, C.L., Hu, Z.-L., Munzenmaier, D.H., Nigam, R., Smith, J.R., et al. (2013), “The vertebrate trait ontology: a controlled vocabulary for the annotation of trait data across species”, Journal of Biomedical Semantics, Vol. 4 No. 1, p. 13.
Crossref Google Scholar
 

Parr, C.S., Wilson, N., Leary, P., Schulz, K.S., Lans, K., Walley, L., Hammock, J.A., et al. (2014), “The encyclopedia of life v2: providing global access to knowledge about life on earth”, Biodiversity Data Journal, Vol. 2, p. e1079.
Crossref Google Scholar
 

Peffers, K., Tuunanen, T., Gengler, C.E., Rossi, M., Hui, W., Virtanen, V. and Bragge, J. (2006), “The design science research process: a model for producing and presenting information systems research”, Proceedings of Design Research in Information Systems and Technology DESRIST’06, Vol. 24, pp. 83-106.
Google Scholar
 
Protege, T. (2000), “Protege 2000”, available at: http://protege.stanford.edu/
 

Purao, S., Rossi, M. and Bush, A. (2002), “Towards an understanding of the use of problem and design spaces during object-oriented system development”, Information and Organization, Vol. 12 No. 4, pp. 249-281.
Crossref Google Scholar
 
Qin, C., Bao, X., Roy Choudhury, R. and Nelakuditi, S. (2011), “TagSense: a smartphone-based approach to automatic image tagging”, MobiSys’11 – Compilation Proceedings of the 9th International Conference on Mobile Systems, Applications and Services and Co-Located Workshops, pp. 1-14.https://doi.org/10.1145/1999995.1999997
Crossref
 
Suárez-Figueroa, M.C., Gómez-Pérez, A. and Fernández-López, M. (2012), “The neon methodology for ontology engineering”, Ontology Engineering in a Networked World, Springer, pp. 9-34.https://doi.org/10.1007/978-3-642-24794-1_2
Crossref
 

Thessen, A.E., Bunker, D.E., Buttigieg, P.L., Cooper, L.D., Dahdul, W.M., Domisch, S., Franz, N.M., et al. (2015), “Emerging semantics to link phenotype and environment”, PeerJ, Vol. 3, p. e1470.
Crossref Google Scholar
 

Uschold, M. and King, M. (1995), “Towards a methodology for building ontologies”, Workshop on Basic and Ontological Issues in Knowledge Sharing, Vol. 80, pp. 275-280.
Google Scholar
 

Uschold, M. and Gruninger, M. (2004). “Ontologies and semantics for seamless connectivity” ACM SIGMOD Record, Vol. 33 4, pp. 58-64.
Crossref Google Scholar
 
von Ahn, L. and Dabbish, L. (2004), “Labeling images with a computer game”, Proceedings of the 2004 Conference on Human Factors in Computing Systems – CHI ‘04, pp. 319-326.https://doi.org/10.1145/985692.985733
Crossref
 

Walter, D.E. and Winterton, S. (2007), “Keys and the crisis in taxonomy: extinction or reinvention?”, Annual Review of Entomology, Vol. 52 No. 1, pp. 193-208.
Crossref Google Scholar
 

Yuen, M., King, I. and Leung, K. (2011), “A survey of crowdsourcing systems”, IEEE International Conference on Social Computing, pp. 766-773.
Google Scholar
International Journal of Crowd Science
Volume 4 Issue 3,
September 2020
Pages 231-243
DOI: 10.1108/IJCS-10-2019-0028
Cite this article:
Kiptoo CC. Ontology enhancement using crowdsourcing: a conceptual architecture. International Journal of Crowd Science, 2020, 4(3): 231-243. https://doi.org/10.1108/IJCS-10-2019-0028

829

Views

15

Downloads

6

Crossref

7

Scopus

Altmetrics
Received: 05 October 2019
Revised: 26 February 2020
Accepted: 03 March 2020
Published: 28 April 2020
© The author(s)

Chepkoech C. Kiptoo. Published in International Journal of Crowd Science. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode
Return