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A Pragmatic Approach Towards Leveraging Employee Competences by Use of Semantic Web Technologies

Part of: Design Management

Published online by Cambridge University Press:  26 July 2019

Felix Ocker  and
Birgit Vogel-Heuser

Abstract

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Global competition in combination with the increasing specialization of labor requires organizations to leverage their employees' competences. The approach presented in this paper empowers organizations to do so in two ways. First, we give employers a lean tool to allocate their employees to current and upcoming projects and make informed decisions whether they should take on new projects. Secondly, we provide the means to identify potential areas for innovation by identifying blind spots of technology transfer. The approach presented relies on semantic web technologies, i.e. an ontology built in OWL and SPARQL queries. To increase usability, we realized a user interface based on a semi-formalized spreadsheet and a python script for the transformation.

Keywords

Employee AllocationCreativityKnowledge managementInnovationOntologies
Type
Article
Information
Proceedings of the Design Society: International Conference on Engineering Design , Volume 1 , Issue 1 , July 2019 , pp. 1045 - 1054
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
© The Author(s) 2019

References

Arp, R., Smith, B. and Spear, A. D., (2015), Building ontologies with basic formal ontology, MIT Press.Google Scholar
Chaston, I. (2012), “Strategy for Sustainable Competitive Advantage”, Taylor & Francis Group, New York. http://doi.org/10.1080/10599230903323698Google Scholar
Draganidis, F. and Mentzas, G. (2006). “Competency based management: a review of systems and approaches”. Information management & computer security, Vol. 14 No. 1, pp. 51–64. https://dx.doi.org/10.1108/09685220610648373Google Scholar
Draganidis, F., Chamopoulou, P. and Mentzas, G. (2008), “A semantic web architecture for integrating competence management and learning paths”, Journal of knowledge management, Vol. 12 No. 6, pp. 121–136. https://dx.doi.org/10.1108/13673270810913667Google Scholar
Gaeta, M., Orciuoli, F., Fenza, G., Mangione, G. R. and Ritrovato, P. (2012), “A semantic approach for improving competence assessment in organizations”, International Conference on Advanced Learning Technologies, IEEE, pp. 85–87. http://doi.org/10.1109/ICALT.2012.168Google Scholar
Gruber, T. R. (1993), “A translation approach to portable ontology specifications”, Knowledge Acquisition, Vol. 5 No. 2: pp. 199–220. http://doi.org/10.1006/knac.1993.1008Google Scholar
HR Open Standards Consortium, Inc. (2018), HR Open Standards, online: https://hropenstandards.org/Google Scholar
Khobreh, M., Ansari, F., Fathi, M., Vas, R., Mol, S. T., Berkers, H. A. and Varga, K. (2016), “An ontology-based approach for the semantic representation of job knowledge”, IEEE Transactions on Emerging Topics in Computing, Vol. 4 No. 3, pp. 462–473. http://doi.org/10.1109/TETC.2015.2449662Google Scholar
Kukk, V., Umbleja, K. and Jaanus, M. (2015), “Two-dimensional knowledge model for learning control and competence mapping”. International Workshop on Learning Technology for Education in Cloud, Springer, Maribor, Slovenia, 2015, pp. 16–27. https://dx.doi.org/10.1007/978-3-319-22629-3_2Google Scholar
Malone, T. W., Laubacher, R. and Johns, T. (2011), “The Big Idea: The Age of Hyperspecialization”, Harvard Business Review, online: https://hbr.org/2011/07/the-big-idea-the-age-of-hyperspecializationGoogle Scholar
McComb, C., Cagan, J. and Kotovsky, K. (2016), “Linking Properties of Design Problems to Optimal Team Characteristics”, International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. https://dx.doi.org/10.1115/DETC2016-59333Google Scholar
Melosi, F., Campana, G. and Cimatti, B. (2018), “Competences Mapping as a Tool to increase Sustainability of Manufacturing Enterprises”, Procedia Manufacturing, Vol. 21, pp. 806–813. https://dx.doi.org/10.1016/j.promfg.2018.02.187Google Scholar
Noy, N. F. and McGuinness, D. L. (2001), Ontology development 101: A guide to creating your first ontology.Google Scholar
Ritchey, T. (2002), “General Morphological Analysis”, Wicked Problems - Social Messes. Risk, Governance and Society, Springer, Berlin, pp. 7–18. http://doi.org/10.1007/978-3-642-19653-9Google Scholar
Rogushina, J. and Gladun, A. (2012), “Ontology-based competency analyses in new research domains”, Journal of Computing and Information Technology, Vol. 20 No. 4, pp. 277–291. https://dx.doi.org/10.2498/cit.1002034Google Scholar
Singh, V., Dong, A. and Gero, J. S. (2012), “Computational studies to understand the role of social learning in team familiarity and its effects on team performance”, CoDesign, Vol. 8 No. 1, pp. 25–41. https://dx.doi.org/10.1080/15710882.2011.633088Google Scholar
Singh, V., Dong, A. and Gero, J. S. (2013), “Social learning in design teams: The importance of direct and indirect communications”, Artificial Intelligence for Engineering Design, Analysis and Manufacturing, Vol. 27, pp. 167–182. https://dx.doi.org/10.1017/S0890060413000061Google Scholar
Volpentesta, A. P. and Felicetti, A. M. (2011), “Competence mapping through analysing research papers of a scientific community”, Doctoral Conference on Computing, Electrical and Industrial Systems, Springer, Berlin, Heidelberg, pp. 33–44. http://doi.org/10.1007/978-3-642-19170-1_4Google Scholar
World Wide Web Consortium (2007), “Semantic Web Stack”. Online, last retrieved 2019-04-07: https://www.w3.org/2007/03/layerCake.pngGoogle Scholar
World Wide Web Consortium (2012), “OWL 2 Web Ontology Language”. Online, last retrieved 2019-04-07: https://www.w3.org/TR/owl2-overview/Google Scholar
Zwicky, F. (1967), “The Morphological Approach to Discovery, Invention, Research and Construction”, In: Zwicky, F., Wilson, A.G. (eds), New Methods of Thought and Procedure, Springer, Berlin, pp. 273–297. http://doi.org/10.1007/978-3-642-87617-2_14Google Scholar