HoloMAS 2015: Industrial Applications of Holonic and Multi-Agent Systems pp 217-229 | Cite as
Big Data Semantics in Industry 4.0
Abstract
The Industry 4.0 is a vision that includes connecting more intensively physical systems with their virtual counterparts in computers. This computerization of manufacturing will bring many advantages, including allowing data gathering, integration and analysis in the scale not seen earlier. In this paper we describe our Semantic Big Data Historian that is intended to handle large volumes of heterogeneous data gathered from distributed data sources. We describe the approach and implementation with a special focus on using Semantic Web technologies for integrating the data.
Keywords
Industry 4.0 Cyber-Physical Systems Big Data Semantics Internet of Things Industrial automation HeterogeneityPreview
Unable to display preview. Download preview PDF.
References
- 1.Becker, A., Sénéclauye, G., Purswani, P., Karekar, S.: Internet of Things. Atos White Paper (2012)Google Scholar
- 2.Bizer, Ch., Boncz, P., Brodie, M.L., Erling, O.: The Meaningful Use of Big Data: Four Perspectives – Four Challenges. SIGMOD Records 40(4), 2011 (2011)Google Scholar
- 3.Compton, M., Barnaghi, P., Bermudez, L., Garcia-Castro, R., Corcho, O., Cox, S., Graybeal, J., Hauswirth, M., Henson, C., Herzog, A.: The SSN ontology of the W3C semantic sensor network incubator group. Web Semantics: Science, Services and Agents on the World Wide Web, 17 (2012)Google Scholar
- 4.Chui, M., Löffler, M., Roberts, R.: The Internet of Things. McKinsey Quarterly (2010)Google Scholar
- 5.GE Intelligent Platforms: The Rise of Industrial Big Data. Whitepaper (2012)Google Scholar
- 6.Herrman, M., Pentek, T., Otto, B.: Design Principles for Industrie 4.0 Scenarios: A Literature Review. Working Paper 01/205, Technishe Universität DortmundGoogle Scholar
- 7.IBM Software: Managing Big Data for smart grids and smart meters. Whitepaper (2012)Google Scholar
- 8.Jirkovsky, V., Obitko, M., Novak, P., Kadera, P.: Big Data analysis for sensor time-series in automation. In: Proc. of the 19th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), Barcelona (2014)Google Scholar
- 9.Lee, E.A.: Cyber physical systems: design challenges. In: 11th IEEE Symposium on Object Oriented Real-Time Distributed Computing (ISORC) (2008)Google Scholar
- 10.Lee, J., Bagheri, B., Kao, H-A.: Recent advances and trends of Cyber-Physical Systems and Big Data analytics in industrial informatics. In: Proceeding of International Conference on Industrial Informatics (INDIN) (2014)Google Scholar
- 11.Manola, F., Miller, E. (eds): RDF Primer. W3C Recommendation (2004)Google Scholar
- 12.NewVantage Partners: Big Data Executive Survey 2012. Consolidated Summary Report (2012)Google Scholar
- 13.Obitko, M., Jirkovský, V., Bezdíček, J.: Big data challenges in industrial automation. In: Mařík, V., Lastra, J.L., Skobelev, P. (eds.) HoloMAS 2013. LNCS, vol. 8062, pp. 305–316. Springer, Heidelberg (2013)CrossRefGoogle Scholar
- 14.Singh, S., Singh, N.: Big Data analytics. In: 2012 International Conference on Communication, Information & Computing Technology (ICCICT), Mumbai, India. IEEE Press (2012)Google Scholar
- 15.Vrba, P., Tichy, P., Marik, V., Hall, K.H., Staron, R.J., Maturana, F.P., Kadera, P.: Rockwell Automation’s Holonic and Multiagent Control Systems Compendium. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews 41 (2011)Google Scholar
- 16.W3C OWL Working Group: OWL 2 Web Ontology Language Document Overview, 2nd edn. W3C Recommendation (2012)Google Scholar