Supporting Context-Aware Engineering Based on Stream Reasoning

  • Dean Kramer
  • Juan Carlos AugustoEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10257)


In a world of increasing dynamism, context-awareness gives promise through the ability to detect changes in the context of devices, environment, and people. Equally, with stream reasoning using languages including C-SPARQL, continuous streams of raw data in RDF can be reasoned over for context-awareness. Writing many context queries and rules this way can however be error prone, and often contains boilerplate. In this paper, we present a context modelling notation designed to support the creation of context-awareness based on stream reasoning systems. In validating our language there is tool support which, amongst other benefits, can generate context queries in C-SPARQL and context aggregation rules for higher level context knowledge processing. An Android-compatible mobile platform context reasoner was developed which can handle these deployable context rules. This methodology and associated tools has been validated as part of an EU funded project.


Context-awareness Stream reasoning Context modelling 


  1. 1.
    Alegre, U., Augusto, J.C., Clark, T.: Engineering context-aware systems and applications: a survey. J. Syst. Softw. 117, 55–83 (2016)CrossRefGoogle Scholar
  2. 2.
    Augusto, J., Kramer, D., Alegre, U., Covaci, A., Santokhee, A.: The User-centred Intelligent Environments Development Process as a Guide to Co-create Smart Technology for People with Special Needs. Universal Access in the Information Society, January 2017Google Scholar
  3. 3.
    Augusto, J., Kramer, D.: Poseidon deliverable d3.2: reasoning and learning module. Technical report, POSEIDON Project (2015)Google Scholar
  4. 4.
    Augusto, J.C.: Increasing reliability in the development of intelligent environments. In: 5th International Conference on Intelligent Environments (IE-09), pp. 20–21, July 2009Google Scholar
  5. 5.
    Barbieri, D.F., Braga, D., Ceri, S., Valle, E.D., Grossniklaus, M.: C-SPARQL: a continuous query language for RDF data streams. Int. J. Semant. Comput. 04(01), 3–25 (2010)CrossRefzbMATHGoogle Scholar
  6. 6.
    Behrmann, G., David, A., Larsen, K.G., Hakansson, J., Petterson, P., Wang, Y., Hendriks, M.: Uppaal 4.0. In: Third International Conference on the Quantitative Evaluation of Systems, QEST 2006. pp. 125–126 (2006)Google Scholar
  7. 7.
    Cafezeiro, I., Viterbo, J., Rademaker, A., Haeusler, E.H., Endler, M.: A formal framework for modeling context-aware behavior in ubiquitous computing. In: Margaria, T., Steffen, B. (eds.) ISoLA 2008. CCIS, vol. 17, pp. 519–533. Springer, Heidelberg (2008). doi: 10.1007/978-3-540-88479-8_37 CrossRefGoogle Scholar
  8. 8.
    Cardelli, L.: Mobility and security. In: Lecture Notes for the Marktoberdorf Summer School 1999 (1999)Google Scholar
  9. 9.
    Golab, L., Ozsu, M.T.: Processing sliding window multi-joins in continuous queries over data streams. In: VLDB, pp. 500–511, February 2003Google Scholar
  10. 10.
    Guilly, T.L., Smedegard, J.H., Pedersen, T., Skou, A.: To do and not to do: constrained scenarios for safe smart house. In: 2015 International Conference on Intelligent Environments, pp. 17–24. IEEE, July 2015Google Scholar
  11. 11.
    Held, A., Buchholz, S., Schill, A.: Modeling of context information for pervasive computing applications. In: Proceedings of the 6th World Multiconference on Systemics, Cybernetics and Informatics (SCI2002), p. 6 (2002)Google Scholar
  12. 12.
    Henricksen, K., Indulska, J.: Developing context-aware pervasive computing applications: models and approach. Pervasive Mob. Comput. 2(1), 37–64 (2006)CrossRefGoogle Scholar
  13. 13.
    Hoyos, J.R., García-Molina, J., Botía, J.A.: A domain-specific language for context modeling in context-aware systems. J. Syst. Softw. 86(11), 2890–2905 (2013)CrossRefGoogle Scholar
  14. 14.
    Katsiri, E., Seranno, J.M., Serrat, J.: Application of logic models for pervasive computing environments and context-aware services support. In: Tsihrintzis, G.A., Virvou, M., Jain, L.C. (eds.) Multimedia Services in Intelligent Environments, vol. 2, pp. 105–117. Springer, Berlin (2010)CrossRefGoogle Scholar
  15. 15.
    Kjærgaard, M.B., Bunde-pedersen, J.: Towards a formal model of context awareness. In: Proceedings of the International Workshop of Combining Theory and Systems Building in Pervasive Computing-Pervasive 2006, pp. 667–674 (2006)Google Scholar
  16. 16.
    Kramer, D., Covaci, A., Augusto, J.C.: Developing navigational services for people with down’s syndrome. In: 2015 International Conference on Intelligent Environments, pp. 128–131 (2015)Google Scholar
  17. 17.
    Kramer, D., Kocurova, A., Oussena, S., Clark, T., Komisarczuk, P.: An extensible, self contained, layered approach to context acquisition. In: Proceedings of the Third International Workshop on Middleware for Pervasive Mobile and Embedded Computing - M-MPAC 2011, pp. 1–7. ACM Press, New York, December 2011Google Scholar
  18. 18.
    Muñoz, J., Pelechano, V., Fons, J.: Model driven development of pervasive systems. In: Proceedings of the 1st International Workshop on Model-Based Methodologies for Pervasive and Embedded Software (MOMPES), pp. 2–14 (2004)Google Scholar
  19. 19.
    Reichle, R., et al.: A comprehensive context modeling framework for pervasive computing systems. In: Meier, R., Terzis, S. (eds.) DAIS 2008. LNCS, vol. 5053, pp. 281–295. Springer, Heidelberg (2008). doi: 10.1007/978-3-540-68642-2_23 CrossRefGoogle Scholar
  20. 20.
    Serral, E., Valderas, P., Muñoz, J., Pelechano, V.: Towards a model driven development of context-aware systems for AmI environments. In: Rudolph, C. (ed.) Developing Ambient Intelligence, pp. 114–124. Springer, Paris (2008)CrossRefGoogle Scholar
  21. 21.
    Sheng, Q.Z., Benatallah, B.: ContextUML: A UML-based modeling language for model-driven development of context-aware web services development. In: Proceedings of the International Conference on Mobile Business, pp. 206–212. IEEE Computer Society, Washington, DC (2005)Google Scholar
  22. 22.
    Siewe, F., Zedan, H., Cau, A.: The calculus of context-aware ambients. J. Comput. Syst. Sci. 77(4), 597–620 (2011)MathSciNetCrossRefzbMATHGoogle Scholar
  23. 23.
    Strang, T., Linnhoff-Popien, C.: A context modeling survey. In: Proceedings of the Workshop on Advanced Context Modelling, Reasoning and Management, Workshop, pp. 1–8 (2004)Google Scholar
  24. 24.
    Valle, E.D., Ceri, S., van Harmelen, F., Fensel, D.: It’s a streaming world! Reasoning upon rapidly changing information. IEEE Intell. Syst. 24(6), 83–89 (2009)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.R.G on Development of Intelligent Environments, Department of Computer ScienceMiddlesex University LondonLondonUK

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