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Context Modeling for the Adaption of Mobile Business Processes – An Empirical Usability Evaluation

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Abstract

Nowadays, the Internet of Things (IoT) and mobile devices are ubiquitous. Both, the IoT and mobile devices contain sensors and thus can provide data about the device’s environment. The sensor data can be used to infer the current context. However, for this purpose, the sensor data have to be aggregated. In this aggregation process, several different sensors and data provided by other sources, such as databases, can be used. In order to facilitate this, the paper presents a modeling language for context modeling based on sensors. Moreover, a detailed usability evaluation of the presented context modeling language is shown. This evaluation is based on three hypotheses regarding learnability, time expenditure and effectiveness. An experiment involving an experimental group and a control group was conducted to test these three hypotheses, and the results were interpreted.

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References

  • Al-alshuhai. A., Siewe, F. (2015). An extension of class diagram to model the structure of context-aware systems. In: The sixth international joint conference on advances in engineering and technology (AET).

  • Al-alshuhai, A., Siewe, F. (2015). An extension of UML activity diagram to model the behaviour of context-aware systems. In: Computer and information technology; ubiquitous computing and communications; dependable, autonomic and secure computing; pervasive intelligence and computing (CIT/IUCC/DASC/PICOM), pp 431–437.

  • Barrenechea, E. S., & Alencar, P. S. C. (2011). An adaptive context-aware and event-based framework design model. Procedia Computer Science, 5, 593–600. https://doi.org/10.1016/j.procs.2011.07.077 .

    Article  Google Scholar 

  • Biederman, I. (1987). Recognition-by-components: A theory of human image understanding. Psychological Review, 94, 115–147. https://doi.org/10.1037/0033-295X.94.2.115 .

    Article  Google Scholar 

  • Birkmeier, D., Kloeckner, S., Overhage, S. (2010). An empirical comparison of the usability of BPMN and UML activity diagrams for business users. In: P. M., Alexander, M. Turpin, J. P. van Deventer (eds) 18th European conference on information systems.

  • Challenger, M., Kardas, G., & Tekinerdogan, B. (2016). A systematic approach to evaluating domain-specific modeling language environments for multi-agent systems. Software Quality Journal, 24, 755–795. https://doi.org/10.1007/s11219-015-9291-5 .

    Article  Google Scholar 

  • Conforti, R., La Rosa, M., Fortino, G., ter Hofstede, A. H. M., Recker, J., & Adams, M. (2013). Real-time risk monitoring in business processes: A sensor-based approach. Journal of Systems and Software, 86, 2939–2965. https://doi.org/10.1016/j.jss.2013.07.024 .

    Article  Google Scholar 

  • Daniel, W. W. (1990). Applied nonparametric statistics, 2. ed. The Duxbury advanced series in statistics and decision sciences. Boston: PWS-KENT.

    Google Scholar 

  • Deelmann, T., & Loos, P. (2004). Grundsätze ordnungsmäßiger Modellvisualisierung. In B. Rumpe (Ed.), Modellierung 2004: Proceedings (pp. 289–290). Bonn: Ges. für Informatik.

    Google Scholar 

  • Dey, A. K. (2001). Understanding and using context. Personal and Ubiquitous Computing, 5, 4–7. https://doi.org/10.1007/s007790170019 .

    Article  Google Scholar 

  • Dey, A. K., Abowd, G. D. (2000). Towards a better understanding of context and context-awareness. In: M. Tremaine (ed) CHI '00 extended abstracts.

  • Dörndorfer, J., & Seel, C. (2017). A Meta model based extension of BPMN 2.0 for Mobile context sensitive business processes and applications. In J. M. Leimeister & W. Brenner (Eds.), Proceedings der 13 (pp. 301–315). St. Gallen: Internationalen Tagung Wirtschaftsinformatik (WI).

    Google Scholar 

  • Dörndorfer, J., & Seel, C. (2018). A framework to model and implement Mobile context-aware business applications. In I. Schäfer, D. Karagiannis, A. Vogelsang, D. Méndez, & C. Seidl (Eds.), Modellierung 2018 (pp. 22–38). Bonn: Gesellschaft für Informatik e.V.

    Google Scholar 

  • Dörndorfer, J., Seel, C., Hilpoltsteiner, D. (2018) SenSoMod – A modeling language for context-aware mobile applications. In: D. Paul, F. Burkhardt, N. Peter, X. Lin (eds) Multikonferenz Wirtschaftsinformatik (MKWI): Data driven X - turning data into value, vol. 4, pp. 1435–1446.

  • Dörndorfer, J., Hopfensperger, F., Seel, C. (2019) The SenSoMod-modeler – A model-driven architecture approach for Mobile context-aware business applications. In: C. Cappiello, M. R.Carmona (eds) CAiSE forum proceedings – Information systems engineering in responsible information systems. Springer Nature.

  • Falk, T., Leist, S. (2014). Effects of mobile solutions for improving business processes. In: M. Avital, J. M. Leimeister, U. Schultze (Eds.), ECIS 2014 proceedings: 22th European Conference on Information Systems; Tel Aviv, AIS Electronic Library.

  • Feldt, R., Magazinius, A. (2010). Validity threats in empirical software engineering research - an initial survey & knowledge engineering (SEKE’2010), Redwood City, San Francisco Bay, CA, USA, July 1 - July 3, 2010. In: Proceedings of the 22nd international conference on Software Engineering & Knowledge Engineering (SEKE’2010). Knowledge systems institute graduate school, pp 374–379.

  • Fowler, M., & Parsons, R. (2011). Domain-specific languages. A Martin Fowler signature book. Boston: Addison-Wesley.

    Google Scholar 

  • Gemino, A., & Wand, Y. (2004). A framework for empirical evaluation of conceptual modeling techniques. Requirements Eng, 9, 248–260. https://doi.org/10.1007/s00766-004-0204-6 .

    Article  Google Scholar 

  • Gemino, A., & Wand, Y. (2005). Complexity and clarity in conceptual modeling: Comparison of mandatory and optional properties. Data & Knowledge Engineering, 55, 301–326. https://doi.org/10.1016/j.datak.2004.12.009 .

    Article  Google Scholar 

  • Genon, N., Heymans, P., & Amyot, D. (2011). Analysing the cognitive effectiveness of the BPMN 2.0 visual notation. In B. Malloy, S. Staab, & M. van den Brand (Eds.), Software language engineering: Third international conference, SLE 2010, Eindhoven, The Netherlands, October 12–13, 2010 ; revised selected papers (pp. 377–369). Berlin: Springer.

    Chapter  Google Scholar 

  • Grubbs, F. E. (1969). Procedures for detecting outlying observations in samples. Technometrics, 11, 1–21. https://doi.org/10.1080/00401706.1969.10490657 .

    Article  Google Scholar 

  • Gruhn, V., Köhler, A., & Klawes, R. (2007). Modeling and analysis of mobile business processes. Journal of Ent Info Management, 20, 657–676. https://doi.org/10.1108/17410390710830718 .

    Article  Google Scholar 

  • Heinrich B, Schön D (2015) Automated Planning of Context-aware Process Models https://doi.org/10.18151/7217352

  • Hevner, A. R., Chatterjee, S. (2010). Design Research in Information Systems Theory and Practice. Integrated Series in Information Systems Volume 22. https://doi.org/10.1007/978-1-4419-5653-8 .

  • Hevner, A. R., March, S. T., Park, J., & Ram, S. (2004). Design science in information systems research. MIS Quarterly, 28, 75–105.

    Article  Google Scholar 

  • Holten, R. (2000) Entwicklung einer Modellierungstechnik für Data Warehouse-Fachkonzepte. In: H. Schmidt (Ed.), Modellierung betrieblicher Informationssysteme: PROCEEDINGS der MobIS-Fachtagung 2000, pp. 3–22.

  • Hoyos, J. R., García-Molina, J., & Botía, J. A. (2013). A domain-specific language for context modeling in context-aware systems. Journal of Systems and Software, 86, 2890–2905. https://doi.org/10.1016/j.jss.2013.07.008 .

    Article  Google Scholar 

  • ISO 9241-11:2018 (2018) Ergonomics of human-system interaction -- part 11: Usability: Definitions and concepts. International organization for standardization.

  • Jedlitschka, A., & Pfahl, D. (2005). Reporting guidelines for controlled experiments in software engineering. In 2005 international symposium on empirical software engineering, 2005 (pp. 95–104). Los Alamitos: IEEE Computer Society.

    Google Scholar 

  • Jeffery, C., & Al-Gharaibeh, J. (2015). Writing virtual environments for software visualization. New York: Springer.

    Book  Google Scholar 

  • Karlsson, F., & Ågerfalk, P. J. (2004). Method configuration: Adapting to situational characteristics while creating reusable assets. Information and Software Technology, 46, 619–633. https://doi.org/10.1016/j.infsof.2003.12.004 .

    Article  Google Scholar 

  • Kerr, D., & Koch, C. (2014). A Creative and Useful Tension? Large Companies Using Bring Your Own Device. In B. Bergvall-Kåreborn & P. A. Nielsen (Eds.), Creating Value for All Through IT: IFIP WG 8.6 International Conference on Transfer and Diffusion of IT, TDIT 2014, Aalborg, Denmark, June 2–4, 2014. Proceedings, vol 429 (pp. 166–178). Berlin: Springer.

    Chapter  Google Scholar 

  • Kitchenham, B. A., Pfleeger, S. L., Pickard, L. M., Jones, P. W., Hoaglin, D. C., El Emam, K., & Rosenberg, J. (2002). Preliminary guidelines for empirical research in software engineering. IIEEE Transactions on Software Engineering, 28, 721–734. https://doi.org/10.1109/TSE.2002.1027796 .

    Article  Google Scholar 

  • Kleppe, A., Warmer, J. B., & Bast, W. (2003). MDA explained: The model driven architecture ; practice and promise. Sebastopol: Safari online books. Addison-Wesley; Safari Books Online, Reading, Mass.

    Google Scholar 

  • Kramer, D., Clark, T., Oussena, S. (2010) MobDSL: A domain specific language for multiple mobile platform deployment. In: 2010 IEEE international conference on networked embedded Systems for Enterprise Applications. IEEE, pp. 1–7.

  • Kruskal, W. H., & Wallis, W. A. (1952). Use of ranks in one-criterion variance analysis. Journal of the American Statistical Association, 47, 583. https://doi.org/10.2307/2280779 .

    Article  Google Scholar 

  • La Vara JL de, Ali R, Dalpiaz F, Sánchez J, Giorgini P (2010) Business processes contextualisation via context analysis. In: Parsons J, Saeki M, Shoval P, Woo C, Wand Y (eds) Conceptual modeling - ER 2010: 29th International Conference on Conceptual Modeling, Vancouver, BC, Canada, November 1–4, 2010 ; proceedings, vol 6412. Springer, Berlin, pp 471–476.

  • Likert, R. (1932). A Technique for the Measurement of Attitudes. New York: Columbia Univ., Diss..

    Google Scholar 

  • Maamar, Z., Sellami, M., Faci, N., Ugljanin, E., & Sheng, Q. Z. (2018). Storytelling integration of the internet of things into business processes. In M. Weske, M. Montali, I. Weber, & J. Vom Brocke (Eds.), Business process management forum: BPM forum 2018, Sydney, NSW, Australia, September 9–14, 2018, proceedings (Vol. 329, pp. 127–142). Cham: Springer International Publishing.

    Chapter  Google Scholar 

  • Marín, B., Pastor, O., & Abran, A. (2010). Towards an accurate functional size measurement procedure for conceptual models in an MDA environment. Data & Knowledge Engineering, 69, 472–490. https://doi.org/10.1016/j.datak.2010.01.001 .

    Article  Google Scholar 

  • Mernik, M., Heering, J., & Sloane, A. M. (2005). When and how to develop domain-specific languages. ACM Computing Surveys, 37, 316–344. https://doi.org/10.1145/1118890.1118892 .

    Article  Google Scholar 

  • Mettler, T., Eurich, M., & Winter, R. (2014). On the use of experiments in design science research: A proposition of an evaluation framework. Communications of the Association for Information Systems, 34, 223–240.

    Article  Google Scholar 

  • Meyer, S., Ruppen, A., & Magerkurth, C. (2019). Internet of things-aware process modeling: Integrating IoT devices as business process resources. In R. King (Ed.), Active flow and combustion control 2018: Papers contributed to the conference “active flow and combustion control 2018”, September 19–21, 2018, Berlin, Germany (Vol. 141, pp. 84–98). Cham: Springer International Publishing.

    Chapter  Google Scholar 

  • Moody, D. (2009). The “physics” of notations: Toward a scientific basis for constructing visual notations in software engineering. IIEEE Transactions on Software Engineering, 35, 756–779. https://doi.org/10.1109/TSE.2009.67 .

    Article  Google Scholar 

  • Morabito, V. (2014). IT Consumerization. In V. Morabito (Ed.), Trends and challenges in digital business innovation (pp. 89–110). Cham: Springer.

    Chapter  Google Scholar 

  • Peffers, K., Tuunanen, T., Rothenberger, M. A., & Chatterjee, S. (2007). A design science research methodology for information systems research. Journal of Management Information Systems, 24, 45–77. https://doi.org/10.2753/MIS0742-1222240302 .

    Article  Google Scholar 

  • Peffers, K., Rothenberger, M., Tuunanen, T., & Vaezi, R. (2012). Design science research evaluation. In D. Hutchison, T. Kanade, J. Kittler, J. M. Kleinberg, F. Mattern, J. C. Mitchell, M. Naor, O. Nierstrasz, C. Pandu Rangan, B. Steffen, M. Sudan, D. Terzopoulos, D. Tygar, M. Y. Vardi, G. Weikum, K. Peffers, M. Rothenberger, & B. Kuechler (Eds.), Design science research in information systems. Advances in theory and practice (Vol. 7286, pp. 398–410). Berlin: Springer.

    Google Scholar 

  • Pereira, M., Mernik, M., da Cruz, D. C., & Henriques, P. (2008). Program comprehension for domain-specific languages. ComSIS, 5, 1–17. https://doi.org/10.2298/CSIS0802001P .

    Article  Google Scholar 

  • Perera, C., Zaslavsky, A., Christen, P., & Georgakopoulos, D. (2014). Context aware computing for the internet of things: A survey. IEEE Communication Surveys and Tutorials, 16, 414–454. https://doi.org/10.1109/SURV.2013.042313.00197 .

    Article  Google Scholar 

  • Rhee, K., Eun, S.-K., Joo, M.-R., Jeong, J., & Won, D. (2013). High-level Design for a Secure Mobile Device Management System. In L. Marinos & I. Askoxylakis (Eds.), Human aspects of information security, privacy, and trust: First international conference, HAS 2013, held as part of HCI International 2013, Las Vegas, NV, USA, July 21–26, 2013 ; proceedings (Vol. 8030, pp. 348–356). Berlin: Springer.

    Chapter  Google Scholar 

  • Rosemann, M., & Van der Aalst, W. M. P. (2007). A configurable reference modelling language. Information Systems, 32, 1–23. https://doi.org/10.1016/j.is.2005.05.003 .

    Article  Google Scholar 

  • Rosemann, M., Recker, J. C., & Flender, C. (2008). Contextualisation of business processes. International Journal of Business Process Integration and Management, 3(1), 47–60.

    Article  Google Scholar 

  • Rosemann, M., Recker, J., & Flender, C. (2011). Designing context-aware business processes. In K. Siau, R. Chiang, & B. C. Hardgrave (Eds.), Systems analysis and design: People, processes and projects (pp. 51–73). Armonk: M.E. Sharpe.

    Google Scholar 

  • Saidani, O., Nurcan, S. (2007). Towards context aware business process Modelling. In: Workshop on business process Modelling, development, and support, Norway, p 1.

  • Schalles, C. (2013). Usability evaluation of modeling languages. Wiesbaden: Springer Gabler. https://doi.org/10.1007/978-3-658-00051-6 .

    Book  Google Scholar 

  • Schilit, B., Adams, N., & Want, R. (1995). Context-aware computing applications. In L.-F. Cabrera & M. Satyanarayanan (Eds.), Workshop on Mobile computing systems and applications: Proceedings, December 8–9, 1994, Santa Cruz, California (pp. 85–90). Los Alamitos: IEEE Computer Society Press.

    Chapter  Google Scholar 

  • Schmidt, A., Beigl, M., & Gellersen, H.-W. (1999). There is more to context than location. Computers & Graphics, 23, 893–901. https://doi.org/10.1016/S0097-8493(99)00120-X .

    Article  Google Scholar 

  • Schmidt, D. C. (2006). Guest Editor's introduction: Model-driven engineering. Computer, 39, 25–31. https://doi.org/10.1109/MC.2006.58 .

    Article  Google Scholar 

  • Selic, B. (2003). The pragmatics of model-driven development. IEEE Software, 20, 19–25. https://doi.org/10.1109/MS.2003.1231146 .

    Article  Google Scholar 

  • Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and quasi-experimental designs for generalized causal inference, [Nachdr.]. Belmont: Wadsworth Cengage learning.

    Google Scholar 

  • Sheng QZ, Benatallah B (2005) ContextUML: A UML-based modeling language for model-driven development of context-aware web services development. In: International conference on Mobile business (ICMB), pp. 206–212.

  • Siau, K., & Loo, P.-P. (2006). Identifying difficulties in learning Uml. Information Systems Management, 23, 43–51. https://doi.org/10.1201/1078.10580530/46108.23.3.20060601/93706.5 .

    Article  Google Scholar 

  • Siau, K., Chiang, R., & Hardgrave, B. C. (Eds.). (2011). Systems analysis and design: People, processes and projects. Advances in management information systems (Vol. 18). Armonk: M.E. Sharpe.

    Google Scholar 

  • Soffer, P. (2005). On the notion of flexibility in business processes. In: Proceedings of the CAiSE’05 workshops, pp 35–42.

  • Sprinkle, J., Mernik, M., Tolvanen, J.-P., & Spinellis, D. (2009). Guest Editors' introduction: What kinds of nails need a domain-specific hammer? IEEE Software, 26, 15–18. https://doi.org/10.1109/MS.2009.92 .

    Article  Google Scholar 

  • Strahringer, S. (2005). Business Engineering. HMD, 241. Jg. 42. Heidelberg: Dpunkt-Verl.

    Google Scholar 

  • Venable, J., Pries-Heje, J., & Baskerville, R. (2016). FEDS: A framework for evaluation in design science research. European Journal of Information Systems, 25, 77–89. https://doi.org/10.1057/ejis.2014.36 .

    Article  Google Scholar 

  • Verclas, S., & Linnhoff-Popien, C. (Eds.). (2012). Smart Mobile Apps. Berlin: Xpert.press. Springer.

    Google Scholar 

  • Weiser, M. (1991). The computer for the 21st century. Scientific American, 265, 94–104. https://doi.org/10.1038/scientificamerican0991-94 .

    Article  Google Scholar 

  • Welch, B. L. (1947). The generalization of `Student's' problem when several different population variances are involved. Biometrika, 34, 28. https://doi.org/10.2307/2332510 .

    Article  Google Scholar 

  • Wohlin, C., Runeson, P., Höst, M., Ohlsson, M. C., Regnell, B., & Wesslén, A. (2012). Experimentation in software engineering. Berlin: Springer.

    Book  Google Scholar 

  • Zander, S., & Schandl, B. (2012). Context-driven RDF data replication on mobile devices. Semantic Web, 3, 131–155. https://doi.org/10.3233/SW-2011-004.

  • Zhu, X., vanden Broucke, S., Zhu, G., Vanthienen, J., & Baesens, B. (2016). Enabling flexible location-aware business process modeling and execution. Decision Support Systems, 83, 1–9. https://doi.org/10.1016/j.dss.2015.12.003.

    Article  Google Scholar 

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  1. University of Applied Sciences Landshut, Am Lurzenhof 1, 84036, Landshut, Germany

    Julian Dörndorfer & Christian Seel

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  1. Julian Dörndorfer
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Christian Seel was Deceased in October 2019

Appendix 1 Experimental Materials

Appendix 1 Experimental Materials

1.1 Experiment Model

Fig. 6
figure 6

Experiment model

Full size image

1.2 Calculation of the Generic Metric Complexity Measuring Model Complexity (GCMM) for the experiment model

Calculations based on (Schalles 2013) formulas (see pages 71–73).

Size

Semantic Spread

Connectivity

GCMM

S = (Edges + Nodes)

S = 11

L = ∑(Diff. Edges + Diff. Nodes)

L = 5

\( c=\frac{\sum Edges\ast 2}{\sum Nodes} \)

c = 16,666

\( {C}_m=\sqrt{\left(S+{L}^2\right)}\ast c \)

Cm = 99,996

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Dörndorfer, J., Seel, C. Context Modeling for the Adaption of Mobile Business Processes – An Empirical Usability Evaluation. Inf Syst Front 24, 195–210 (2022). https://doi.org/10.1007/s10796-020-10073-w

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