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Process-Driven Data Collection with Smart Mobile Devices

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Web Information Systems and Technologies (WEBIST 2014)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 226))

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Abstract

Paper-based questionnaires are often used for collecting data in application domains like healthcare, psychology or education. Such paper-based approach, however, results in a massive workload for processing and analyzing the collected data. In order to relieve domain experts from these manual tasks, we propose a process-driven approach for implementing as well as running respective mobile business applications. In particular, the logic of a questionnaire is described in terms of an explicit process model. Based on this process model, in turn, multiple questionnaire instances may be created and enacted by a process engine. For this purpose, we present a generic architecture and demonstrate the development of electronic questionnaires in the context of scientific studies. Further, we discuss the major challenges and lessons learned. In this context the presented process-driven approach offers promising perspectives in respect to the development of mobile data collection applications.

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Author information

Authors and Affiliations

  1. Institute of Databases and Information Systems, Ulm University, Ulm, Germany

    Johannes Schobel, Marc Schickler, Rüdiger Pryss & Manfred Reichert

Authors
  1. Johannes Schobel
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  2. Marc Schickler
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  3. Rüdiger Pryss
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  4. Manfred Reichert
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Corresponding author

Correspondence to Johannes Schobel .

Editor information

Editors and Affiliations

  1. University of Paris, Paris, Paris, France

    Valérie Monfort

  2. RWTH Aachen University, Aachen, Germany

    Karl-Heinz Krempels

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Schobel, J., Schickler, M., Pryss, R., Reichert, M. (2015). Process-Driven Data Collection with Smart Mobile Devices. In: Monfort, V., Krempels, KH. (eds) Web Information Systems and Technologies. WEBIST 2014. Lecture Notes in Business Information Processing, vol 226. Springer, Cham. https://doi.org/10.1007/978-3-319-27030-2_22

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  • DOI: https://doi.org/10.1007/978-3-319-27030-2_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27029-6

  • Online ISBN: 978-3-319-27030-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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