End-User Programming of Mobile Services: Empowering Domain Experts to Implement Mobile Data Collection Applications

The widespread use of smart mobile devices (e.g., in clinical trials or online surveys) offers promising perspectives with respect to the controlled collection of high-quality data. The design, implementation and deployment of such mobile data collection applications, however, is challenging in several respects. First, various mobile operating systems need to be supported, taking the short release cycles of vendors into account as well. Second, domain-specific requirements need to be flexibly aligned with mobile application development. Third, usability styleguides need to be obeyed. Altogether, this turns both programming and maintaining mobile applications into a costly, time-consuming, and error-prone endeavor. To remedy these drawbacks, a model-driven framework empowering domain experts to implement robust mobile data collection applications in an intuitive way was realized. The design of this end-user programming framework is based on experiences gathered in real-life mobile data collection projects. Facets of various stakeholders involved in such projects are discussed and an overall architecture as well as its components are presented. In particular, it is shown how the framework enables domain experts (i.e., end users) to flexibly implement mobile data collection applications on their own. Overall, the framework allows for the effective support of mobile services in a multitude of application domains.

[1]  Kenton O'Hara,et al.  Social Impact , 2019, Encyclopedia of Food and Agricultural Ethics.

[2]  Russell A. McCann,et al.  mHealth for mental health: Integrating smartphone technology in behavioral healthcare. , 2011 .

[3]  Jason I. Hong,et al.  Marmite: Towards End-User Programming for the Web , 2007, IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC 2007).

[4]  Manfred Reichert,et al.  Using Smart Mobile Devices for Collecting Structured Data in Clinical Trials: Results from a Large-Scale Case Study , 2015, 2015 IEEE 28th International Symposium on Computer-Based Medical Systems.

[5]  Manfred Reichert,et al.  Supporting medical ward rounds through mobile task and process management , 2015, Inf. Syst. E Bus. Manag..

[6]  Eser Kandogan,et al.  A1: end-user programming for web-based system administration , 2005, UIST '05.

[7]  Steve Rabin,et al.  Introduction to Game Development , 2005 .

[8]  Manfred Reichert,et al.  Enabling Flexibility in Process-Aware Information Systems: Challenges, Methods, Technologies , 2012 .

[9]  Andrea Gaggioli,et al.  A mobile data collection platform for mental health research , 2013, Personal and Ubiquitous Computing.

[10]  Manfred Reichert,et al.  Enabling Flexibility in Process-Aware Information Systems , 2012, Springer Berlin Heidelberg.

[11]  Peter Dadam,et al.  Enabling Adaptive Process-Aware Information Systems with ADEPT2 , 2008, Handbook of Research on Business Process Modeling.

[12]  Eric Paulos,et al.  Sensr: evaluating a flexible framework for authoring mobile data-collection tools for citizen science , 2013, CSCW.

[13]  Wil M. P. van der Aalst,et al.  Process mining: a research agenda , 2004, Comput. Ind..

[14]  Manfred Reichert,et al.  Mobile Crowd Sensing Services for Tinnitus Assessment, Therapy, and Research , 2015, 2015 IEEE International Conference on Mobile Services.

[15]  Ricarose Roque OpenBlocks : an extendable framework for graphical block programming systems , 2007 .

[16]  Jakob Nielsen,et al.  Usability engineering , 1997, The Computer Science and Engineering Handbook.

[17]  Manfred Reichert,et al.  Process-Driven Data Collection with Smart Mobile Devices , 2014, WEBIST.

[18]  Frank Leymann,et al.  Web Services Platform Architecture: SOAP, WSDL, WS-Policy, WS-Addressing, WS-BPEL, WS-Reliable Messaging, and More , 2005 .

[19]  Susan A. Yoon,et al.  Teaching Complex Dynamic Systems to Young Students with StarLogo , 2005 .

[20]  Andrew Begel,et al.  StarLogo TNG: An Introduction to Game Development , 1996 .

[21]  T Elbert,et al.  The role of FKBP5 genotype in moderating long-term effectiveness of exposure-based psychotherapy for posttraumatic stress disorder , 2014, Translational Psychiatry.

[22]  Manfred Reichert,et al.  Detecting adverse childhood experiences with a little help from tablet computers , 2013 .

[23]  Manfred Reichert,et al.  Preventing further trauma: KINDEX mum screen - assessing and reacting towards psychosocial risk factors in pregnant women with the help of smartphone technologies , 2013 .