Peter Khisa Wakholi defends his PhD thesis

Peter Khisa Wakholi, an assistant lecturer in the department of Information Systems successfully defended his PhD thesis titled, Process Aware Mobile Systems: Applied to mobile-phone based data collection, at the University of Bergen, Norway on 24th May, 2013.

His thesis can be accessed at


The quest to provide computing services to resource-constrained environments in developing countries is becoming a reality due to the wide use of mobile phones and penetration of mobile networks. Nowadays, many organisations use Mobile Data Collection (MDC) tools to enable the collection and digitalisation of data at source, hence improving quality and increasing efficiencies. Mobile devices and environments present challenges to computing and application design that need to be overcome.

Beyond mere digitalisation of data, MDC tools need to consider the process-related aspects of data collection used in paper-based routines expressed through paper trails. This lack of process-related support hinders the adoption of MDC routines in cases where great attention is paid to the data collection process. In conventional information systems, process-related features are implemented using workflows which may be embedded in an application or separately defined using Workflow Management Systems. This has led to the development of Process-Aware Information Systems (PAISs), which are software systems for managing and executing operational processes involving people, applications, and/or information sources on the basis of process models. PAISs facilitate the inclusion of process- related activities which include the ordering of various tasks undertaken to achieve a business goal (control flow), the collaboration among various entities, and the allocation and provision as well the exchange of relevant information necessary for decision making.

The use of mobile devices to carry out tasks is not the most preferable choice due to hardware limitations. Mobile-based systems should integrate with existing desktop- based solutions to provide a multiple access platform for work execution. This calls for integrating workflow systems with generic mobile data collection tools, which would require modifications in approach, methods and architecture to cater for device and environmental constraints in order to enable the mobile devices to be used appropriately.

This thesis proposes a range of techniques that can be used to enable workflow support for mobile data collection. The overall goal is to minimise changes in workflow systems architecture, since these are based on widely agreed standards. Therefore, we propose an approach for online execution of work, for scenarios where network connection is readily available, and offline execution of work controlled by a workflow engine, when the connection is not available. A workflow adapter is proposed to enable matching of forms for data collection and workflow specifications. A distributed architecture for offline data collection based on partitioning a process model into fragments for distributed execution is also proposed.

The methods proposed have been implemented with the OpenXdata MDC suite used for data collection and YAWL workflow management system. The OpenXdata and YAWL platforms adhere to commonly agreed standards for mobile data collection and workflow management and thus provide generalizable concepts within the domain of process-aware mobile data collection. Experiments were carried out on foundational concepts in order to determine that all relevant workflow-related constraints are observed. In addition, artefacts developed from the application of these methods were implemented in real life projects. The findings and results of these applications were used to validate the methods and frameworks suggested.


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