The field of process mining has evolved from discovering single work processes towards providing broad insights into peoples’ work practices. Existing techniques can be used to analyse such work practices, but this can be problematic if the available data is limited to the use of a single IT system or is not captured at the right level of granularity. We propose the use of a personal informatics technique, called Active Window Tracking (AWT), as a new way of gathering data for mining work practices. In this study, we identify the opportunities that this technique brings through a case study within our research group. In particular, we show how AWT helps to: capture previously-unrecorded work activities, expose the relations between work processes, and navigate between different levels of data granularity. The technique, which allows for generating new data as well as complementing existing data, is a valuable asset for the community when it comes to better understanding people’s work practices across individual systems and processes.

Before the findings of a process mining project can be turned into actionable insights or recommendations, it is essential to make sure that the findings are actually valid. Therefore, the evaluation of the findings is a crucial part of a successful process mining project. Current process mining methodologies, however, fall short in providing actionable support to perform such an evaluation. This is especially true when domain experts are involved. To close this gap, we performed a literature study considering all process mining case studies published in the last two decades. In total, we identified 244 candidate papers of which we analyzed 80 in depth. Based on this literature study, we found a need for a more systematic approach for qualitative evaluations in process mining projects where domain experts are involved. Therefore, we build on these results to propose six validation strategies, which originate from qualitative research. We believe that this proposal for more rigor in the evaluation phase of process mining projects helps to move the discipline forward.

The objective of this paper is to identify the current state of cloud business model adoption in Indonesia. We use an exploratory case study approach, since the number of publications on this topic is limited. We conducted 12 case studies with cloud service providers in Indonesia, which consisted of interviews and document studies. The analysis of our interviews revealed that the cloud business model adoption in Indonesia is mainly initiated by the local IT services providers. We also found that market demand was the main triggering factor for adopting the cloud business model. One of the key benefits that was mentioned, is the positive trend in revenue gains. The most encountered challenge for Indonesian cloud service providers is the low speed of internet connection in rural areas. The findings revealed from our study can serve as reference for IT practitioners and researchers who look for information and understanding on cloud business model adoption in Indonesia.

The process of implementing a Web Content Management System (WCM) can be complex and time consuming. We argue that there is a need for a web engineering methods specifically addressing WCM implementations. In this paper we present the design phase of our Web Engineering Method (WEM). The design phase of WEM addresses fourteen identified key WCM concepts and consists of the main activities: Conceptual Design, Architecture Design, Presentation Design and Detailed Component Design. The proposed method is validated through an expert validation and a case study. Based on the outcome, we developed a prototype of a CASE-application supporting the Conceptual Design activity. Future research includes further development of the CASE-application including the abstract syntax and automation of the transition.