The project consortium consists of three partners having complementary expertise. SINTEF Digital brings expertise in service science. Eindhoven University of Technology brings expertise in process mining. The University of Oslo brings expertise in formal methods and model-based analysis. The motivation for the project arose from a strong desire among the partners to impose an explicit, persistent user-centred focus on process mining by introducing (and digitising) the powerful concept of user journeys.
SINTEF - Human Computer Interaction (HCI) Group
The HCI group at SINTEF researches the interplay between technology, humans, and society. This knowledge is used to develop and evaluate computer systems suited to the needs and requirements of humans and society. The HCI group is multidisciplinary, spanning informatics, media science, psychology, and the natural sciences. Our research is always in the close vicinity of the end users. We do applied research in close collaboration with industrial partners.
The HCI group researches service processes and user journeys from theoretical and practical perspectives. A key tool when working with digital service innovation is the Customer Journey Modelling Language, a simple and visual way to create a common understanding of the details of digital services as seen from the user’s perspective. User journeys - or customer journeys - put humans at the center of a process, whether we have the role of patient, employee, user or employee. CJML helps you keep track of the details of the user journey and how it relates to IT systems.
Dr. Ragnhild Halvorsrud
Website: Human-Computer Interaction group
Website: Customer Journey Modelling Language
Eindhoven Univ. of Technology - Process Analytics Group
One of the foundations of computer science today is data. The omnipresence of increasingly large volumes of data has become a key driver for many innovations and new research directions in computer science. Specifically in information systems, data – and the analytics developed on top of this data – have transformed the field from expert-driven to evidence-based, which in turn massively broadens the applicability of results to more and larger contexts. Our main mission is to bridge the gap between process science (BPM, WFM, formal methods, etc.) and data science. This explains the focus on process mining.
The research concentrates on formalisms for modeling and methods to discover and analyze models. Fundamental to the research group at the Eindhoven University of Technology is the choice for Petri nets as the language to precisely describe process dynamics also in complex settings at a foundational level. The choice for this language is what distinguishes our research group from research groups in more industrial engineering oriented information systems groups. The research in the our group continues to expand outward from a “classical” situation of data with clear case notions in the context of explicitly structured processes to a broad, multi-faceted field, where processes are less structured or consist of many interacting artifacts and where case notions in data become more fluid or are complex, multi-dimensional networks.
The Process Analytics (PA) group tries to make research results accessible by providing (open-source) software. Many advanced process analysis tools and techniques exist today in over 25 commercial packages that were developed in the PA (formerly AIS) group over the last 15 years. Our prototyping framework ProM (process mining and process analysis) illustrates that the problems of tomorrow’s practice are the driving force behind the development of new theory, methods, and tools by PA.
Dr. Felix Mannhardt
Web site: Process Analytics Group:
Univ. of Oslo - Analytical Solutions and Reasoning Group
Designing a complex system is challenging: many possible settings and parameters can be tuned. Poor choices can result in system failure, high costs and displeased customers. These systems are technical, such as computer-based systems, organizational, such as maintenance programs, or both. Simulation and formal analysis can be used to capture and systematically analyse different aspects of such systems.
We develop tools and techniques within formal methods. We research on formal languages for system specifications and techniques to describe, predict and prescribe the behaviours and interactions of system executions based on the analysis of models. The research contributes to various methods and tools. In particular, we are building and maintaining ABS, a modelling and analysis framework for distributed systems. Using the ABS modelling language and analysis framework, we analyse both functional and non-functional properties such as safety properties, timing properties, resource management and scaling strategies.
Prof. Einar Broch Johnsen:
Web site: The Analytical Solutions and Reasoning group
Web site: The ABS language (Abstract Behavioral Specification)