Attending my first online conference
https://www.emmsad.org/home
In this post, I share some reflections from attending and chairing my first online conference. Inspired by Renata Guizzardi, I write some take away messages from each presentation :-). I hope this can be useful to someone!

This is the 25th edition of EMMSAD. Since this is an online event, the sessions are not like traditional sessions. Three papers are presented per session, with just one discussion for all papers. Chairs and mediators are the ones who guide the discussion.

Take away messages from the talks

• Automated Process Improvement: Status, Challenges & Perspectives. Keynote by Marlon Dumas
  • From event logs it is possible exploit 4 capabilities. to 1) discover how to automate processes, 2) conduct conformance checking, 3) run performance measures, and 4) do variant analysis from different contexts. Process mining tools in general implement these 4 capabilities.
  • In this talk, the main focus is on process mining (PM) 2.0. Predictive process monitoring and prescriptive process monitoring is part of the operational level of PM 2.0. Predicting future states, outcomes, recommending actions on the basis of prediction. At a tactical level, we talk in terms of automated process improvement. For this, robotic (task) process mining, and search based process automation.
  • Predictive models are based on ML or DL techniques.
  • Prescriptive process monitoring is to use prediction techniques for further improvement.
  • For automated process improvement, we can think about package changes. These package changes can refer to tasks (best practices), control flow (add, merge, split, parallelise, etc), decision (add/delete decision points, refine/enhance decision rules), resource (check resource pools and refine/adapt them).
  • Interesting research in the area of search-based process optimisation. The main challenges discusses possible research questions that can trigger PhD/Postdoc projects.
  • Check out PIX: The process improvement explorer https://sep.cs.ut.ee/Main/PIX
• Opening and requirements & method engineering
  • A Multi-Concern Method for Identifying Business Services: A Situational Method Engineering Study. video. By Onat Ege Adali, Oktay Turetken, Baris Ozkan, Rick Gilsing and Paul Grefen.
    Situational method engineering can also be focused from the perspective of modelling concerns. This is a very interesting point of view that could help to develop methods. To me, it sounds like a stakeholders’ perspective of developing methods.
  • Sara Perez-Soler, Gwendal Daniel, Jordi Cabot, Esther Guerra and Juan De Lara. Towards Automating the Synthesis of Chatbots for Conversational Model Query (short paper). video
    A big challenge is to adapt bots to specific context. Here, MDE can greatly help to model context.

• Enterprise & business modeling
  • Steven Alter. Applying Facets of Work as a Source of Knowledge and Insight for Requirements Determination. video
    The notion of work system framework allows the implementation of facets.
  • Rui Song, Tong Li and Zhiming Ding. Automatically Identify Requirements-oriented Reviews Using a Hybrid Feature Extraction Approach. video . Important to review related work on identification of requirements from user reviews. One of the main problems is: do you rely on user reviews? What kind of users tend to write reviews? Are reviews a trusted source of requirements and feedback?

• Evaluated related research
  • Ben Roelens and Dominik Bork. An Evaluation of the Intuitiveness of the PGA Modeling Language Notation. video
    This paper discusses the evaluation of the process goal alignment language in terms of intuitiveness. A specific method for evaluating intuitiveness was applied (Bork et al 2019). Interesting to examples for evaluating IS languages. To what extent do you implement modifications to the notation based evaluation’s feedback? Evaluation of notations can boost the use of new languages in practice. Would it be interesting to adapt notation based on users’ profile? it would be that certain users, like enterprise architecture. Intuitiveness is defined as semantic transparency by the authors.
  • Mouaad Hafsi and Said Assar. Does Enterprise Architecture support Customer Experience Improvement? Towards a Conceptualization in Digital Transformation Context. video
    Does EAM support experience customer improvement projects in a digital transformation context? Digital transformation is triggered thanks to the need to improve customer experience. It is expected that digital transformation would help, but, what is the role of enterprise modelling? Can you elaborate more how in your study, the connection between digital transformation processes and the use of EA can be used? Is the objective to model digital transformation?
  • Rick Gilsing, Anna Wilbik, Paul Grefen, Oktay Turetken and Baris Ozkan. A Formal Basis for Business Model Evaluation with Linguistic Summaries. video
    Using soft-quantified business models for evaluating business models. The great thing of this research is that the proposed soft- quantified evaluation can be applied to any other kind of business model, like the business model canvas.

• Domain-specific modeling
  • Roman Lukyanenko. A journey to BSO: Evaluating Earlier and More Recent Ideas of Mario Bunge as a Foundation for Information and Software Development. video
    Somehow ontologies frames your thinking, this paper discusses the role of ontologies in information and software development. This is an interesting paper to find a good balance between the use of ontology and formalism, and the use of IS tools in practice.
    This paper got the best paper award! There is an amazing story behind this paper. What a beautiful way to transfer philosophical concepts to computer science.
  • Thomas Gray, Dominik Bork and Marne De Vries. A New DEMO Modelling Tool that Facilitates Model Transformations. video
    In the video, the authors present a live demo of their tool DEMO. DEMO currently supports BPMN transformation. For modelling with DEMO, there is no way to specify orders (procedural steps). The DEMO process model presents the different parameters on how the interaction needs to be supported.
  • Sabine Molenaar, Laura Schiphorst, Metehan Doyran, Albert Salah, Fabiano Dalpiaz and Sjaak Brinkkemper. Reference Method for the Development of Domain Action Recognition Classifiers: the Case of Medical Consultations. video
    Given that it is so hard to find available data to train ML algorithms which are not annotated. This research proposes a method for automatically recognise action classifiers. Despite the method is designed for the medical domain, there is quite a great potential to be used on different domains.

• Software-related modeling
  • Florian Rademacher, Sabine Sachweh and Albert Zündorf. A Modeling Method for Systematic Architecture Reconstruction of Microservice-Based Software Systems. video
    
  • Luiz Marcio Cysneiros and Julio Cesar Leite. Non-Functional Requirements Orienting the Development of Socially Responsible Software. (short paper). video
    One of the most interesting aspects of this research is its potential to support XAI.

This book presents TraceME, a traceability-based method for conceptual model evolution whose general purpose is to support the evolution of information systems. By providing a set of four TraceME chunks, TraceME is situational-oriented. In this way, it can be adapted to support different evolution projects by just assembling the TraceME chunks. To facilitate its industrial adoption, open source tools were developed and described which support the implementation of the TraceME chunks.

The work presented highlights various research endeavors for the development of methods and techniques to automate the evolution of software systems. It explores the requirements engineering field as a steppingstone to a successful software development processes. In 2017, the underlying PhD dissertation won the “CAiSE PhD award”, granted to outstanding PhD theses in the field of Information Systems Engineering.

The book is available in Amazon and Springer.

Best PhD award CAiSE 2017. The CAiSE PhD Award is granted to outstanding PhD theses in the field of Information Systems Engineering. The award, co-sponsored by the CAiSE Steering Committee and Springer, consists of a certificate, a free full registration (5 days) to the next two CAiSE conferences, and a book voucher for a free selection worth EUR 500,- from Springer’s printed books collection. In addition, my thesis is going to be published as a monograph in the LNBIP series by Springer in 2018.