From Representation to Mediation: Modeling Information Systems in a Digital World
Jan Recker, University of Hamburg, Germany
Myths and Misconceptions about Machine Learning and How They Are Related to Software Engineering
Stefan Kramer, Johannes Gutenberg - Universität Mainz, Germany
What Can We Learn from Play?
Panos Markopoulos, Eindhoven University of Technology, Netherlands
How AI and Digital Are Key of Manufacturers Survival
Eric Prevost, Oracle, United States
Impact of End User Human Aspects on Software Engineering
John Grundy, Monash University, Australia
From Representation to Mediation: Modeling Information Systems in a Digital World
Jan Recker
University of Hamburg
Germany
http://www.janrecker.com/
Brief Bio
Prof Dr Jan Recker is a Professor for Information Systems and Digital Innovation in the Hamburg Business School at the University of Hamburg. He is also Adjunct Professor at the QUT Business School, Australia.
In his research he explores the intersection of technology, people and work. He works with particularly large organizations, such as Woolworths, SAP, Hilti, Commonwealth Bank, Lufthansa, Ubisoft, federal and state governments, and with particularly small organizations ("start-ups") in the consumer goods, information techology, and financial sectors. He tackles questions such as:
• How do small and large organizations deal with digital innovation and transformation?
• How do products and processes change through digitalization?
• How can digital solutions help building a sustainable future?
Jan's research in these areas draws on quantitative, qualitative and mixed field methods. His research has appeared in leading information systems, management science, software engineering, project management, computer science, and sociology journals. He has also written popular textbooks on scientific research and data analysis, which are in use in over 500 institutions in over 60 countries. He ranks as one of the most published information systems academics of all time. In 2019, he was named #1 business researcher under 40 years of age by the German Magazine Wirtschaftswoche. He was the youngest academic ever to be named an AIS fellow in 2018.
Abstract
The role of information systems is changing in an increasingly digitalized world. Does this situation mean that established conceptual modeling practices relevant to the analysis and design of systems must change as well? In this talk, I will answer this question with a definite and affirmative “yes”. I will review the traditional assumptions around the conceptual modeling of information systems and demonstrate how advances in digital technology increasingly challenge these assumptions. I will then present a new framework for conceptual modeling that is consistent with the emerging requirements of a digital world. The framework draws attention to the role of conceptual models as mediators between physical and digital realities. It identifies new research questions about grammars, methods, scripts, agents, and contexts that are situated in intertwined physical and digital realities. I will discuss several implications for conceptual modeling scholarship for systems analysis and design that relate to the necessity of developing new methods and grammars for conceptual modeling, broadening the methodological array of conceptual modeling scholarship, and considering new dependent variables.
Myths and Misconceptions about Machine Learning and How They Are Related to Software Engineering
Stefan Kramer
Johannes Gutenberg - Universität Mainz
Germany
Brief Bio
Stefan Kramer is professor of data mining at the Institute of Computer Science at Johannes Gutenberg University (JGU) Mainz and Honorary Professor at the University of Waikato in Hamilton, New Zealand. He has been active in data mining since the first conference worldwide in 1995, had more than 30 funded projects, authored more than 200 publications, and authored award-winning papers at conferences such as IEEE ICDM, ACM SIGKDD, ILP, and IEEE ICBK. He was Vice Chair of IEEE ICDM 2013 and is 2021 Program Chair of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2021). His research interests include mining structured data (sequences, strings, text, time series, trees, graphs, data in logical formalisms, etc.), stream mining, the use of prior knowledge in machine learning, and machine learning under real-world constraints such as privacy, confidentiality, fairness, and explainability.
Abstract
In the talk I will discuss machine learning (ML) myths and misconceptions, with a perspective of software and systems engineering, including requirements as well as verification and validation (V&V). The often-cited ideas about ML include: ML is always data-hungry, always opaque, can only deal with association and not causation, cannot at all deal with uncertainty, that ML is per se not within the scope of computer science and software engineering, or, vice versa, can be dealt with completely by standard tools from these areas. The talk will clarify the concepts and relationship among concepts, will point to literature that may not generally be known to audiences outside ML, and thus hopefully contribute to a better understanding of the current state of the art, the chances and risks of the methods and technologies, and potential future developments.
What Can We Learn from Play?
Panos Markopoulos
Eindhoven University of Technology
Netherlands
Brief Bio
Prof. Panos Markopoulos is a computer scientist specializing in the field of Human-Computer Interaction. He is a professor in Design for Behaviour Change at the Department of Industrial Design at the Eindhoven University of Technology. He has worked on several topics including task analysis, awareness systems, ambient intelligence, and interaction design for children. His current research concerns designing interactive technologies for rehabilitation and for playful learning. He is a founding editor of the journal Child-Compute Interaction and is currently serving as chief editor of the Behaviour & Information technology journal.
Abstract
This talk shall review the design of a number of games designed with the purpose of supporting motor learning, social skills, and encouraging physical activity and social interaction for various user groups emphasizing on the role of embodiment in interaction. It will also demonstrate how games can be valuable media for learning about people and I discuss the potential and limits of player modelling. The talk shall conclude with some general lessons and challenges for future work in this area.
How AI and Digital Are Key of Manufacturers Survival
Eric Prevost
Oracle
United States
Brief Bio
Eric Prévost has a role of Global Strategy Vice President for Discrete Manufacturing & Industry 4.0 at Oracle Industry Strategy organization. He has 21 years of experience working in digital strategy roles for Manufacturing, Banking, Healthcare and Public sectors.
Eric spent 16 years on IBM Global Services and Capgemini running then leading consulting activities on Business transformation and Digital transformation. Writer of several papers about Innovation practices for business and Artificial intelligence for the manufacturing. And co-author of a BPM: Modeling through Monitoring book. Eric is also the president of the TRIZ-France innovation association in charge of developing innovation practices in France and worldwide innovation cooperation
Abstract
Industry 4.0 trends require manufacturers rethink their digital strategy and platforms to transform their challenges into opportunities. In this turmoil period, manufacturers must use data as the new creativity, efficiency and revenue oil while the golden age of traditional delocalized mass manufacturing is over. New business models, and new supply chain, geopolitical, environmental, societal challenges are creating new opportunities. A new world of convergence between Modern Digital like Cloud, AI, IOT, Blockchain, mixed with Modern experience economy of services and manufacturing needs to be setup for getting value of new opportunities.
Impact of End User Human Aspects on Software Engineering
Brief Bio
John Grundy is Australian Laureate Fellow and Professor of Software Engineering at Monash University, Melbourne, Australia. His five year Laureate programme on Human-centric Model-driven Software Engineering aims to address some of the deficiencies in current software development practices that fail to take account of diverse software developer human characteristics and diverse software end user human characteristics. He leads the Human-centric Software Engineering (HumaniSE) lab and has published over 500 refereed papers in software tools, visual modelling languages, model-driven software engineering, software architecture, requirements engineering, and software security. He is a Fellow of Automated Software Engineering and Fellow of Engineers Australia.
Abstract
Software is designed and built to help solve human problems. However, much current software fails to take into account the diverse end users of software systems and their differing characteristics and needs eg. age, gender, culture, language, educational level, socio-economic status, physical and mental challenges, etc. I give examples of some of these diverse end user characteristics and the need to better incorporate them into requirements engineering, design, implementation, testing, and defect reporting activities in software engineering. I report on some of our work trying to address some of these issues, including: use of personas to better characterise diverse end user characteristics; extending requirements and design models to capture diverse end user needs; analysis of app reviews and JIRA logs to identify problems and ways developers try to address them; analysis of approaches to improve the accessibility of software designs for diverse end users; improved human-centric defect reporting approaches; and use of living lab co-design approaches to ensure end users are first class contributors during all phases of software development. I finish by outlining a research roadmap aiming to improve the incorporation of end user human aspects into software engineering.