The keynote will open with a virtual introduction of the Creating Secure Societies collaboration by initiators Karen van Oudenhoven-van der Zee (dean Faculty of Social Sciences, VU University) and Theo Toonen (dean faculty Behavioral Management and Social Sciences, University of Twente). After the opening we will have a round table discussion on a variety of (creeping) safety crises with, amongst others, societal stakeholders Bas Boïng (National Police, UT) Badia Bentayeb (Senior Advisor Digital Security & PhD candidate - Municipality of Amsterdam) Jacqueline van Stekelenburg (Professor Social Change and Conflict VU) and social scientist Peter de Vries (UT).
The term “Big Data” is about 10 years old. However, each major period of IT and of computer science has had its own perception of what is “big” when it comes to data. While the term in the past was directly connected to storage sizes, more recently it refers to the fact that everything we do online leaves a digital data trace which can be collected, saved, immediately or later analyzed, and eventually used (or misused). Presently, techniques from mathematics and computer science that are employed for these purposes considerably accelerate the area of machine learning. While this will persist for some time to come, big data might in the future impact such diverse topics as currency and algorithm design. This talk will try to give a perspective on the different phases within the development of big data.
ABOUT GOTTFRIED VOSSEN
Dr. Gottfried Vossen has been a Professor of Computer Science in the Department of Information Systems at the University of Muenster in Germany since 1993. He is a Fellow of the German Computer Science Society and an Honorary Professor at the University of Waikato Management School in Hamilton, New Zealand. He is European Co-Editor-in-Chief of Elsevier's Information Systems - An International Journal, and a Director of the European Research Center for Information Systems (ERCIS) in Muenster. His research interests include conceptual as well as application-oriented challenges concerning databases and information systems, business process modelling, digitalization, digital business models, cloud computing, and big data. Dr. Vossen is CEO and a co-founder of Janus Innovation GmbH and of the consulting cooperative digital ganz normal eG, both headquartered in Ahaus, which advise enterprises in data- and process-related challenges in the context of digitalization.
Mariëlle goes on to talk about her keynote: "My keynote is about predictive maintenance, or, in good Dutch, predictive maintenance". In 'predictive maintenance', we use sensor data and historical fault data to predict – with the help of big data and artificial intelligence – when failures in devices can occur and how they will then proceed. This helps with planning maintenance – because if you know what's coming, you can respond to that and make sure that, for example, you replace a machine part, just before it breaks down. This saves costs, reduces interruptions and reduces nuisance. So a win-win situation."
Working on trust in data
But what does it take for this 'predictive maintenance'? Quite a bit, says Mariëlle: "There are already all kinds of (technological) cleverness with which we can collect data on the time and how we can best perform maintenance, such as sensors and optimization techniques. But how do we ensure that all the information we get is well-matched? And what sensors do we need and where exactly should they be? What we also don't know well is: how, for example, maintenance workers deal with the (predictive) information that is available? What can and dare them to do?
Step by step to data-driven maintenance
Behaviour, therefore, plays a key role. A solution is an important place, which is far from always there in our traditional – human-driven culture– that is far from there. The large-scale introduction of 'predictive maintenance' can only be done if companies transform from a traditional culture to a data-driven culture – into a corporate culture in which data and artificial intelligence are integrated and embedded in the organizational and work processes. How that can be done, what solutions there are and what principles companies can help with this, I will tell you in my keynote. I tell you how your organisation – step by step – is also reaping the benefits of data-driven maintenance."