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Keynote Lectures

From Representation to Mediation: Modeling Information Systems in a Digital World
Jan Recker, University of Cologne, Germany

Big Data Integration
Philippe Cudré-Mauroux, University of Fribourg, Switzerland


From Representation to Mediation: Modeling Information Systems in a Digital World

Jan Recker
University of Cologne

Brief Bio
Prof Dr Jan Recker is Alexander-von-Humboldt Fellow, Chaired Professor for Information Systems at the University of Cologne, and 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.

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.



Big Data Integration

Philippe Cudré-Mauroux
University of Fribourg

Brief Bio
Philippe Cudre-Mauroux is a Full Professor and the Director of the eXascale Infolab at the University of Fribourg in Switzerland. He received his Ph.D. from the Swiss Federal Institute of Technology EPFL, where he won both the Doctorate Award and the EPFL Press Mention in 2007. Before joining the University of Fribourg, he worked on information management infrastructures at IBM Watson (NY), Microsoft Research Asia and Silicon Valley, and MIT. He recently won the Verisign Internet Infrastructures Award, a Swiss National Center in Research award, a Google Faculty Research Award, as well as a 2 million Euro grant from the European Research Council. His research interests are in next-generation, Big Data management infrastructures for non-relational data and AI. Webpage: http://exascale.info/phil

Until recently, structured (e.g., relational) and unstructured (e.g., textual) data were managed very differently: Structured data was queried declaratively using languages such as SQL, while unstructured data was searched using boolean queries over inverted indices. Today, we witness the rapid emergence of Big Data Integration techniques leveraging knowledge graphs to bridge the gap between different types of contents and integrate both unstructured and structured information more effectively. I will start this talk by giving a few examples of Big Data Integration. I will then describe two recent systems built in my lab and leveraging such techniques: ZenCrowd, a socio-technical platform that automatically connects Web documents to semi-structured entities in a knowledge graph, and Guider, a Big Data Integration system for the cloud.