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Keynote Lectures

The Two Pillars
Robert Pergl, Czech Technical University in Prague, Czech Republic

Digitalization: A Meeting Point of Knowledge Management and Enterprise Engineering
Eduard Babkin, National Research University “Higher School of Economics”, Russian Federation

A Tale Rarely Told
Karl-Erik Sveiby, Hanken School of Economics, Finland

To Combine or Not to Combine: Ranking and Scoring for Data Analytics and Knowledge Discovery
Frank Hsu, Fordham University, United States

Kandinsky Pattern
Heimo Müller, Medical University of Graz, Austria

 

The Two Pillars

Robert Pergl
Czech Technical University in Prague
Czech Republic
 

Brief Bio
Dr. Robert Pergl is an Assistant Professor at Department of Software Engineering, Faculty of Information Technologies of Czech Technical University in Prague, Czech Republic, where he founded "Centre for Conceptual Modelling and Implementation", a group focusing on research, development and applications of methods and tools for ontological engineering, enterprise engineering, software engineering and data stewardship. Apart from his publishing work, Dr. Pergl is also a General Chair of EOMAS Workshop, a representative in the CIAO! Enterprise Engineering Network and National Node Committee member of ELIXIR Czech Republic.


Abstract
In his keynote, Dr. Pergl is going to discuss two pillars of intellectual human endeavour: naming and hierarchies. He digs into the essence of these corner-stones of conceptualisation and explores their presence, significance and forms in various disciplines. Challenges of naming and hierarchies in engineering disciplines are discussed and "lessons learned" are formulated.



 

 

Digitalization: A Meeting Point of Knowledge Management and Enterprise Engineering

Eduard Babkin
National Research University “Higher School of Economics”
Russian Federation
 

Brief Bio
Eduard Babkin is a tenured professor in the department of Information Systems and Technologies of National Research University Higher School of Economics (HSE Nizhny Novgorod, Russia), where he takes a position of the head in the research laboratory of theory and practice of decision support systems (TAPRADESS). Also Eduard Babkin has been working in IT industry, he has more than twenty years of practical experience in architecting, software design and project management of complex distributed information systems. In 1993 Eduard Babkin obtained BS degree in Informatics and started the academic carrier as a lecturer. In 2007 Eduard Babkin obtained his PhD degree in Computer Science in National Institute of Applied Sciences (Rouen, France). Since that time he has been carried out scientific research in enterprise engineering, multi-agent systems, knowledge management as a principal investigator or a team lead. Currently Eduard Babkin is mostly interested in multidisciplinary studies where advances of conceptual modeling, distributed algorithms and multi-agent systems were fused with corresponding domains of sociology and economics.


Abstract
Digital transformation of organizations became a significant research and engineering challenge worldwide. In many cases digitalization requires extraction of tacit individual, interpersonal or organizational knowledge to explicit machine-readable forms and their conscious application during enterprise reengineering. Successful accomplishment of these tasks vitally relies on a rigorous scientific theory and formal methods. This lecture demonstrates how the technique of evolvable domain-specific languages solves several problems of knowledge management in organizations, the enterprise ontology approach facilitates comprehensive understanding of socio-technical systems, and how fusion of these approaches may provide a reliable tool for digitalization. Illustration of results obtained in several research projects supports the main statements of the lecture.



 

 

A Tale Rarely Told

Karl-Erik Sveiby
Hanken School of Economics
Finland
 

Brief Bio
Karl-Erik is often described as one of the”founding fathers” of knowledge management due to his seminal works during the early ”Nordic KM movement” in the 1980’s, such as Managing Know-How (w. Tom Lloyd) Bloomsbury 1987; The Invisible Balance Sheet (w. the Konradgroup) Affärsvärlden 1990, and; the world’s first book titled Knowledge Management, (Sw. Kunskapsledning) Affärsvärlden 1990. He was appointed Professor in Knowledge Management at Hanken in 2001 and Emeritus in 2013. Previous appointments include honorary professorships at Queensland University of Technology, Griffith university, Macquarie Graduate School of Management in Australia and Hongkong Polytechnic University. He is on the editorial board of Journal of Intellectual Capital and has been on Management Decision, among others. He has published a.o. in journals such as Journal of Knowledge Management, Leadership, Sustainable Development and written 13 books among them the bestseller The New Organizational Wealth Berret-Koehler 1997 and the co-edited Challenging the Innovation Paradigm Routledge 2012. Most of his books and articles can be downloaded free from www.sveiby.com. Unlike most academics, he has been a manager, among others a co-owned publishing house, which became Sweden´s largest in financial and trade press. He has consulted worldwide and developed a wide range of tools that help managers and consultants implementing IC and KM concepts in practice, among them the Intangible Assets Monitor and Tango (w. Klas Mellander), the business simulation that helps managers experience how to create value from knowledge. His mission is to help organisations become better for people.


Abstract

I have been for 35 years in what has become known as Knowledge Management in roles as corporate manager, consultant, KM tool developer and researcher. I will tell a story about what I have learned about the consequences that our work has enabled and contributed to.

During this time, KM practices have become extremely efficient in collecting, transferring, storing and disseminating information in ways that we couldn’t even dream of. This is all down to massive investments in information and communication technology and the related know-how. KM-practitioners and scholars have contributed to the efficiency of practically all types of manufacturing, transport, finance, governance, management systems, public services, agriculture – the list goes on and on and it accelerates at the speed of Moore’s Law.

But it is high time for self-reflection. To cite TS Eliot: “Where is the knowledge we have lost in information?” Where are the people lost in the computer systems? Are they just products, sources of our income, objects of analysis and surveillance? Why are we doing this? For whom are we doing it? Are KM practices and research only enabling the construction of the bars of iron cages, ultimately for ourselves?
Is KM becoming bad for people, society and the planet?



 

 

To Combine or Not to Combine: Ranking and Scoring for Data Analytics and Knowledge Discovery

Frank Hsu
Fordham University
United States
 

Brief Bio
D. Frank Hsu is the Clavius Distinguished Professor of Science, a professor of Computer and Information Science, and director of the Laboratory of Informatics and Data Mining at Fordham University in New York, USA. He was chair of the CIS Department and associate dean of the Graduate School of Arts and Sciences. He held visiting positions at JAIST, Keio University, MIT, Taiwan University, and University of Paris-Sud. Hsu’s main research interests are: interconnection networks, graph database, micro- and macro-informatics, data science, ensemble method, and combinatorial fusion algorithm. He has co-authored/co-edited 40 books and book chapters and published over 200 technical papers. He has given over 400 presentations worldwide. Hsu served or is serving on many editorial boards including IEEE Transactions on Computers, IEEE Transactions on Reliability, IEEE Systems Journal, Brain Informatics, and Journal of Interconnection Networks. Among the honors and awards he received are IEEE-AINA Conference Best Paper Award, Foundation Fellow of ICA, Fellow of ICIC, Fellow of the New York Academy of Sciences; and IBM Faculty Award. Hsu received his M.S. from the University of Texas at El Paso and Ph.D. from the University of Michigan. He is a Senior member of the IEEE. (http://storm.cis.fordham.edu/~hsu)


Abstract
In the big data era, scientific discovery of knowledge tends to have fewer but sophisticated experiments with more variables (cues, criteria, features, attributes, or indicators) and larger number of hypotheses. As such, various ensemble methods combining multiple models or multiple machine learning algorithms are frequently used to improve forecasting, prediction, decision making, and policy formulation. However, it remains to be a great challenge to know when and how to combine these models or algorithms. This keynote talk will cover the design of intelligent scoring systems and discuss when and how these systems should be combined using a rank-score characteristic (RSC) function and the notion of cognitive diversity. Examples will include figure skating judgement, information retrieval systems, intrusion detection, wireless network selection, and multi-layer combinational fusion.



 

 

Kandinsky Pattern

Heimo Müller
Medical University of Graz
Austria
 

Brief Bio
Heimo Müller, born in Austria not far from the Slovenian Carinthian border, studied mathematics in Graz and Vienna. He began his professional career in computer graphics and multimedia at Joanneum Research at the Institute for Digital Image Processing and Computer Graphics and at the Institute for Information Systems. His work in the field of film and video, including storage, indexing, archiving and restoration, is particularly noteworthy. As Marie-Curie Research Fellow at the Free University of Amsterdam he was involved in the modelling of semantic structures in moving image sequences and back in Graz Heimo Müller was the founding head of the Information Design course at the University of Applied Sciences Joanneum. Since a decade he is at the Medical University of Graz working on data management in biobanka and precision medicine. In Particular his research topics today are  visual computing, information design, digital pathology and – most important – explanability of AI in the medical domain. 


Abstract
Available Soon



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