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Keynote Lectures

Context-aware Knowledge Management for Socio-Cyber-Physical Systems: New Trends towards Human-machine Collective Intelligence
Alexander Smirnov, SPIIRAS, Russian Federation

From Activity- to Data-centric Approaches to Business Process Management: Challenges, Technologies, Applications
Manfred Reichert, Ulm University, Germany

Hybrid Intelligence: AI Systems That Collaborate with People Instead of Replacing Them
Frank van Harmelen, The Hybrid Intelligence Center & Vrije Universiteit Amsterdam, Netherlands

Persistent Identification for Interoperable Data Management and Preservation
Stefan Decker, RWTH Aachen University, Germany

 

Context-aware Knowledge Management for Socio-Cyber-Physical Systems: New Trends towards Human-machine Collective Intelligence

Alexander Smirnov
SPIIRAS
Russian Federation
 

Brief Bio
Alexander Smirnov is a Head of Computer Aided Integrated Systems Laboratory, St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences (SPIIRAS). He received his Ph.D from St. Petersburg State University of Electrical Engineering (1984) and Dr.habil. from SPIIRAS (1994), and became a Full Professor in 1998. Also, he is a Professor and a Head of International Laboratory on Intelligent Technologies for Socio-Cyberphysical Systems, ITMO University, St. Petersburg (from 2014), and a Founder of Joint Master Program on Business Informatics between ITMO University and Rostock University (Germany). He has been involved in projects sponsored by Ford, Nokia, Festo, US DoD, European Research Programs (Information Society Technologies, Esprit, Eureka/Factory, etc.), and Russian agencies in the areas of distributed intelligent systems, ontology management, intelligent decision support systems, etc.


Abstract
The competitiveness of companies and organizations heavily depends on how they maintain and access highly decentralized up-to-date information & knowledge coming from various resources located in their Socio-Cyber-Physical Systems. Such systems tightly integrate heterogeneous resources of the physical world and IT (cyber) world together with social networking concepts. Context-Aware Knowledge Management is becoming de facto one of the required business strategies in these systems. Its goal is to facilitate knowledge transfer and sharing in the context of business structures and activities bound together with the cultural norms. This keynote presents new trends (including role-based organization, dynamic motivation mechanisms and multi-aspect ontology) in knowledge management for socio-cyber-physical systems. Such trends can facilitate creation of innovative IT & HR environments based on human-machine collective intelligence, where information & knowledge are shared between participants and across collectives of participants, who can be both people (collective intelligence as the methods used by humans to act collectively for problem solving) and software services (based on artificial intelligence models). The keynote considers examples of trends and their implementation experience in a global production company.



 

 

From Activity- to Data-centric Approaches to Business Process Management: Challenges, Technologies, Applications

Manfred Reichert
Ulm University
Germany
 

Brief Bio
Manfred is Professor of Computer Science and Director of the Databases and Information Systems Institute at Ulm University, Germany. His research spans across the fields of digital services, information systems, business process management, and process flexibility. Moreover, he has been engaged in many projects related to healthcare, logistics, automotive engineering, and Industry 4.0. Currently, he collaborates with several large companies, including Daimler,BMW Uhlmann Pac Systems, and adesso. Manfred was PC co-chair of the BPM’08, CoopIS’11, and EDOC’13 conferences, and general chair of the BPM’09 and EDOC’14 conferences as well as the BPM’15 workshops. He received several best paper wards (e.g. OTM’05, EDOC’08, AIMS‘17) as well as the BPM Test of Time Award at the BPM’13 conference. Finally, he is co-founder of the AristaFlow Ltd. and co-author of a Springer book on process flexibility.


Abstract
The utmost importance of data for knowledge-intensive business processes has led to the emergence of data-centric process management approaches. By tightly integrating process and data, which more or less constitute two sides of the same coin, these approaches differ significantly from the widely used activity-centric process paradigm, aiming at the support of semi- or unstructured  processes and offering by far the highest flexibility. The progress of a data-centric process depends on the availability of data rather than on the completion of black-box activities. Moreover, the focus has shifted from large, monolithic processes towards small data-driven processes (e.g., object lifecyces), which are running concurrently, but need to interact with each other to reach a given business goal.
The keynote speech will give insights into the evolution from activity- to data-centric business process management (BPM) approaches with a focus on process flexibility issues. Moreover, it will deal with fundamental concepts, features and enabling technologies of data-centric approaches to BPM. Finally, it will discuss how data-driven and data-centric process management approaches open up new avenues with respect to the engineering, automation, and monitoring of large-scale business processes in the era of digitization and Industry 4.0.



 

 

Hybrid Intelligence: AI Systems That Collaborate with People Instead of Replacing Them

Frank van Harmelen
The Hybrid Intelligence Center & Vrije Universiteit Amsterdam
Netherlands
 

Brief Bio
Frank van Harmelen has a PhD in Artificial Intelligence from Edinburgh University, and has been professor of AI at the Vrije Universiteit since 2001, where he leads the research group on Knowledge Representation. He was one of the designers of the knowledge representation language OWL, which is now in use by companies such as Google, the BBC, New York Times, Amazon, Uber, Airbnb, Elsevier, Springer Nature, XMP, and Renault among others. He co-edited the standard reference work in his field (The Handbook of Knowledge Representation), and received the Semantic Web 10-year impact award ifor his work on the open source software Sesame (over 200.000 downloads). He is a Fellow of the European Association for Artificial Intelligence, member of the the Dutch Royal Academy of Sciences (KNAW), of The Royal Holland Society of Sciences and Humanities (KHWM) and of the Academia Europaea, and is adjunct professor at Wuhan University and Wuhan University of Science and Technology in China.


Abstract
Much of current AI research is implicitly aimed at building systems that replace humans: self-driving cars to replace Uber drivers, translation software replacing interpreters, image analysis software replacing radiologists. But it's becoming increasingly clear that machine intelligence will be rather different from human intelligence. It is therefore more interesting to build AI systems that collaborate in hybrid teams of people and machine, in order to combine their complementary skills. This will require that we start asking a whole set of new research questions. How to equip AI systems with a "theory of mind" to make them collaborative? How to make AI systems adaptive to changes in the team and the environment? How to instill moral values into these systems? And of course how to make them explainable? We will outline a research agenda for hybrid intelligence and present some early results from researchers worldwide into hybrid intelligence.



 

 

Persistent Identification for Interoperable Data Management and Preservation

Stefan Decker
RWTH Aachen University
Germany
 

Brief Bio
Prof. Dr. Stefan Decker is Professor of Databases and Information Systems at RWTH Aachen University and Managing Director of the Fraunhofer Institute for Applied Information Technology in Birlinghoven.
Previously, he was Professor of Digital Enterprise at the National University of Ireland, Galway, Director of the Digital Enterprise Research Institute (DERI) and the Insight Center in Galway, Ireland, Research
Assistant Professor at the Information Sciences Institute of the University of Southern California, USA, and held research positions at Stanford University and the University of Karlsruhe (now KIT).
He is an elected member of the Royal Irish Academy and a Fellow of Engineers Ireland.

Since 1998 he has been working with linked data and semantic web technology. His current research interests include knowledge representation and data modeling, research data management, and applications for linked data technologies. More information on Prof. Decker's publications can be found at http://www.stefandecker.org/ and at Google Scholar. 


Abstract

The digitally connected economy requires infrastructure supporting the open exchange, reuse and integration of constantly evolving data. One of these infrastructure is identification via persistent identifiers (PIDs). While this concept of PIDs is not new, requirements for PIDs have rarely been investigated.

After a brief survey of relevant concepts and related work, I will present some recent results from my laboratory, where we work on interoperable data management and preservation systems for evolving data on the Web. I will discuss the need for a general data interoperability and persistence layer for the Web, addressing issues such as link rot, reliable resource referencing and citation, authenticity, integrity and trust. 



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