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Keynote Speakers
IC3K is a joint conference composed of three concurrent conferences: KDIR, KEOD and KMIS. These three conferences are always co-located and held in parallel. Keynote lectures are plenary sessions and can be attended by all IC3K participants.

KEYNOTE SPEAKERS LIST

Daniel O'LearyUniversity of Southern California, United States
          Title: Enterprise Ontologies: Emerging Issues from the Internet of Things and Social Media

Sophia AnaniadouUniversity of Manchester, United Kingdom
          Title: Title not yet available

Alfred InselbergTel Aviv University, Israel
          Title: Parallel Coordinates: Visual Multidimensional Geometry and its Applications

Peter F. Patel-Schneider, United States
          Title: Challenges in the Core of Ontology Support Systems

Florian MichahellesETH Zürich, Switzerland
          Title: Internet of Things – Towards New Frontiers of Knowledge Management

 

Keynote Lecture 1
Enterprise Ontologies: Emerging Issues from the Internet of Things and Social Media
Daniel O'Leary
University of Southern California
United States


Brief Bio
Daniel O'Leary is a Professor at the University of Southern California, focusing on emerging technologies (e.g., Social Media and the Internet of Things), artificial intelligence, enterprise resource planning systems and knowledge management systems. Dan received his Ph. D. from Case Western Reserve University and his master’s degree from the University of Michigan. He is the former editor of IEEE Intelligent Systems and current editor of John Wiley's Intelligent Systems in Accounting, Finance and Management. His book, Enterprise Resource Planning Systems, published by Cambridge University Press, has been translated into both Chinese and Russian. Dan’s research is been concerned with the nexus of emerging and advanced technologies and enterprise systems.


Abstract
Enterprise ontologies emerged in artificial intelligence roughly 15 years ago. Recently, the Internet of Things (IoT) and social media have developed as two of the most important technologies and philosophies of the world. Unfortunately, researchers in enterprise ontologies have largely ignored recent developments in these areas. Accordingly, this lecture will address the interaction between generation and generations of enterprise ontologies in light of the Internet of Things and Social Media. For example, I will investigate development of an ontology generated for a “supply chain of things,” evolution (i.e., generations) of a supply chain taxonomy based on data gathered from social media sources and other research issues. As part of this analysis, I will examine different emerging approaches to development of these ontologies, and their relationship to some classic notions of the semantic web.

 

Keynote Lecture 2
Title not yet available
Sophia Ananiadou
University of Manchester
United Kingdom


Brief Bio
Available soon.


Abstract
Available soon.

 

Keynote Lecture 3
Parallel Coordinates: Visual Multidimensional Geometry and its Applications
Alfred Inselberg
Tel Aviv University
Israel


Brief Bio
Alfred Inselberg received a Ph.D. in Mathematics and Physics from the University of Illinois (Champaign- Urbana) then was Research Professor there until 1966. He held research positions at IBM, where he developed a Mathematical Model of Ear (TIME Nov. 74), concurrently having joint appointments at UCLA, USC and later at the Technion and Ben Gurion University. Since 1995 he is Professor at the School of Mathematical Sciences at Tel Aviv University. He was elected Senior Fellow at the San Diego Supercomputing Center in 1996, Distinguished Visiting Professor at Korea University in 2008 and Distinguished Visiting Professor at National University of Singapore in 2011. Alfred invented and developed the multi-dimensional system of Parallel Coordinates for which he received numerous awards and patents (on Air Traffic Control, Collision-Avoidance, Computer Vision, Data Mining). The textbook "Parallel Coordinates: VISUAL Multidimensional Geometry and its Applications", Springer (October) 2009, has a full chapter on Data Mining and was acclaimed, among others, by Stephen Hawking.


Abstract
With parallel coordinates the perceptual barrier imposed by our 3-dimensional habitation is breached enabling the visualization of multidimensional problems. A panorama of highlights from the foundations to the most recent results, interlaced with applications and interactive demonstrations, are intuitively developed. By learning to untangle patterns from the displays, a powerful knowledge discovery process has evolved. It is illustrated on real datasets together with guidelines for exploration and good query design. Realizing that this approach is intrinsically limited leads to a deeper geometrical insight, the recognition of M-dimensional objects recursively from their (M-1)-dimensional subsets. In turn, this yields powerful geometrical algorithms (e.g. for intersections, containment, proximities) and applications including classification. A smooth surface is the envelope of its tangent planes. This is equivalent to representing the surface by its normal vectors, rather than projections as in standard surface descriptions. Developable surfaces are represented by curves revealing the surfaces’ characteristics. Convex surfaces in any dimension are recognized by the hyperbola-like (i.e. having two assymptotes) regions from just one orientation. Nonorientable surfaces (i.e. like the M¨obius strip) yield stunning patterns unlocking new geometrical insights. Non-convexities like folds, bumps, concavities and more are no longer hidden and are detected from just one orientation. Evidently this representation is preferable for some applications even in 3-D. The patterns persist in the presence of errors deforming in ways revealing the type and magnitude of the errors and that’s good news for the applications. We stand on the threshold of cracking the gridlock of multidimensional visualization. The parallel coordinates methodology is used in collision avoidance and conflict resolution algorithms for air traffic control (3 USA patents), computer vision (USA patent), data mining (USA patent) for data exploration and automatic classification, optimization, process control and elsewhere.

 

Keynote Lecture 4
Challenges in the Core of Ontology Support Systems
Peter F. Patel-Schneider

United States


Brief Bio
Peter F. Patel-Schneider received his Ph. D. in Computer Science from the University of Toronto in 1987. From 1983 to 1988 he was in the AI research group at Fairchild and Schlumberger. Peter then joined the AI Principles Research Department at AT&T Bell Laboratories, and then went to AT&T Labs - Research when AT&T split up in 1995. In 1997 he rejoined Bell Labs Research and remained there until 2012. Peter has taught courses at both the University of Toronto and Rutgers University. Peter's research interests center on the properties and use of Description Logics, particularly the W3C OWL Web Ontology Language. Peter designed and implemented large sections of CLASSIC, a Description Logic-based Knowledge Representation system. He designed and implemented DLP, a heavily-optimized prover for expressive Description Logics and propositional modal logics. He has performed extensive empirical evaluation of DLP and other provers for Description Logics and propositional modal logics. He developed much of OWL, and its predecessor DAML+OIL, as well as SWRL, the Semantic Web Rule Language, and OWL 2, the recent revision of OWL. Peter has recently been working on extracting semantic information from data sources, allowing data to be more easily integrated into the Semantic Web or the Web of Data. He has been determining how to use parallel computation for more effective semantic processing of large amounts of data. Peter has also been investigating how to represent and reason with services, particularly for semi-automatic service discovery


Abstract
The effective use of ontology languages, such as the W3C Semantic Web Languages OWL and RDFS, requires a complex support system, with developer interface, development cycle, knowledge acquisition, learning, application interface, and data access components as well as the core components that actually implement reasoning and querying using the ontology language. Usable versions of these core components exist for RDFS and the various versions of OWL that can reason with many large complex ontologies, and integrated systems that support the use of OWL and similar languages are now proliferating. However, the current reasoners are less capable when handling large amounts of data and expressive ontologies, and there remain daunting challenges in building reasoners supporting the full use of ontology languages.

 

Keynote Lecture 5
Internet of Things – Towards New Frontiers of Knowledge Management
Florian Michahelles
ETH Zürich
Switzerland


Brief Bio
At ETH Zurich Florian Michahelles heads the Auto-ID Lab ETH Zurich/HSG and directs research at the forefront of mobile commerce innovations and global standards for supply-chain optimization. Additionally, he coordinates the research agenda of the global Auto-ID Labs network comprising labs at Fudan, KAIST, Keio University, MIT, Cambridge, and ETH Zurich/St. Gallen. His research interests include RFID-based approaches against anti-counterfeiting, NFC, and and mobile consumer apps in the retail domain. Michahelles received a PhD from ETH Zurich for research in wearable computing and ubiquitous computing. He holds a M.Sc (Diplom-Informatiker Univ.) degree in computer science and psychology from the Ludwig-Maximilians-University of Munich and was an MIT Sloan Visiting Fellow in 2000. Michahelles has published 50+ papers in international journals, conferences and scientific workshops. He is currently chairing the IoT2012, MuM2012 and NFC2013 conferences.


Abstract
With the emergence of networked appliances, tagged objects and products, and computing and communication capabilities in everyday devices, the Internet is reaching out to the real-world. Various application areas from retail to supply-chain logistics and from smart grid to traffic monitoring will accumulate massive amount of data which has to managed and processed in order to derive value. This talk will introduce to the main concepts of Internet of Things, present specific applications and open the space for future research challenges.