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
Jay Liebowitz, University of Maryland University College, U.S.A.
Title: Knowledge Management and e-Learning: Putting Theory into Practice
Carole Goble, University of Manchester, U.K.
Title: Accelerating Scientists' Knowledge Turns
Mayer Aladjem, Ben-Gurion University of the Negev, Israel
Title: Probabilistic Modeling, Projection Pursuit and Blind Source Separation
Guus Schreiber, VU University Amsterdam, The Netherlands
Title: Principles for Knowledge Engineering on the Web
Jan L. G. Dietz, Delft University of Technology, The Netherlands
Title: Intellectually Managing Organized Complexity
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Jay Liebowitz University of Maryland University College U.S.A. |
Brief Bio
Dr. Jay Liebowitz is the Orkand Endowed Chair of Management and Technology in the Graduate School of Management & Technology at the University of Maryland University College (UMUC). He previously served as a Professor in the Carey Business School at Johns Hopkins University. He was ranked one of the top 10 knowledge management researchers/practitioners out of 11,000 worldwide. He was recently ranked #2 worldwide in KM Strategy, according to the January 2010 Journal of Knowledge Management. At Johns Hopkins University, he was the founding Program Director for the Graduate Certificate in Competitive Intelligence and the Capstone Director of the MS-Information and Telecommunications Systems for Business Program, where he engaged over 30 organizations in industry, government, and not-for-profits in capstone projects.
Prior to joining Hopkins, Dr. Liebowitz was the first Knowledge Management Officer at NASA Goddard Space Flight Center. Before NASA, Dr. Liebowitz was the Robert W. Deutsch Distinguished Professor of Information Systems at the University of Maryland-Baltimore County, Professor of Management Science at George Washington University, and Chair of Artificial Intelligence at the U.S. Army War College.
Dr. Liebowitz is the Founder and Editor-in-Chief of Expert Systems With Applications: An International Journal (published by Elsevier), which was ranked #1 worldwide in the OR/MS category according to 2008 Thomson Impact Factors. He is a Fulbright Scholar, IEEE-USA Federal Communications Commission Executive Fellow, and Computer Educator of the Year (International Association for Computer Information Systems). He has published over 40 books and a myriad of journal articles on knowledge management, intelligent systems, and IT management. His most recent books are Knowledge Retention: Strategies and Solutions (Taylor & Francis, 2009), Knowledge Management in Public Health (Taylor & Francis, 2010), and Knowledge Management and E-Learning (Taylor & Francis, 2011). He has lectured and consulted worldwide. He can be reached at jliebowitz@umuc.edu.
Abstract
Knowledge management and e-learning have synergistic effects. They both contain elements of leveraging knowledge internally and externally, and both could add to the strategic intelligence of the organization. The combination of these two areas is just starting to evolve, per the evidence of the Knowledge Management and E-Learning Journal and the recent book publication of "Knowledge Management and E-Learning" (Liebowitz and Frank, eds., Taylor & Francis/CRC Press, 2011). Closer attention is warranted in the integration of these fields in order to advance the current state-of-the-art. The presentation will talk about these areas from a strategic intelligence framework, and will show examples of how the theory can be translated into practice.
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Carole Goble University of Manchester U.K. |
Brief Bio
Carole Goble is a full professor in the School of Computer Science at the University of Manchester. She researches semantic technologies, distributed systems, data integration and social computing to solve information management problems for life scientists and other scientific disciplines.
She directs the myGrid e-Science consortium (http://www.mygrid.org.uk) which focuses on automated workflow-based scientific pipelines and e-laboratories for research and researchers.
She is well known for turning research into production software and services such as: the Taverna scientific workflow system; the myExperiment crowd-sourced workflow sharing platform; the BioCatalogue socially curated catalogue of web services; the SEEK data/models sharing platform for pan-European Systems Biology; and the MethodBox for socially sharing statistical methods and survey data. A partner in the UK's Open Middleware Infrastructure Institute and Software Sustainability Institute, she is currently building infrastructure for several EU scientific programmes in Systems Biology, Biodiversity, Astro-Physics, Astronomy and Digital Library preservation. In 2008 she received the inaugural Microsoft Jim Gray award for outstanding contributions to e-Science and in 2010 she was elected a Fellow of the Royal Academy of Engineering.
Abstract
Science is knowledge work, cumulatively building on prior results. In particular scientific method and scholarly communication are about facilitating "knowledge turns" - that is, the turning of observation and hypothesis through experimentation, comparison, and analysis into new, pooled knowledge. Turns depend on the flow and availability of knowledge.
They also depend on scientists coordinating and collaborating, and in particular a "long tail" of small researcher units who contribute to, and benefit from online resources and the accumulated pool of know-how, know-what and know-why. My own research and tools - scientific workflows and services, social crowd-sourcing and sharing, and semantic technologies - focus on aiding these "long tail scientists" to accelerate knowledge turns, including the development of community ontologies.
Knowledge turns must get faster. Long tail scientists are wrestling with vast, new scales of information, rapid changes in data, richly interconnected knowledge and collaboration/coordinations. Knowledge practices work within the social and cultural systems that scientists currently operate in if they are to be truly adopted and make any useful impact. However, our scientists are operating in outdated models of scholarly publishing. Computational and data intensive methods are on the increase but much of the scientific knowledge generated is not readily available, reproducible, reusable or repeatable.
To really accelerate knowledge and liberate our scientific long-tail we need a greater openness to increase productivity, widen equity and offer ethical transparency. Ecosystems of Research Objects could be the future currency of scholarly knowledge; that is, packaged, interconnected and citable units of active knowledge combining remote and local source data, results data, methods, protocols, presentations, lab books, experts.
So what are scientific knowledge assets? What are the trends and challenges knowledge flows in science? How would we preserve, curate, reproduce or publish complex, online digital Research Objects? What are the prospects for the "Executable Publication"? What are social issues that speed up and slow down knowledge turns? How can we get scientists to share? How can you help?
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Mayer Aladjem Ben-Gurion University of the Negev Israel |
Brief Bio
Mayer Aladjem received the M.Sc. degree in electrical engineering and applied mathematics and PhD degree in electrical engineering from the Technical University, Sofia, Bulgaria. He was an associate Professor of Biomedical Cybernetics in Bulgarian Academy of Sciences. He joined the Department of Electrical and Computer Engineering at Ben-Gurion University of the Negev, Israel in 1990 and he is currently an associate Professor in this department. His research interests are Statistical pattern recognition; Neural networks for pattern recognition; Multivariate density estimation; Blind source separation; Independent component analysis; Feature extraction, reduction, and analysis; Applications in signal and image processing. Prof. Aladjem served as Chairman of the International Symposium on Advances in intelligent data analysis (AIDA'2001), Bangor, Wales, U.K. and was Guest Editor of the Special Edition: "Advanced Data Analysis and Biomedical Applications" in the journal Knowledge-Based Intelligent Engineering Systems. He is currently an Associate Editor of the journal Pattern Analysis& Applications. For more information see http://www.ee.bgu.ac.il/~aladjem/
Abstract
In this talk I will present methods for estimation (approximation) of n-variate probability density functions using a statistical techniques named projection pursuit (PP) and independent component analysis (ICA). We seek a Gaussian mixture model (GMM) of an n-variate probability density function. Usually the parameters of GMMs are determined in the original n-dimensional space by optimizing a maximum likelihood (ML) criterion. A practical deficiency of this method of fitting GMMs is its poor performance when dealing with high-dimensional data since a large sample size is needed to match the accuracy that is possible in low dimensions. We will present recent methods for fitting the GMM based on the PP and ICA strategies. These GMMs are highly constrained and hence its ability to model structure in subspaces is enhanced, compared to a direct ML fitting of a GMM in high dimensions. The comparisons with ML fitting of GMM in n-dimensions show that the PP and ICA methods are attractive choices for fitting GMMs using small sizes of training sets.
An important application of these methods is blind source separation (BSS). I will present several examples for BSS. The presented methods can be applied to knowledge discovery, information retrieval, mining high-dimensional data, data visualization and many other practical problems.
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Guus Schreiber VU University Amsterdam The Netherlands |
Brief Bio
Guus Schreiber is a professor of Intelligent Information Systems at the Department of Computer Science department of the VU University Amsterdam.
His research interests are mainly in knowledge and ontology engineering, with a special interest for applications in the field of cultural heritage. He was one of the key developers of the CommonKADS methodology. He acts as chair of W3C groups for Semantic Web standards such as RDF, OWL, SKOS and RDFa. His research group is involved a wide range of national and international research projects.
He is now project coordinator of the EU Integrated Project NoTube concerned with integration of Web and TV data with the help of semantics and was previously Scientific Director of the EU Network of Excellence "Knowledge Web".
For more information see http://www.cs.vu.nl/~guus/
Abstract
With the advent of the Web and the efforts towards a Semantic Web the nature of knowledge engineering has changed drastically. In this talk I will discuss some guiding principles for knowledge engineering on a Web scale. We illustrate these principles with examples from knowledge-intensive Web applications in areas such as digital heritage, social TV, and e-humanities. Web-based knowledge engineering is a key component of the emerging discipline of Web Science, which studies the virtual world as a relatively new phenomenon for which scientific laws and theories of the physical world do not always hold.
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Jan L. G. Dietz Delft University of Technology The Netherlands |
Brief Bio
Jan Dietz is full professor in Information Systems Design at Delft University of Technology (The Netherlands). He holds a Master degree in Electrical Engineering and a Doctoral degree in Computer Science. He has published over 200 scientific and professional articles as well as several books. His current research interests are in Enterprise Architecture, Enterprise Ontology, and Enterprise Governance, the three pillars of Enterprise Engineering. Before his academic career, he has been in business automation for 10 years.
He is the spiritual father of DEMO (Design & Engineering Methodology for Organizations), as well as co-founder and honorary chairman of the DEMO Center of Expertise (http://www.demo.nl). For developing the emerging discipline of Enterprise Engineering, he chairs the international research network CIAO! (Cooperation & Interoperability - Architecture & Ontology) (http://www.ciaonetwork.org). He also acts as editor-in-chief of a book series on Enterprise Engineering, published by Springer. He can be reached at j.l.g.dietz@tudelft.nl.
Abstract
The notion of organized complexity, as defined by Gerald Weinberg, seems to be a good indication for the kind of artifacts that professionals in organization and information system science are dealing with. As Edsger Dijkstra already pointed at, our primary task in dealing with those artifacts is to manage intellectually their inherent complexity. Five intellectual techniques will be presented and discussed that provide adequate help in mastering complexity: 1) separation of concerns, 2) use of abstraction, 3) devising proper concepts, 4) verification by instantiation, and 5) validation from ontology. Particular emphasis will be put on the third one, since it appears that many currently popular methods in systems development lack a proper conceptual basis. As a step towards improving this situation, ideas about a new theoretical foundation of information systems are presented and discussed.
