Below is secured for the future. As of 24 December 2010 it is still online at Carleton University. Dr. Robert Garigue passed away 10 January 2007 at the age of 55. He was the only person we knew then or know of today that was deliberately and completely integrating belief systems, knowledge, information, data, security, and technology as a single cyberspace.
|Dr Robert Garigue||Carleton University|
|Research Interests |
Epistemological Systems and computational epistemology
Ontology Engineering and Ontology Management
Organizations as products of Information Engineering and Constructions
Information Warfare and Information Peacekeeping
|Memetics||“Information Warfare weapons can be Physical, Syntactical, or Semantic. The use of a physical weapon will result in the permanent destruction of physical components and denial of service. A Syntactical weapon will focus on attacking the operating logic of the system and introduce delays or unpredictable behaviors. A Semantic weapon will focus its effects on destroying the trust and truth maintenance components of the system”. |
Information Warfare. – Developing a Conceptual Framework 1995
Information Warfare is not the way to solve conflict – the new agenda is to transform information warfare theory into effective information peacekeeping capabilities. ”
Managing Ontological Ambiguity: Extending The Knowledge Management Framework 2003
|Ontologies||Here are some referent Ontologies that I have built as part of my ongoing research. |
They were built using Kayvium http://www.kayvium.com/ and are in OWL format
Regional Health Registry ontology
The ontology of Sarbanes – Oxley
The ontology of control within Basel 2
Ontology of Terrorism
Here is an ontology of Computational Epistemology
They can be further extended and modified with the following tools:
CMAP COE http://cmap.ihmc.us/coe/
|Academic||PhD – Carleton University, Ottawa. Information Systems – 2005 |
Evaluating Data Interoperability: A Policy Driven Ontological Analysis Model.
Organizations seek more and more to reuse existing datasets across multiple applications. Interoperability being the ability to exchange and use information makes possible the integration of various dataset and applications into a more complex and intricate enterprise wide applications. Interoperability requires that the original concepts represented in each of the various databases, are the equivalent.
This research explores the use ontological analysis as a way to assess and identify potential interoperability issues between datasets due to concepts differences and inconsistencies. Without being able to ensure some kind of conceptual equivalence across multiple datasets the integrity of the datasets will be destroyed and as a result the organization will be making invalid assertions statements. Concepts that are used in the datasets can also be represented through ontologies.
In support of this research, the notion of a Policy Driven Ontology is introduced to establish an enterprise wide defined concept. This Policy Driven Ontology acts as a reference model and will be used to compare other domain level ontologies against it. The research proposal will present the Policy Driven Ontological Analysis framework. Eventually, the practicability of the methodology is demonstrated using corporate information. The validation of the results is done using the model through comparative analysis. By reviewing cases where the interoperability outcome is known a priori, the Policy Driven Ontological Analysis model is applied and results compared. This approach is more effective in terms of granularity and efficiency
Areas of Research: Knowledge Discovery and Knowledge Management, Strategic Information Systems Development, Advanced Decision Support Models, Intelligent Systems Design and Development, Semiotics and Visualization, Information Warfare. Three time recipient of The Forum Ph.D. Scholarship ($30, 000 research funds) – Canadian Association of University and Colleges Program. 1996/1997, 1997/1998 and 1998/1999
Master of Science in Computer and Information Systems. MSc. CIS
Claremont Graduate University Los Angeles. California. 1992
Area of specialization: Design and Development of Intelligent Systems, Large Scale System Development, Information System Policy and Planning, Decision Support Systems, Computational Epistemology. – CGS Graduate Student Council Academic Award (1992) and Top Graduate (1992)
Baccalauréat en Administration des Affaires – Méthodes Quantitatives. B.A.A. – MQ
École des Hautes Études Commerciales. Université de Montréal. 1976
Area of specialization: Quantitative Analysis and Decision Modeling, Statistics, Econometrics, and Operational Research.
|Weltanschauung||My present main focus is Ontological Engineering and Semantic Management. I am interested in Computational Epistemology and investigating related areas such as data mining, self-organization, and how computational processes “create and discover” information and knowledge. |
Knowledge is used to understand reality. It helps us adapt to the world that we live in and enables us to act with effect. However, knowledge is still a human construct even if in the near future it will be the result of an automated process. Knowledge has limitations and biases. In most instances, humanity goes through its daily routines using limited, false, and sometimes ineffective knowledge about the world. The more knowledge is based on valid evidence (justified true beliefs), the more that knowledge seems to be effective. Ultimately, knowledge as a construct is effective even though it has flaws because it captures causal relationships and explains in part how world seems to function.
Knowledge has a life cycle; it is created, it is used, and then when some better knowledge is generated as a consequence of a new theory or a new concept, then that less effective knowledge is displaced. This displacement is not done without a fight from those who have vested interest in maintaining the legitimacy of that knowledge – in some cases; it might even result in a war. Ever wonder why so many dogmatic belief systems have been the root case of wars? Maybe when people realize that knowledge does not mean truth they can start constructing new understandings together.
Computational Epistemology was the reason I became interested in Information Warfare and Knowledge Management.
Validating and falsifying knowledge are the two complementary activities that in my view define the human condition as well as determine the dynamics of humanity’s struggle for relevance. At present I am looking at how knowledge is used to make sense of the world we live in. I also believe that the next group of world-builders (after the civil, mechanical, electrical, and software engineers) will be the “applied” philosophers – the computational epistemologists. In many instances, these “applied philosophies” will be in practices software systems themselves. This is why ontological engineering is so important it is in essence the soul of the belief systems that will be embodied in the technical reality of an information system.
As the microscope permitted us to explore biology and the telescope helped us to explore cosmology, so will computers and software permit us to explore cognitive worlds that are still unseen. Computers are epistemological exploration tools. They become the playground for the exploration of the life cycle of knowledge. Eventually, computational resources will construct and falsify knowledge all by themselves.
Over the last few years, I have written on two main themes that relate to the life cycle of knowledge. I have investigated how systems destroy knowledge and how systems create knowledge. The first theme is called Information Warfare and the second is called Knowledge Management.
Information Warfare and Information Peacekeeping
The struggle for control of in a decision space is called Information Warfare. Generically these are aspects of how agents define Cooperation and Conflict in Cyberspace.
Reasoning about a new problem such as Information Warfare demands the creation of a cognitive space that offer to the investigator a representation of all the causal links between the main concepts of the domain. Here is a report about Using Cognitive Maps To Visualize Belief Systems On Information Warfare. Establishing Information Warfare concepts and their relationships are the results of both a private and public investigation. Cognitive maps have proven their value for the elucidation of new knowledge. This report describes some of the differences involved in the process of constructing static and dynamic cognitive maps. The products of these activities are different types of views. One is a structural representation, the other a declarative functional representation. The static view will be created using pen and paper; the dynamic view will be created with a software package called COPE.
“Hacking Belief Systems” was published in Al Campen and Dough Dearth in their book called CyberWar 2.0 : Myths and Realities. AFCEA Press June 98. This paper is a personal stance. I am more and more convinced that one of the danger humans will face is their own short-sighted approach to technology. Technology is not value free and without knowing it the creators of any technology perpetuate unknowingly some of their conceptual shortcomings. Belief systems today are much more than just ideas. They are made real through software and information systems. We are faced with the danger of having to live within these false worlds unless we learn to hack belief systems.
If knowledge being destroyed is done via information warfare methods and theories then knowledge management is all about creating new shared meaning and information peacemaking.
The present business environment is described as wicked and is characterized by massive and unpredictable technical, economical, and social discontinuities. To survive and thrive in this harsh environment organizations need do be able, to not just reinvent their product, or services, or even themselves as required, but to reinvent elements of the market itself. This capacity for innovation can be attributed to an organization Knowledge Management capability. This strategic function enables an organization to exploit what in the past was considered intangible assets such as know-how, and Intellectual Capital. Knowledge Management encompasses activities such as knowledge creation, storage, diffusion, exploitation and disposal.
The paper Knowledge Management: Strategic Management in an Enlightened Organization. This report will out line the main issues and methods that define Knowledge Management. It is a description and review of the core functions that an organization must do to enable a capability in the area of Knowledge Management. The paper focuses on the different perspectives that make Knowledge Management a critical new requirement for all organizations.
The term Knowledge Management is unfortunately becoming a fad. So prepare to face a next buzz word war. It is important to understand what is, and what it is not. This way you will be in a better position to exert a stabilizing influence within your group. I am also involved researching issues of Knowledge Transfer as part of the notion of risk.
Self Organizing Maps
Self Organizing Maps help in the discovery process of hidden relations. They are unsupervised learning processes. I have done research using Kohonen’s Self-Organizing Maps (SOM) to visualize large data sets. The paper is called The Application of Self-Organizing Maps to Structure Data on National Information Warfare Capabilities and it looks at how SOM can be used “discover” hidden relationships in multi-space. There is an image of the final map in the paper that shows (not so evidently because of the scale) various imaginary countries clustered together based on their Information Warfare capabilities.
This research used theoretical data to prove the process but in a later phase real world data was used. In the map you can identify the three main clusters. In the top left corner you can see the low capabilities countries clustered together. In the bottom right, you can see the high capability countries and on the diagonal between the first two you can see the average countries.
Ontological Engineering Resources
One of the main open source Ontological Engineering Environment is Protégé from the Stanford Medical Informatics
An ontology is a formal, explicit specification of a shared conceptualization. ‘Conceptualization’ refers to an abstract model of phenomena in the world by having identified the relevant concepts of those phenomena. ‘Explicit’ means that the type of concepts used, and the constraints on their use are explicitly defined. ‘Formal’ refers to the fact that the ontology should be machine readable. ‘Shared’ reflects that ontology should capture consensual knowledge accepted by the communities.
Ontologies resemble faceted taxonomies but use richer semantic relationships among terms and attributes, as well as strict rules about how to specify terms and relationships. Because ontologies do more than just control a vocabulary, they are thought of as knowledge representation. The oft-quoted definition of ontology is “the specification of one’s conceptualization of a knowledge domain.”
“Ontologies are being developed as specific concept models by the Knowledge Management community. They can represent complex relationships between objects, and include the rules and axioms missing from semantic networks. Ontologies that describe knowledge in a specific area are often connected with systems for data mining and knowledge management”. “NKOS Taxonomy of Knowledge Organization Sources/Systems” Draft, July 31, 2000. Online. Available at http://nkos.slis.kent.edu/KOS_taxonomy.htm
A partial specification of a conceptual vocabulary to be used for formulating knowledge-level theories about a domain of discourse. The fundamental role of an ontology is to support knowledge sharing and reuse.
The hierarchical structuring of knowledge about things by subcategorizing them according to their essential (or at least relevant and/or cognitive) qualities. This is an extension of the previous senses of “ontology” which has become common in discussions about the difficulty of maintaining subject indices.
The creation of a systematically ordered data structure that enhances exchange of information between computers and scientists. Ontologies enable the definition and sharing of domain-specific vocabularies.
Computational Epistemology. Knowledge Summit 2006. Moniesion Center. Queen’s School of Business. Ontario, Canada.
Technical Preface to Information Operations – All information, All languages, All The Time. The new semantics of War and Peace, Wealth and Democracy. Robert Steele. OSS publication. 2006.
Managing Ontological Ambiguity: Extending The Knowledge Management Framework Graduate Colloquium Summer 2003. Queens Center for Knowledge Based Enterprise.
Search Engines – From Algorithms to Engines of Discovery. Unpublished Research Paper. Decision Laboratory Research Group. Carleton University 80 pages. March 2002.
A Strategic Approach to Information Management: evolving from departmental applications to enterprise integration. CIO Congress Government of Canada – Lac Carling IV. May 2000.
The Application of Cognitive Mapping to Characterize Information Operation Capabilities. Institute for Operations Research and the Management Sciences. INFORMS Conference Montreal Canada. 1998.
Hacking Belief Systems. Cyberwar 2.0: Myths and Realities. Ed. Al Campen and Dough Dearth. AFCEA Press. June 98.
The Use of Cognitive Maps to Visualize Belief Systems About Information Warfare published in Information Warfare. Ed. by Winn Schwartau. 2nd edition Oct 96.
The Use of Self Organizing Maps to Structure Massive Data Sets (NATO pub RSG 30 – May 98).
Information Security Governance. Information Security Magazine. Robert Garigue, Marc Stefaniu. Feb 2004.
Information Security Governance Reporting. Robert Garigue Marc Stefaniu. Information Systems Security – Auerbach Publication. Sept. 01 2003 Volume 12 Issue 4.
A National Information Protection Agenda for Securing Government in Cyberspace. – From Provincial Action to National Security. CIO Congress. Lac Carling III. May 1999.
Knowledge Management Lac Carling Review. LTI publications1999.
rgarigue at ccs.carleton.ca