Knowledge Systems

Public policy in knowledge-based economies: Foundations and frameworks

by David Rooney

Knowledge Systems and Global Advertising Services

by Joanne Roberts

Creativity and Innovation Management, Volume 9, Issue 3, pages 163–170, September 2000.

This paper explores the contribution of global advertising services to the creation and dissemination of knowledge... more This paper explores the contribution of global advertising services to the creation and dissemination of knowledge through an examination of their role in knowledge systems at a national and international level. The aim is not only to gain an understanding of global advertising services as bridges between national knowledge systems but also to examine how such services shape the institutions that constitute a knowledge system. In this way, an appreciation of the contribution of advertising services, and knowledge intensive services (KIBS) more generally, to the knowledge creation and distribution process will be developed.

Utilizing Indigenous Knowledge in Environmental Research and Assessment

by Mike Ferguson

Ferguson, M.A.D. 2001. Utilizing Indigenous Knowledge in Environmental Research and Assessment. Terra Borealis No. 2. Institute for Environmental Monitoring and Research, Labrador, Newfoundland, Canada

Textual representations and knowledge support-systems in research intensive networks.

by William P. Hall

2011: Vines, R., Hall, W.P., McCarthy, G. Textual representations and knowledge support-systems in research intensive networks. (in) Cope, B., Kalantzis, M., Magee, L. (eds). Towards a Semantic Web: Connecting Knowledge in Academic Research. Oxford: Chandos Press, pp. 145-195.

To support the increased efficacy and efficiency of research intensive networks and their impact in the world, we... more To support the increased efficacy and efficiency of research intensive networks and their impact in the world, we claim there is a need to expand the context of knowledge systems associated with research intensive networks. This idea for us involves the development of a public knowledge imperative. We suggest that textual representations expressed as knowledge claims can no longer be hidden away from the eyes of public scrutiny when there are important matters of public interest either implicitly or explicitly at stake. The recent catastrophe in the Gulf of Mexico provides an example of how particular types of knowledge, for example, procedures associated with offshore oil rigs, can rise up to become of the highest public priority almost overnight. To neglect the potency of such knowledge through a lack of public scrutiny can have devastating consequences, as the whole world has found out.
In this chapter we set out to provide a rationale as to why we think a public knowledge imperative is so important. To give expression to this imperative, we think there is a need for a new type of institutional and regulatory framework to protect and enhance the role of public knowledge. We call this framework a public knowledge space. It is public by virtue of the fact that it relies on semantic technologies and web publishing principles. But more importantly, in order to understand the multiple functions of a public knowledge space, we suggest it is first necessary to develop a detailed ontology of knowledge itself. Our ontology outlined in this chapter is broadly based because we emphasise the value of experience and lifeworlds as much as we do the importance of rigorous critiquing and transparent review. By extension, our views are slightly orthogonal to prevailing perspectives of the semantic web.

Reverse Ontology Matching

by Jorge Martinez-Gil

Jorge Martinez-Gil, José F. Aldana-Montes. Reverse Ontology Matching. Accepted for publication in SIGMOD Record.Jorge Martínez Gil, José Francisco Aldana Montes: Reverse ontology matching. SIGMOD Record 39(4): 5-11 (2010)

Ontology Matching aims to find the semantic correspondences between ontologies that belong to a single domain but that... more Ontology Matching aims to find the semantic correspondences between ontologies that belong to a single domain but that have been developed separately. However, there are still some problem areas to be solved, because experts are still needed to supervise the matching processes and an efficient way to reuse the alignments has not yet been found. We propose a novel technique named Reverse Ontology Matching, which aims to find the matching functions that were used in the original process. The use of these functions is very useful for aspects such as modeling behavior from experts, performing matching-by-example, reverse engineering existing ontology matching tools or compressing ontology alignment repositories. Moreover, the results obtained from a widely used benchmark dataset provide evidence of the effectiveness of this approach.

Optimizing Ontology Alignments by Using Genetic Algorithms.

by Jorge Martinez-Gil

Jorge Martínez Gil, Enrique Alba, José Francisco Aldana Montes: Optimizing Ontology Alignments by Using Genetic Algorithms. NatuReS 2008

In this work we present GOAL (Genetics for Ontology Alignments) a new approach to compute the optimal ontology... more In this work we present GOAL (Genetics for Ontology Alignments) a new approach to compute the optimal ontology alignment function for a given ontology input set. Although this problem could be solved by an exhaustive search when the number of similarity measures is low, our method is expected to scale better for a high number of measures. Our approach is a genetic algorithm which is able to work with several goals: maximizing the alignment precision, maximizing the alignment recall, maximizing the f-measure or reducing the number of false positives. Moreover, we test it here by combining some cutting-edge similarity measures over a standard benchmark, and the results obtained show several advantages in relation to other techniques.

An Overview of Current Ontology Meta-Matching Solutions

by Jorge Martinez-Gil

Accepted for publication in Knowledge Engineering Review

Nowadays there are a lot of techniques and tools for addressing the ontology matching problem, however, the complex... more Nowadays there are a lot of techniques and tools for addressing the ontology matching problem, however, the complex nature of this problem means that the existing solutions are unsatisfactory. This work intends to shed some light on a more flexible way of matching ontologies using ontology meta-matching. This emerging technique selects appropriate algorithms and their associated weights and thresholds in scenarios where accurate ontology matching is necessary. We think that an overview of the problem and an analysis of the existing state-of-the-art solutions will help researchers and practitioners to identify the most appropriate specific features and global strategies in order to build more accurate and dynamic systems following this paradigm.

Evaluation of two heuristic approaches to solve the ontology meta-matching problem

by Jorge Martinez-Gil

J. Martinez-Gil and J. Aldana-Montes, "Evaluation of two heuristic approaches to solve the ontology meta-matching problem," Knowledge and Information Systems, December 2009. Available: http://dx.doi.org/10.1007/s10115-009-0277-0

Nowadays many techniques and tools are available for addressing the ontology matching problem, however, the complex... more Nowadays many techniques and tools are available for addressing the ontology matching problem, however, the complex nature of this problem causes existing solutions to be unsatisfactory. This work aims to shed some light on a more flexible way of matching ontologies. Ontology meta-matching, which is a set of techniques to configure optimum ontology matching functions. In this sense, we propose two approaches to automatically solve the ontology meta-matching problem. The first one is called maximum similarity measure, which is based on a greedy strategy to compute efficiently the parameters which configure a composite matching algorithm. The second approach is called genetics for ontology alignments and is based on a genetic algorithm which scales better for a large number of atomic matching algorithms in the composite algorithm and is able to optimize the results of the matching process.