Computing and Information Systems - Theses
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ItemModelling knowledge for scientific collaboration on the semantic web( 2006)This thesis analyses the modelling of knowledge in relation to knowledge sharing in scientific collaboration on the semantic web. It outlines both general and specific conceptual frameworks, as well as hypotheses for the description of the knowledge models. The key motivation form this work is drawn from the vision of e-science research agenda to support effective communication and to enable automated task achievement in scientific research based on accessible data and information on the web. A scientific collaboration is a widely distributed networking scientific community. The internet has become the major vehicle for the distributed groups in scientific collaborations to share knowledge related to their research. The next generation web, called the semantic web promises to dispense with some of the human effort to both conserve and operationalise part of the shared knowledge. A fundamental requirement to move towards a semantic-aware web environment necessitates formal and explicit terminologies based on knowledge models. A knowledge model is an extendable conceptual framework of knowledge. We have proposed two types of knowledge models for scientific collaboration, namely domain and task knowledge models. Hence, the key objective of this research work is to characterise the task and domain knowledge models of a scientific collaboration with particular intention of increasing the confidence of knowledge sharing and reuse on the semantic web. We claim that a shared terminology must agree with the purpose and ultimate use of the model. Consequently, we advocate the modelling of the directively and paradigmatically share knowledge in a scientific collaboration. The directively share knowledge is identified with the ratified and widely disseminated general domain knowledge motivated by general informational needs in a domain. The paradigmatically shared knowledge alludes to the sharing of purposive domain knowledge motivated by the needs of common tasks of researchers in a scientific collaboration. We highlight that both content and context are important for sharing of purposive domain knowledge in a scientific collaboration. We have adapted some previous works on the representation of mathematical expressions to arrive at a general framework for representing mathematical relations involving concepts in a domain knowledge model. Similarly, we have adapted and extended an existing set of evaluation criteria to formatively evaluate the knowledge models being built. The concrete implications of the work reported in this thesis are applied to model knowledge within the domain of Experimental High Energy Physics (EHEP), specifically the Belle scientific collaboration. We sum up the key contributions of this thesis as follows: • Analysis of the requirements in developing knowledge models for sharing of knowledge in a scientific collaboration on the sematic web. • A task model to make explicit the task functionality, which includes the task input-output information that can be relied upon as the context for modelling of purposive knowledge of a domain. • A method to identify, analyse, conceptualise and model general and purposive knowledge of a domain. • An approach to introduce explicit mathematical notation into a web-portal knowledge model. • A detailed study of the knowledge classification specific to the EHEP domain. • An adopted and extended criteria based scheme to formatively evaluate the knowledge models being built.