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A model is designed for the restructuring of knowledge. By way of suitably designed ontologies knowledge can be analysed to facilitate the creation of new knowledge and to render the knowledge suitable for reuse and for linkage to word-wide ontologies. / SUMMARY The need for this research emanated from the requirement for learning and adaptation in the fast-changing world we live in today. The changing world goes along with developments in communication means, whereby information becomes more accessible and sophisticated daily. A vast number of resources is available and accessible, distributing an enormous amount of information. The need is to turn these vast amounts of information into usable knowledge for use by an engineer in practice. Restructuring of knowledge is one way of approaching this need and is addressed in this study. This process can be facilitated by experienced persons who know what knowledge is needed in practice. There is a decline in the numbers of experienced civil engineers, leaving a gap between the supply and demand for suitably qualified and experienced civil engineers. The objective of this study is to meet the need for the restructuring of knowledge by the design a model (referred to as a logic base in this study) for the acquisition, reuse and the creation of engineering knowledge in a civil engineering environment. The main research question posed in this study is as follows: What are the key characteristics of a model (termed a “logic base” in this study) for the acquisition, reuse and the creation of knowledge in a civil engineering environment? This research commences with a set of research questions, followed by a literature review. Consideration is given to theories of knowledge, various methods of knowledge creation and knowledge acquisition. Several problem-solving techniques are reviewed. The structuring and architecture of knowledge and ontologies are researched and the role of systems engineering is studied. Various research methods are investigated and it is shown that case study research is the most suitable for the development of ontologies in civil engineering. The ontology of the logic base is therefore based on typical topics of case studies. Concept maps are employed to structure knowledge. This is done by defining appropriate concepts and classifying these into several ontological levels. The relationships among concepts and other influencing domains are studied. Knowledge of these relationships enables the application of several problem-solving techniques that enhance and stimulate the creation of knowledge. A logic base is designed containing three modules, namely an input module whereby concept maps are used to capture and structure knowledge entities. The second module consists of an analysis module where problem-solving can be done. The third module contains the output of work and processes where engineering knowledge can be documented for reuse. The contribution of this research lies in the design of an application in knowledge management in the field of civil engineering. Integration is done of ontologies, knowledge theories, knowledge acquisition and knowledge creation through problem-solving techniques. Knowledge is structured that can be linked to other external civil engineering taxonomies and ontologies. This enhancement of knowledge makes knowledge explicit and renders it suitable for reuse. When engineers are equipped in the use of the logic base, problems can be addressed in a holistic way and the underlying thought processes can be documented. This may be of great value to inexperienced engineers and for the preservation of valuable knowledge. Some case studies are analysed to demonstrate the functioning of the model. / Thesis (DPhil) University of Pretoria 2018. / Information Science / DPhil / Unrestricted

The IEC Common Information Model (CIM) is of central importance in enabling smart grid interoperability. Its continual development aims to meet the needs of the smart grid for semantic understanding and knowledge representation for a widening domain of resources and processes. With smart grid evolution the importance of information and data management has become an increasingly pressing issue not only because far more data is being generated using modern sensing, control and measuring devices but also because information is now becoming recognised as the ‘integral component’ that facilitates the optimal flexibility required of the smart grid. This thesis looks at the impacts of CIM implementation upon the landscape of smart grid issues and presents research from within National Grid contributing to three key areas in support of further CIM deployment. Taking the issue of Enterprise Information Management first, an information management framework is presented for CIM deployment at National Grid. Following this the development and demonstration of a novel secure cloud computing platform to handle such information is described. Power system application (PSA) models of the grid are partial knowledge representations of a shared reality. To develop the completeness of our understanding of this reality it is necessary to combine these representations. The second research contribution reports on a novel methodology for a CIM-based model repository to align PSA representations and provide a knowledge resource for building utility business intelligence of the grid. The third contribution addresses the need for greater integration of information relating to energy storage, an essential aspect of smart energy management. It presents the strategic rationale for integrated energy modeling and a novel extension to the existing CIM standards for modeling grid-scale energy storage. Significantly, this work has already contributed to a larger body of work on modeling Distributed Energy Resources currently under development at the Electric Power Research Institute (EPRI) in the USA.

A guide to the mindset needed to perform competent knowledge work.

This submission reports on a cross-disciplinary inquiry into topicality and relevance, involving an in-depth literature analysis and an inductive development of a faceted typology (containing 227 fine-grained topical relevance relationships arrayed in three facets and 33 types of presentation relationships). This inquiry reveals a large variety of topical connections beyond topic matching (the common assumption of topical relevance in the field), renders a closer look into the structure of a topic, and induces a generic topic-oriented information architecture that is meaningful across topics and domain boundaries. The findings from the analysis contribute to the foundation work of information organization, metadata development, intellectual access / information retrieval, and knowledge discovery. The typology of topical relevance relationships is structured with three major facets: * Functional role of a piece of information plays in the overall structure of a topic or an argument; * Mode of reasoning: How information contributes to the userâ s reasoning about a topic; * Semantic relationship: How information connects to a topic semantically. This inquiry demonstrated that topical relevance with its close linkage to thinking and reasoning is central to many disciplines. The multidisciplinary approach allows synthesis and examination from new angles, leading to an integrated scheme of relevance relationships or a system of thinking that informs each individual discipline. The scheme resolving from the synthesis can be used to improve text and image understanding, knowledge organization and retrieval, reasoning, argumentation, and thinking in general, by people and machines.

Energy models are optimisation tools which aid in the formulation of energy policies. Built on mathematics, the strength of these models lie in their ability to process numerical data which in turn allows for the generation of an electricity generation mix that incorporates economic and the environmental aspects. Nevertheless, a comprehensive formulation of an electricity generation mix should include aspects associated with politics and society, an evaluation of which requires the consideration of non-numerical qualitative information. Unfortunately, the use of energy models for optimisation coupled with the evaluation of information other than numerical data is a complicated task. Two prerequisites must be fulfilled for energy models to consider political and societal aspects. First, the information associated with politics and society in the context of energy policies must be identified and defined. Second, a software tool which automatically converts both quantitative and qualitative data into mathematical expressions for optimisation is required. We propose a software framework which uses a semantic representation based on ontologies. Our semantic representation contains both qualitative and quantitative data. The semantic representation is integrated into an Optimisation Modelling System which outputs a model consisting of a set of mathematical expressions. The system uses ontologies, engineering models, logic inference and linear programming. To demonstrate our framework, a Prototype Energy Modelling System which accepts energy policy goals and targets as inputs and outputs an optimised electricity generation mix has been developed. To validate the capabilities of our prototype, a case study has been conducted. This thesis discusses the framework, prototype and case study.

During the early modern period, practitioners in oftentimes unrelated arts and sciences began to experiment with transcribing and disseminating technical information by means of new symbolic notations. Algebra, music, chemistry, dance—whole fields of knowledge were quite literally rewritten with plus signs, treble clefs, affinity tables, and step symbols. “The Art of Signs” examines why early modern people working within and across disciplinary boundaries converged on the idea that developing complex symbolic notations would ultimately be worthwhile by reconstructing the reasons that they gave for doing so. It argues that symbolic notations appealed because they enabled powerful techniques of “visual thinking” that had no analogue in more conventional methods of inquiry. Notations transformed problems of information into problems of visualization whose solutions could then be derived by manipulating the properties of the drawn, two-dimensional plane. Indeed, early modern proponents of notations frequently described them in terms of vision, of being able to “see” things with them that they had not recognized before. However, because established methods of reasoning were predominantly verbal or empirical, symbolic notations and the visual thinking that they entailed necessarily challenged received ideas about how information ought to be represented and how knowledge ought to be discovered. Critics of the new notations argued that, at best, they amounted to a form of intellectual obscurantism that stymied rather than facilitated the circulation of knowledge. At worst, notations harbored disturbing implications for human ingenuity if the generation of new ideas truly could be reduced to the ranging and rearranging of symbols on a piece of paper. All told, “The Art of Signs” argues that early modern debates about the use and abuse of symbolic notations represent an underappreciated component of the epistemological ruptures that characterize the Scientific Revolution. Moreover, by recovering early modern understandings of symbolic notation, this dissertation demonstrates that a historical treatment of early modern semiotic thought can be leveraged to take a fresh look at perennial questions of representation that concern scholars across the humanities.

The goal of the Programmer's Apprentice project is to develop a theory of how expert programmers analyze, synthesize, modify, explain, specify, verify, and document programs. This research goal overlaps both artificial intelligence and software engineering. From the viewpoint of artificial intelligence, we have chosen programming as a domain in which to study fundamental issues of knowledge representation and reasoning. From the viewpoint of software engineering, we seek to automate the programming process by applying techniques from artificial intelligence.

The interest in extensions of the logic programming paradigm beyond the class of normal logic programs is motivated by the need of an adequate representation and processing of knowledge. One of the most difficult problems in this area is to find an adequate declarative semantics for logic programs. In the present paper a general preference criterion is proposed that selects the ‘intended’ partial models of generalized logic programs which is a conservative extension of the stationary semantics for normal logic programs of [Prz91]. The presented preference criterion defines a partial model of a generalized logic program as intended if it is generated by a stationary chain. It turns out that the stationary generated models coincide with the stationary models on the class of normal logic programs. The general wellfounded semantics of such a program is defined as the set-theoretical intersection of its stationary generated models. For normal logic programs the general wellfounded semantics equals the wellfounded semantics.

The overall purpose of this study is to investigate lexical semantic representation in bilinguals who speak typologically different languages, specifically, Mandarin and English. Three questions are posed about semantic representation: 1) Do bilingual speakers demonstrate greater heterogeneity in semantic knowledge than monolingual speakers; 2) To what extent do bilingual speakers use paradigmatic and syntagmatic relations to organize their semantic knowledge; and 3) What is the cross- linguistic overlap in bilingual speakers' semantic representation. Thirty Mandarin- English bilingual adults and 30 monolingual English-speaking adults participated in a repeated word association task and generated three associations to each of 36 stimuli. The bilingual speakers completed the same task in their two languages on two different days whereas the monolingual speakers responded to the same 36 stimuli on two different days. Results indicated that 1) the bilingual speakers produced a more heterogeneous set of responses in English than monolingual speakers; heterogeneity was greater in English than Mandarin among the bilingual speakers; 2) the bilingual speakers produced more paradigmatic associations (e.g., happy-sad, spoon-chopsticks, catch-throw) and fewer syntagmatic associations (e.g., happy-smile, spoon-eat, catch-ball) than the monolingual speakers; and 3) approximately 48% of the bilingual speakers' responses were cross- linguistic synonyms, whereas approximately 76% of the monolingual speakers' responses were identical from session 1 to session 2. These findings suggest that late bilinguals (second language learners) use categorical relations to organize their semantic knowledge to a greater extent than monolingual speakers and that reduced experience with a second language can lead to greater heterogeneity in semantic knowledge in that language. The findings also suggest that bilingual speakers have more distributed semantic representations than monolingual speakers. Additional research is needed to explore the areas of heterogeneity, categorical organization, and cross-linguistic overlap in order to further our understanding of bilingual speakers' semantic knowledge representation. / text