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This thesis is a linguistic/ontological inquiry into narrative dynamics. Particular attention is drawn to elucidating the mechanism for recognising story events as one reads narrative discourse. The overall discussion is a criticism of formal approaches to narrative dynamics which tend to make observations on the assumption that there is a fixed relation between language form and meaning (e.g. the distinction between events and non-events in narrative circumstances). As two possible factors responsible for preventing formal analysts from taking an elastic view of story-event structure in narrative, I point out overly metalinguistic and metatemporal attitudes held by many narrative poeiticians, grammarians and formal semanticists. The recognition of narrative dynamics is primarily concerned with our concept of time, so that this thesis focuses a good deal of attention on explicating how time can be conceptualised in narrative. The basic component of the argument, therefore, is made up of ontological observations concerning time, event, and change, which are mainly made in Chapters 3 and 5. This thesis concludes that overly metalinguistic and metatemporal approaches to narrative dynamics tend to be fallacious, and that it is the commonsensical view that counts in the recognition of the event structure in narrative discourse. A hypothetical stance I adopt in constructing a narrative theory is the viewpoint of the ordinary reader of narrative fiction who is not formally trained, and therefore, does not necessarily respond to narrative texts in a highly metalinguistic or metatemporal way. The importance of assuming the ordinary reader's viewpoint for the proper recognition of the story-event structure of narrative is referred to in many different respects throughout the thesis.

Data provenance refers to the lineage or pedigree of data, including information such as its origin and key events that affect it over the course of its lifecycle. In recent years, provenance has become increasingly important as more and more people are using data that they themselves did not generate. Tracking data provenance helps ensure that data provided by many different providers and sources can be trusted and used appropriately. Data provenance also has several other critical uses, including data quality assessment, generating data replication recipes, data security management, etc.One of the major objectives of our research is to investigate the semantics or meaning of data provenance. We describe a generic ontology of data provenance called the W7 model that represents the semantics of data provenance. Formalized in the conceptual graph formalism, the W7 model represents provenance as a combination of seven interconnected elements including "what," "when," "where," "how," "who," "which" and "why." The W7 model is designed to be general and comprehensive enough to cover a broad range of provenance-related vocabularies. However, the W7 model alone, no matter how comprehensive it is, is insufficient for capturing all domain-specific provenance requirements. We hence present a novel approach to developing domain ontologies of provenance. This approach relies on various conceptual graph mechanisms, including schema definitions and canonical formation rules, and enables us to easily adapt and extend the W7 model to develop domain ontologies of provenance. The W7 model for data provenance has been widely adopted and adapted for use within Raytheon Missile Systems and the iPlant Collaborative, as well as the US Army's ATRAP IV (Asymmetric Threat Response and Analysis Program) system.We also developed a domain ontology of provenance for Wikipedia based on the W7 model. This domain ontology enables us to extract provenance for each Wikipedia article. We present a study in which we use their provenance to assess the quality of Wikipedia articles. Assessing and guaranteeing data quality has become a critical concern that, to a large extent, determines the future success and survival of Wikipedia since the quality of Wikipedia has been continuously called into question due to various incidents of vandalism and misinformation since its launch in 2001. Our study shows that the quality of Wikipedia articles depends not only on the different types of contributors but also on how they collaborate. We identify a number of contributor roles based on the provenance. Based on the roles and provenance, our research identifies several collaboration patterns that are preferable or detrimental for data quality, thus providing insights for designing tools and mechanisms to improve Wikipedia article quality.

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This work is based upon fieldwork carried out among indigenous Pehuenche people living in the Andes in Southern Chile. It is an ethnographic investigation of the relations between Pehuenche vision and healing practices in different local settings. The first part of this thesis focuses on Pehuenche vision from a cosmo-political angle. In order to set the scene for my overall argument, I explore the constitutive relation between mutual vision among real people (Ch. che) and the emergence of the Pehuenche person, which I call the ‘dynamic personal composition.’ With mutual vision between people being a precondition for the emergence of social relations, I examine the experience of particular witchcraft actions in which mutual vision is not possible. This leads to the conceptualization of ‘unilateral vision’ as a key phenomenon associated with the emergence of illnesses and the alteration of the shared plane of Pehuenche visibility. I also explore how mutual vision can be restored only through the assemblage of particular visual capacities known in the vernacular as ‘the gift of vision.’ In the second part of the thesis, I analyze the ways in which public health services respond to particular illnesses not detectable or treatable by medical technicians. In particular, I focus on the implications of ‘the visualization of traditional healers,’ inherent in the State’s approach to intercultural health. Through the examination of both particular intercultural health projects, as well as local expressions of discontent and animosity towards the State, this thesis seeks to create awareness about the ontological relevance of mutual vision in relations among real people. By pointing out the equivocal understandings of the visible and the invisible domains within intercultural relations, the analysis as a whole seeks to explain why Pehuenche vision must be understood through ontological examination rather than through a multicultural approach.

Ontology has been developed to offer a commonly agreed understanding of a domain that is required for knowledge representation, knowledge exchange and reuse across domains. Therefore, ontology organizes information into taxonomies of terms (i.e., concepts, attributes) and shows the relationships between them. In fact, it is considered to be helpful in reducing conceptual confusion for users who need to share applications of different kinds, so it is widely used to capture and organize knowledge in a given domain. Although ontologies are considered to provide a solution to data heterogeneity, from another point of view, the available ontologies could themselves introduce heterogeneity problems. In order to deal with these problems, ontologies must be available for sharing or reusing; therefore, semantic heterogeneity and structural differences need to be resolved among ontologies. This can be done, in some cases, by aligning or matching heterogeneous ontologies. Thus, establishing the relationships between terms in the different ontologies is needed throughout ontology alignment. Semantic interoperability can be established in ontology reconciliation. The original problem is called the ―ontology alignment‖. The alignment of ontologies is concerned with the identification of the semantic relationships (subsumption, equivalence, etc.) that hold between the constituent entities (which can be classes, properties, etc.) of two ontologies. In this thesis, an ontology alignment technique has been developed in order to facilitate communication and build a bridge between ontologies. An efficient mechanism has been developed in order to align entities from ontologies in different description languages (e.g. OWL, RDF) or in the same language. This approach tries to use all the features of ontologies (concept, attributes, relations, structure, etc.) in order to obtain efficiency and high quality results. For this purpose, several matching techniques have been used such as string, structure, heuristic and linguistic matchingtechniques with thesaurus support, as well as human intervention in certain cases, to obtain high quality results. The main aim of the work is to introduce a method for finding semantic correspondences among heterogeneous ontologies, with the intention of supporting interoperability over given domains. The approach brings together techniques in modelling, string matching, computation linguistics, structure matching and heuristic matching, in order to provide a semi-automatic alignment framework and prototype alignment system to support the procedure of ontology alignment in order to improve semantic interoperability in heterogeneous systems. This technique integrates some important features in matching in order to achieve high quality results, which will help when searching and exchanging information between ontologies. Moreover, an ontology alignment system illustrates the solving of the key issues related to heterogeneous ontologies, which uses combination-matching strategies to execute the ontology-matching task. Therefore, it can be used to discover the matching between ontologies. This thesis also describes a prototype implementation of this approach in many real-world case studies extracted from various Web resources. Evaluating our system is done throughout the experiments provided by the Ontology Alignment Evaluation Initiative. The system successfully achieved 93% accuracy for ontology matching. Finally, a comparison between our system and well-known tools is achieved so that our system can be evaluated.