Personality disorders (PD) are among the most complex aspects of human behaviour to understand and manage. Stability is thought to be one of the major distinguishing features between PD’s and other forms of psychopathology, however, recent studies have challenged this notion. Borderline personality disorder (BPD) is the focus of this review and is characterised by interpersonal and emotion regulation difficulties. This thesis aimed to first examine the naturalistic course of BPD, through systematic review of the current literature. Following screening, 12 studies, that met all inclusion/exclusion criteria, were critically evaluated. The results, from studies rated as methodologically sound, suggested that the categorical diagnosis of BPD has poor stability over time, with only 3%-35% of participants retaining a diagnosis of BPD over time. However, the studies reviewed were limited by the population they examined: mainly working age adults with mental health problems. Therefore, studies need to be continued and replicated to increase our understanding of the lifespan course of BPD. PD’s within older adults with mental health problems is a highly debated topic. Clinicians have highlighted the presence of PD symptoms within this group and the need for appropriate therapies. Schema therapy is one intervention that has shown to be effective in the treatment of PD symptoms within a working adult population. A recent Delphi-study led to the consensus that existing therapies for PD, such as schema therapy, that have shown to be effective in working aged adults are applicable to older adults. Therefore, the empirical project focused on exploring the theoretical underpinnings of schema therapy in older adults with mental health problems. 3 self-report questionnaires were administered to 62 participants (aged 65- 85 years); Young’s Schema Questionnaire – Short Form (YSQ-S3), Coolidge Axis-II Inventory (Short) (SCATI-II) and The Regulation of Emotions Questionnaire (REQ- 2). Analysis highlighted that YSQ-S3 and REQ-2 scores significantly predicted 69% of the variance in SCATI-II scores. To the author’s knowledge, this study is the first of its kind to find support for the relationships between early maladaptive schemas (EMS), PD symptoms and the use of dysfunctional emotion regulation (ER) strategies, consistent with the schema therapy model, in older adults with mental health problems.

Schema mappings have been extensively studied in the context of data exchange and data integration, where they have turned out to be the right level of abstraction for formalizing data interoperability tasks. Up to now and for the most part, schema mappings have been studied as static objects, in the sense that each time the focus has been on a single schema mapping of interest or, in the case of composition, on a pair of schema mappings of interest. In this paper, we adopt a dynamic viewpoint and embark on a study of sequences of schema mappings and of the limiting behavior of such sequences. To this effect, we first introduce a natural notion of distance on sets of finite target instances that expresses how "Close" two sets of target instances are as regards the certain answers of conjunctive queries on these sets. Using this notion of distance, we investigate pointwise limits and uniform limits of sequences of schema mappings, as well as the companion notions of pointwise Cauchy and uniformly Cauchy sequences of schema mappings. We obtain a number of results about the limits of sequences of GAV schema mappings and the limits of sequences of LAV schema mappings that reveal striking differences between these two classes of schema mappings. We also consider the completion of the metric space of sets of target instances and obtain concrete representations of limits of sequences of schema mappings in terms of generalized schema mappings, that is, schema mappings with infinite target instances as solutions to (finite) source instances.

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Data warehouses were envisioned to facilitate analytical reporting and data visualization by providing a model for the flow of data from operational databases to decision support environments. Decision support environments provide a multidimensional conceptual view of the underlying data warehouse, which is usually stored in relational DBMSs. Typically, there is an impedance mismatch between this conceptual view — shared also by all decision support applications accessing the data warehouse — and the physical model of the data stored in relational DBMSs. This thesis presents a mapping compilation algorithm in the context of the Conceptual Integration Model (CIM) [67] framework. In the CIM framework, the relationships between the conceptual model and the physical model are specified by a set of attribute-to-attribute correspondences. The algorithm compiles these correspondences into a set of mappings that associate each construct in the conceptual model with a query on the physical model. Moreover, the homogeneity and summarizability of data in conceptual models is the key to accurate query answering, a necessity in decision making environments. A data-driven approach to refactor relational models into summarizable schemas and instances is proposed as the solution of this issue. We outline the algorithms and challenges in bridging multidimensional conceptual models and the physical model of data warehouses and discuss experimental results.

Dataspaces aim to remove upfront cost in the generation of the schema mappings that reconcile schematic heterogeneities, and to incrementally improve the generated mappings based on user feedback. The reconciliation of schematic heterogeneities is a crucial step for translating queries between a mediating schema and data sources. The generation of schema mappings depends on the elicitation of conceptually equivalent schema constructs and information on schematic heterogeneities. Furthermore, many dataspace operations manipulate associations between schemas, for example for generating a global schema to mediate user queries. With a view to minimizing upfront costs associated with understanding the relationships between schemas, many schema matching algorithms and tools have been developed for postulating equivalent schema constructs. However, they derive simple associations between schema constructs, and do not provide rich information on schematic heterogeneities. Without manual refinement, the elicitation of conceptually equivalent schema constructs and schematic heterogeneities may create uncertainties that must be managed.The schematic correspondences captures a wide range of one-to-one and many-to-many schematic heterogeneities. This thesis investigates the use of schematic correspondences as a central component in a dataspace management system. To support query evaluation in a dataspace in which relationships between schemas are represented using schematic correspondences, we propose a mechanism for automatically generating schema mappings from the schematic correspondences. We then characterise model management operators, which can underpin the bootstraping and maintenance of dataspaces, over schematic correspondences. To support the management of uncertainty in dataspaces, we propose techniques for quantifying uncertainty in the equivalence of schema constructs from evidence in the form of similarity scores and user feedback, and provide a flexible framework for incrementally updating the uncertainties in the light of new evidence.

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Information visualizations utilizing multiple coordinated views allow users to rapidly explore complex data spaces and discover complex relationships. Most multiple-view visualizations are static with regard to the views that they provide and the coordinations that they support. Despite significant progress in the field of Information Visualization and development of novel interaction techniques, user interfaces for exploring data have lacked flexibility. As a result, the vast quantities of information rapidly being collected in databases are underutilized and opportunities for advancement of knowledge are lost. This research proposes the central concept of visualization schemas based on the Snap-Together Visualization (Snap) model, analogous to the successful database concept of data schemas, which will enable dynamic specification of information visualizations for any given database without programming. Relational databases provide significant flexibility to organize, store, and manipulate an infinite variety of complex data collections. This flexibility is enabled by the concept of relational data schemas, which allow data owners to easily design custom databases according to their unique needs. We bring the same level of flexibility to visualization development through visualization schemas. Visualization Schemas is a conceptual model, user interface, and software architecture while Fusion is the implemented system that enable users to rapidly and dynamically construct personalized multi-view visualization workspaces by coordinating visualizations in ways unforeseen by the original developers. / Master of Science