548 research outputs found

    Semantic integrity in data warehousing : a framework for understanding : a thesis presented in partial fulfilment of the requirements for the degree of Masters of Business Studies in Information Systems at Massey University, Palmerston North, New Zealand

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    Data modelling has gathered an increasing amount of attention by data warehouse developers as they come to realise that important implementation decisions such as data integrity, performance and meta data management, depend on the quality of the underlying data model. Not all organisations model their data but where they do, Entity-Relationship (E-R) modelling, or more correctly relational modelling, has been widely used. An alternative, dimensional modelling, has been gaining acceptance in recent years and adopted by many practitioners. Consequently, there is much debate over which form of modelling is the most appropriate and effective. However, the dimensional model is in fact based on the relational model and the two models are not so different that a debate is necessary. Perhaps, the real focus should be on how to abstract meaning out of the data model. This research explores the importance of semantic integrity during data warehouse design and its impact on the successful use of the implemented warehouse. This has been achieved through a detailed case study. Consequently, a conceptual framework for describing semantic integrity has been developed. The purpose of the framework is to provide a theoretical basis for explaining how a data model is interpreted through the meaning levels of understanding, connotation and generation, and also how a data model is created from an existing meaning structure by intention, generation and action. The result of this exploration is the recognition that the implementation of a data warehouse may not assist with providing a detailed understanding of the semantic content of a data warehouse

    Understanding Categorization: An Experientialist Perspective

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    A considerable amount of research has been undertaken to establish how end users interpret, understand and verify data models often with the motivation of improving understanding, accuracy and completeness. However, there is relatively little research examining how and why humans make categorisation decisions when developing information systems. The research question addressed in this paper is: what is it about the human mind that allows it to categorise concepts in a particular way for conceptual data modelling? From a cognitive psychology perspective Lakoff’s (1987) image schema structures provide answers to such questions. I argue that acknowledging such structures is the first step in defining an experientialist strategy for data modelling. In addition a case example is used to illustrate the problems with utilising the objectivist approach to categorisation

    Critical Appraisal Guidelines for Single Case Study Research

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    The use of critical appraisal guidelines to assess the validity of research findings has become an established technique in those disciplines, such as healthcare and medicine, that encourage the use of evidence-based practice. Critical appraisal guidelines provide a rigorous set of criteria, often in the form of a checklist, against which a piece of research can be assessed. Although well established criteria exist for many forms of quantitative research, such as clinical trials and cohort studies, qualitative research is less well served. Through a synthesis of existing best practices in interpretative research this paper provides comprehensive guidelines for the conduct of single case study research and extrapolates from them a set of critical appraisal guidelines to assist in the evaluation of such work

    Carbon dioxide accounting:2014 Commonwealth Games Atheletes’ Village

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    A spreadsheet-based tool for whole-life carbon dioxide accounting of soil remediation projects has been created. The tool carries out whole-life analysis of projects, including supply chain emissions. It was applied to the Glasgow 2014 Commonwealth Games Athletes' Village remediation project, for which a calculated total ‘carbon footprint’ of 2328 t of carbon dioxide equivalent emission (tCO2e) was obtained. This is 71 tCO2e/ha of the site or 13·3 kgCO2e/t whole life of soil treated. These figures are not comparable with those reported for other projects, which have typically not included supply chain emissions. Fuel use was the main contributor to emissions, but the contribution made by staff transport and carbon dioxide embodied in construction plant was also found to be significant. A comparison was made with an excavate and disposal (E&D) approach, which required considerable use of estimation for the hypothetical E&D. However, it was determined that the carbon footprint of E&D may have been 14% higher than the soil washing actually used. It was concluded that fuel efficiency would be key to future reduction of the carbon footprint of remediation projects, that the accounting tool would be useful for ongoing project management, and its application over time could lead to a database of values for optioneering at the process design stage

    Real bad grammar: realistic grammatical description with grammaticality

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    Sampson (this issue) argues for a concept of “realistic grammatical description” in which the distinction between grammatical and ungrammatical sentences is irrelevant. In this article I also argue for a concept of “realistic grammatical description” but one in which a binary distinction between grammatical and ungrammatical sentences is maintained. In distinguishing between the grammatical and ungrammatical, this kind of grammar differs from that proposed by Sampson, but it does share the important property that invented sentences have no role to play, either as positive or negative evidence

    Effects of Mental Health First Aid Course: Knowledge, Confidence, and Stigma Among Occupational Therapy Students

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    In the United States, one in five adults are impacted by some form of mental illness in any given year, but only about 40% of individuals seek professional mental health support. While occupational therapists (OT) may work with individuals with mental illness to improve social skills, activities of daily living (ADLs), instrumental ADLs, and neurocognitive interventions, research suggests there is not enough emphasis on this content in professional OT education. Mental Health First Aid (MHFA) training is designed to educate individuals on mental illness, including how to recognize signs and symptoms and how to support individuals experiencing a concern or crisis. This study examined changes in stigma, knowledge, and confidence among OT students following MHFA training, and compared to a control group. Results demonstrated improved knowledge and confidence within the experimental group, highlighting the impact of MHFA training in this population
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