Semantic Model Alignment for Business Process Integration

Business process models describe an enterprise’s way of conducting business and in this form the basis for shaping the organization and engineering the appropriate supporting or even enabling IT. Thereby, a major task in working with models is their analysis and comparison for the purpose of aligning them. As models can differ semantically not only concerning the modeling languages used, but even more so in the way in which the natural language for labeling the model elements has been applied, the correct identification of the intended meaning of a legacy model is a non-trivial task that thus far has only been solved by humans. In particular at the time of reorganizations, the set-up of B2B-collaborations or mergers and acquisitions the semantic analysis of models of different origin that need to be consolidated is a manual effort that is not only tedious and error-prone but also time consuming and costly and often even repetitive. For facilitating automation of this task by means of IT, in this thesis the new method of Semantic Model Alignment is presented. Its application enables to extract and formalize the semantics of models for relating them based on the modeling language used and determining similarities based on the natural language used in model element labels. The resulting alignment supports model-based semantic business process integration. The research conducted is based on a design-science oriented approach and the method developed has been created together with all its enabling artifacts. These results have been published as the research progressed and are presented here in this thesis based on a selection of peer reviewed publications comprehensively describing the various aspects

SUPPORTING TERMINOLOGICAL STANDARDIZATION IN CONCEPTUAL MODELS - A PLUGIN FOR A META-MODELLING TOOL

Today´s enterprises are accumulating huge repositories of conceptual models, such as data models, organisational charts and most notably business process models. Those models often grow heterogeneously with the company and are thus often terminologically divers and complex. This terminological diversity originates from the fact that natural language allows an issu to be described in a large variety of ways especially when many modellers are involved. This diversity can become a pitfall when conceptual models are subject to model analysis techniqus, which require terminologically comparable model elements. Therefore, it is essential to ensure model quality by enforcing naming conventions. This paper introduces a prototype, which intends to resolve all associated issus of terminological standardisation already during the modelling phase or ex-post based on existing models. The modeller is guided through the standardization process by providing an automated list of all correct phrase propositions according to his entered phrase. In this approach, naming conventions can easily be defined and enforced. This leads to terminologically unambiguous conceptual models, which are easier to understand and ready for further analysis purposes

Wicked problems in public policy

Some of the most difficult policy problems of the modern era have been described as complex, intractable, open-ended and 'wicked'. What are the key features of such problems? And are they really very different in nature from more routine problems? Are we developing better ways to address these wicked problems? This paper sketches some key aspects of wicked problems, and illustrates the discussion with two contemporary Australian examples - recent attempts to address the causes and possible solutions to Indigenous disadvantage; and policy responses to climate change

Evidence synthesis on the occurrence, causes, consequences, prevention and management of bullying and harassment behaviours to inform decision making in the NHS

Background Workplace bullying is a persistent problem in the NHS with negative implications for individuals, teams, and organisations. Bullying is a complex phenomenon and there is a lack of evidence on the best approaches to manage the problem. Aims Research questions What is known about the occurrence, causes, consequences and management of bullying and inappropriate behaviour in the workplace? Objectives Summarise the reported prevalence of workplace bullying and inappropriate behaviour. Summarise the empirical evidence on the causes and consequences of workplace bullying and inappropriate behaviour. Describe any theoretical explanations of the causes and consequences of workplace bullying and inappropriate behaviour. Synthesise evidence on the preventative and management interventions that address workplace bullying interventions and inappropriate behaviour. Methods To fulfil a realist synthesis approach the study was designed across four interrelated component parts: Part 1: A narrative review of the prevalence, causes and consequences of workplace bullying Part 2: A systematic literature search and realist review of workplace bullying interventions Part 3: Consultation with international bullying experts and practitioners Part 4: Identification of case studies and examples of good practic

Proceedings of the Salford Postgraduate Annual Research Conference (SPARC) 2011

These proceedings bring together a selection of papers from the 2011 Salford Postgraduate Annual Research Conference(SPARC). It includes papers from PhD students in the arts and social sciences, business, computing, science and engineering, education, environment, built environment and health sciences. Contributions from Salford researchers are published here alongside papers from students at the Universities of Anglia Ruskin, Birmingham City, Chester,De Montfort, Exeter, Leeds, Liverpool, Liverpool John Moores and Manchester

Sensitivity analysis in a scoping review on police accountability : assessing the feasibility of reporting criteria in mixed studies reviews

In this paper, we report on the findings of a sensitivity analysis that was carried out within a previously conducted scoping review, hoping to contribute to the ongoing debate about how to assess the quality of research in mixed methods reviews. Previous sensitivity analyses mainly concluded that the exclusion of inadequately reported or lower quality studies did not have a significant effect on the results of the synthesis. In this study, we conducted a sensitivity analysis on the basis of reporting criteria with the aims of analysing its impact on the synthesis results and assessing its feasibility. Contrary to some previous studies, our analysis showed that the exclusion of inadequately reported studies had an impact on the results of the thematic synthesis. Initially, we also sought to propose a refinement of reporting criteria based on the literature and our own experiences. In this way, we aimed to facilitate the assessment of reporting criteria and enhance its consistency. However, based on the results of our sensitivity analysis, we opted not to make such a refinement since many publications included in this analysis did not sufficiently report on the methodology. As such, a refinement would not be useful considering that researchers would be unable to assess these (sub-)criteria

Retrieving, annotating and recognizing human activities in web videos

Recent e orts in computer vision tackle the problem of human activity understanding in video sequences. Traditionally, these algorithms require annotated video data to learn models. In this work, we introduce a novel data collection framework, to take advantage of the large amount of video data available on the web. We use this new framework to retrieve videos of human activities, and build training and evaluation datasets for computer vision algorithms. We rely on Amazon Mechanical Turk workers to obtain high accuracy annotations. An agglomerative clustering technique brings the possibility to achieve reliable and consistent annotations for temporal localization of human activities in videos. Using two datasets, Olympics Sports and our novel Daily Human Activities dataset, we show that our collection/annotation framework can make robust annotations of human activities in large amount of video data

Altering choice architecture to change population health behaviour: a large-scale conceptual and empirical scoping review of interventions within micro-environments.

A concise summary of this report is also available as a journal article: http://www.biomedcentral.com/1471-2458/13/1218 Hollands, G. J., Shemilt, I., Marteau, T. M., Jebb, S. A., Kelly, M. P., Nakamura, R., Suhrcke, M., Ogilvie, D. (2013). Altering micro-environments to change population health behaviour: towards an evidence base for choice architecture interventions. BMC Public Health, 13, 1218.There is considerable public policy interest in choice architecture, an approach that involves altering features of physical or social environments to change behaviour. To date there has been no systematic attempt to clarify the concept and definition or describe the evidence base for such interventions. We conducted a systematic scoping review of empirical evidence, and related conceptual material, to identify the effects of choice architecture interventions in micro-environments on diet-, physical activity-, alcohol- and tobacco-related behaviours