Investigating the role of knowledge management in driving the development of an effective business process architecture

Business Process Architecture (BPA) modelling methods are not dynamic and flexible enough to effectively respond to changes. This may create a barrier that contributes to a lack of knowledge and learning capabilities which can affect the BPA regarding its support for a sustainable competitive advantage in an organisation. New business challenges are driving business enterprises to adopt Knowledge Management (KM) as one means of making a positive difference to their performance and competitiveness. However, shortcomings still remain in utilising knowledge management in business processes where efforts were mostly directed towards the integration of knowledge management with business process management but not including BPAs. The idea of applying KM as a memory to be timely retrieved and updated as needed is no longer sufficient. The resource-based view suggests a number of key factors to be investigated and taken into consideration during the development of knowledge management systems. These key factors are known as Knowledge Management Enablers (KMEs). KMEs are crucial for representing KM and understanding how knowledge is created, shared and disseminated. They are also essential to identify available assets and resources, and to clarify how organisational capabilities are created and utilised.This research is aimed at investigating the role of the knowledge management enablers in the development of an effective process architecture. An effective process architecture needs to be dynamic and supports a sustainable competitive advantage in an organisation. Identifying the KMEs, selecting an appropriate BPA method, aligning these KMEs with this method as well as undertaking a critical evaluation of this alignment are the main objectives set for this research. In order to accomplish the research aim and objectives, a resource-based and semantic-enriched framework, namely the KMEOntoBPA has been designed using KMEs to drive the process of BPA development. Organisational structure, culture, information technology, leadership, knowledge context and business repository have been selected as representatives of the KMEs. The object-based BPA modelling, specifically the semantically enriched Riva BPA (srBPA) method, has been adopted in order to embrace the knowledge resources generated by KMEs and utilise them in the derivation and re-configuration of its constitutional elements. These knowledge resources are employed as business objects. They are considered as Candidate Essential Business Entities (CEBEs) in the Riva method, that characterise or represent a form of business of an organisation. The Design Science Research Methodology (DSRM) is used to guide the research phases with an emphasis on the design and development, demonstration and evaluation of the research framework. The KMEOntoBPA has been demonstrated using sufficient and representative core banking case studies of the Treasury, Deposits and Financing. These case studies have been applied to the DSRM iterations beginning with the Treasury as the 1st case study, followed by the Deposits and the Financing case studies.The results have revealed that KMEs utilisation provides an agile generation of representative CEBEs and their corresponding Riva BPA elements, which reflect the real business in each of the core banking business studies. This research also demonstrated the semantic Riva BPA method as an appropriate object-based method that is well aligned with KMEs in exploiting knowledge resources for the development of a dynamic BPA with reference to robustness and learning capabilities. In addition to these results, the research framework, i.e, the KMEOntoBPA has shown an understanding of the flow of knowledge in the bank and has provided several possible advantages such as the accuracy of service delivery and the improvement of the financial control. It also supports the sources of sustainable competitive advantage (SCA): technical capabilities, core competences and social capital.Finally, a number of significant contributions and artefacts have been attained. For example, there is the aKMEOnt which is the abstract ontology that utilises six KMEs in this research to investigate the effectiveness of using such KMEs in driving the development of the BPA. These contributions along with the research results provide a guide to future research directions such as using the aKMEOnt in the development of different business process modelling and deriving the Enterprise Information Architecture (EIA) and Service Oriented Architecture (SOA)

Domain-specific textual meta-modelling languages for model driven engineering

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-31491-9_20Proceedings of 8th European Conference, ECMFA 2012, Kgs. Lyngby, Denmark, July 2-5, 2012Domain-specific modelling languages are normally defined through general-purpose meta-modelling languages like the MOF. While this is satisfactory for many Model-Driven Engineering (MDE) projects, several researchers have identified the need for domain-specific meta-modelling (DSMM) languages providing customised meta-modelling primitives aimed at the definition of modelling languages in a specific domain, as well as the construction of meta-model families. In this paper, we discuss the potential of multi-level meta-modelling for the systematic engineering of DSMM architectures. For this purpose, we present: (i) several primitives and techniques to control the meta-modelling facilities offered to the users of the DSMM languages, (ii) a flexible approach to define textual concrete syntaxes for DSMM languages, (iii) extensions to model management languages enabling the practical use of DSMM in MDE, and (iv) an implementation of these ideas in the metaDepth tool.This work was funded by the Spanish Ministry of Economy and Competitivity (project “Go Lite” TIN2011-24139) and the R&D programme of the Madrid Region (project “e-Madrid” S2009/TIC-1650

Construct redundancy in process modelling grammars: Improving the explanatory power of ontological analysis

Conceptual modelling supports developers and users of information systems in areas of documentation, analysis or system redesign. The ongoing interest in the modelling of business processes has led to a variety of different grammars, raising the question of the quality of these grammars for modelling. An established way of evaluating the quality of a modelling grammar is by means of an ontological analysis, which can determine the extent to which grammars contain construct deficit, overload, excess or redundancy. While several studies have shown the relevance of most of these criteria, predictions about construct redundancy have yielded inconsistent results in the past, with some studies suggesting that redundancy may even be beneficial for modelling in practice. In this paper we seek to contribute to clarifying the concept of construct redundancy by introducing a revision to the ontological analysis method. Based on the concept of inheritance we propose an approach that distinguishes between specialized and distinct construct redundancy. We demonstrate the potential explanatory power of the revised method by reviewing and clarifying previous results found in the literature

Semantic Modelling of Interactive 3D Content with Domain-specific Ontologies

AbstractThe creation of interactive 3D presentations is typically a complex process involving activities related to various aspects of the content such as geometry, structure, space, appearance, logic and behaviour. However, widespread dissemination of interactive 3D content on the web requires flexible and efficient methods of content creation. In this paper, an approach to semantic modelling of 3D content is proposed. The proposed solution enables creation of content components and properties - reflecting different aspects of the content - with domain-specific ontologies and knowledge bases. The use of domain-specific knowledge liberates authors from going into details that are specific to 3D modelling, allows for content representation at different levels of abstraction and permits content creation by domain experts, who are not required to be IT-professionals

The MOLDY short-range molecular dynamics package

We describe a parallelised version of the MOLDY molecular dynamics program. This Fortran code is aimed at systems which may be described by short-range potentials and specifically those which may be addressed with the embedded atom method. This includes a wide range of transition metals and alloys. MOLDY provides a range of options in terms of the molecular dynamics ensemble used and the boundary conditions which may be applied. A number of standard potentials are provided, and the modular structure of the code allows new potentials to be added easily. The code is parallelised using OpenMP and can therefore be run on shared memory systems, including modern multicore processors. Particular attention is paid to the updates required in the main force loop, where synchronisation is often required in OpenMP implementations of molecular dynamics. We examine the performance of the parallel code in detail and give some examples of applications to realistic problems, including the dynamic compression of copper and carbon migration in an iron-carbon alloy

Evaluating Wiki Collaborative Features in Ontology Authoring (Extended abstract)

Abstract: This extended abstract summarizes a rigorous investigation about the effectiveness of the impact of wiki collaborative functionalities on the collaborative ontology authoring. The work summarized in this extended abstract has been published in Context. This extended abstract summarizes a rigorous investigation about the impact of wiki collaborative functionalities on ontology modelling, presented in: Good quality ontology modelling often demands for multiple competencies and skills, which are difficult to find in a single person. This results in the need of involving more actors, possibly with different roles and expertise, collaborating towards the ontology construction. Collaborative ontology authoring has been recently widely investigated in the literature A first requirement deals with the collaboration between who knows the domain that is going to be modelled, i.e., the Domain Expert (DE) and who has the technical skills to formalize the domain modelling. i.e., the Knowledge Engineer (KE). Traditional methodologies and tools were mainly based on the idea that knowledge engineers should drive the modelling process (producing ontologies in a formalism which is usually not understandable for domain experts) and domain experts should only report to KEs their knowledge of the domain. However, these methodologies often create an unnecessary extra layer of indirectness, an imbalance between the two roles and the impossibility for the domain experts to understand the modelled ontology. DEs should be actively involved in the ontology modelling process rather than only provide domain knowledge to KEs. A second important requirement deals with the support of distributed teams of actors. Independently of their geographical position or their role, team members should be made aware about the collaborative development of the modelled artefacts, should be supported in the communication of modeling choices, as well as in the work coordination. Wiki tools for the ontology authoring offer an appealing option for tackling these collaborative aspects. Indeed wikis usually provide collaborative features (wiki collaborative 1 Fondazione Bruno Kessler, Via Sommarive, 18, 38123 Trento, dfmchiara|ghidini|rospocher@fbk,e

Mathematical Modelling and Design for the Scale-up of an AACVD Process

The manufacturing process of photovoltaic devices, such as solar cells, relies on the production of Transparent and Conductive Oxide (TCO) films. One of the techniques for creating these films is based on Aerosol-Assisted Chemical Vapour Deposition (AACVD). The AACVD process comprises the atomisation of a precursor solution into aerosol droplets, which are transported to a heated chamber for the synthesis of films such as the TCOs, as well as coatings, powders, composites and nanotubes. At present, AACVD has not been used as an industrial deposition technique. However, it has the potential to be scaled-up due to its versatility and the ease through which effective functional coatings can be deposited at a laboratory-scale. Computational simulations are pivotal to study the feasibility of such a scale-up. This thesis presents, therefore, an integrated model to support the AACVD process scale-up. The model is comprised of four stages: aerosol generation, transport, delivery and chemical deposition. The generation of aerosol is described by a distribution of droplet sizes, which is the input to a transport model that incorporates the impact of aerosol losses. The output distribution provides sufficient information to predict the amount and sizing of aerosol reaching the deposition site. Experimental validation has shown the model to be effective at predicting transport losses and droplet sizes. The delivery stage includes the solvent evaporation, accounting for uncertainties in the temperature profile of the deposition site. This is a key factor for the solvent evaporation, setting the precursors free to react and form the desired products. For the chemical deposition stage, reactions in the solid and gas phases were studied. The model presented is suitable for application on the scale of industrial processes and is also suitable for processes that rely on atomisation and transport of particles, for example, spray drying or cooling and fuel combustion. Lessons learned in modelling uncertainties and their impact on process scale-up motivated the research into formulation, modelling and solution methods for such applications. Therefore, as an additional contribution, this thesis introduces Uncertainty.jl, a modelling framework focused on the treatment of uncertainty