Generic unified modelling process for developing semantically rich, dynamic and temporal models

Models play a vital role in supporting a range of activities in numerous domains. We rely on models to support the design, visualisation, analysis and representation of parts of the world around us, and as such significant research effort has been invested into numerous areas of modelling; including support for model semantics, dynamic states and behaviour, temporal data storage and visualisation. Whilst these efforts have increased our capabilities and allowed us to create increasingly powerful software-based models, the process of developing models, supporting tools and /or data structures remains difficult, expensive and error-prone. In this paper we define from literature the key factors in assessing a model’s quality and usefulness: semantic richness, support for dynamic states and object behaviour, temporal data storage and visualisation. We also identify a number of shortcomings in both existing modelling standards and model development processes and propose a unified generic process to guide users through the development of semantically rich, dynamic and temporal models.

Rationality of service composition of Workflow Net in a service oriented architecture

Users’ requirements change drives an information system evolution. Consequently, such evolution affects those atomic services which provide functional operations from one state of their composition to another state of composition. A challenging issue associated with such evolution of the state of service composition is to ensure a resultant service composition remaining rational. This paper presents a method of Service Composition Atomic-Operation Set (SCAOS). SCAOS defines 2 classes of atomic operations and 13 kinds of basic service compositions to aid a state change process by using Workflow Net. The workflow net has algorithmic capabilities to compose the required services with rationality and maintain any changes to the services in a different composition also rational. This method can improve the adaptability to the ever changing business requirements of information systems in the dynamic environment.

Assessing the business risk of technology obsolescence through enterprise modelling

The problem of technology obsolescence in information intensive businesses (software and hardware no longer being supported and replaced by improved and different solutions) and a cost constrained market can severely increase costs and operational, and ultimately reputation risk. Although many businesses recognise technological obsolescence, the pervasive nature of technology often means they have little information to identify the risk and location of pending obsolescence and little money to apply to the solution. This paper presents a low cost structured method to identify obsolete software and the risk of their obsolescence where the structure of a business and its supporting IT resources can be captured, modelled, analysed and the risk to the business of technology obsolescence identified to enable remedial action using qualified obsolescence information. The technique is based on a structured modelling approach using enterprise architecture models and a heatmap algorithm to highlight high risk obsolescent elements. The method has been tested and applied in practice in two consulting studies carried out by Capgemini involving three UK police forces. However the generic technique could be applied to any industry based on plans to improve it using ontology framework methods. This paper contains details of enterprise architecture meta-models and related modelling.

Modelling the resistance of Enterprise Architecture adoption: linking strategic level of Enterprise Architecture to organisational changes and change resistance

During the last few years Enterprise Architecture (EA) has received increasing attention among industry and academia. By adopting EA, organisations may gain a number of benefits such as better decision making,increased revenues and cost reduction, and alignment of business and IT. However, EA adoption has been found to be difficult. In this paper a model to explain resistance during EA adoption process (REAP) is introduced and validated. The model reveals relationships between strategic level of EA, resulting organisational changes, and sources of resistance. By utilising REAP model, organisations may anticipate and prepare for the organisational change resistance during EA adoption.

Design of a unified data with business rules storage model for OLTP and OLAP systems

This paper reviews the literature concerning the practice of using Online Analytical Processing (OLAP) systems to recall information stored by Online Transactional Processing (OLTP) systems. Such a review provides a basis for discussion on the need for the information that are recalled through OLAP systems to maintain the contexts of transactions with the data captured by the respective OLTP system. The paper observes an industry trend involving the use of OLTP systems to process information into data, which are then stored in databases without the business rules that were used to process information and data stored in OLTP databases without associated business rules. This includes the necessitation of a practice, whereby, sets of business rules are used to extract, cleanse, transform and load data from disparate OLTP systems into OLAP databases to support the requirements for complex reporting and analytics. These sets of business rules are usually not the same as business rules used to capture data in particular OLTP systems. The paper argues that, differences between the business rules used to interpret these same data sets, risk gaps in semantics between information captured by OLTP systems and information recalled through OLAP systems. Literature concerning the modeling of business transaction information as facts with context as part of the modelling of information systems were reviewed to identify design trends that are contributing to the design quality of OLTP and OLAP systems. The paper then argues that; the quality of OLTP and OLAP systems design has a critical dependency on the capture of facts with associated context, encoding facts with contexts into data with business rules, storage and sourcing of data with business rules, decoding data with business rules into the facts with the context and recall of facts with associated contexts. The paper proposes UBIRQ, a design model to aid the co-design of data with business rules storage for OLTP and OLAP purposes. The proposed design model provides the opportunity for the implementation and use of multi-purpose databases, and business rules stores for OLTP and OLAP systems. Such implementations would enable the use of OLTP systems to record and store data with executions of business rules, which will allow for the use of OLTP and OLAP systems to query data with business rules used to capture the data. Thereby ensuring information recalled via OLAP systems preserves the contexts of transactions as per the data captured by the respective OLTP system.