Pub. online:14 Mar 2023Type:Research ArticleOpen Access
Volume 34, Issue 1 (2023), pp. 121–146
Experience shows that Agile project management tools such as Atlassian Jira capture the state of EAS projects by relying solely on expert judgement that is not supported by any knowledge model. Therefore, the assessment of project content against strategic objectives and business domain features are not supported by any tool. This is one of the reasons why Agile project management still does not provide sufficient EAS project delivery results. In order to address this problem, the Enterprise Application Software (EAS) development using Agile project management is summarized in a conceptual model. The model highlights the knowledge used and indicates its nature (empirical or causal digitized). The modified Agile management process we have developed and described in previous works is based on causal knowledge models that supports EAS development and Agile management processes. The purpose of this article is to specify knowledge repository to ensure the Agile management solutions of an EAS project are aligned with strategic goals and business domain causality. It is worth noticing that strategic goals have been identified and specified as capabilities using some enterprise architecture framework (NAF, MODAF, ArchiMate, etc.). The novelty of the proposed method is incorporating the business domain causal knowledge modelling approach into the Agile project management process. The causal knowledge unit is considered as a Management Transaction (MT), which includes closed loop dependence of its components. The modified Agile activity hierarchy (theme, initiative, epic, user story) defines the required content of their mutual interactions. An important new results obtained are the conceptual model of causal knowledge base (KB) and specification of enhanced Agile management tool components: project management database and project state assesment knowledge base. Causal KB includes specification of causal knowledge unit (MT metamodel) and specifications of traditional and causal Agile hierarchy meta-models. These conceptual models define the causal knowledge components necessary to evaluate the state of Agile activities in the EAS development project using intelligent Agile project management tool.
Volume 32, Issue 2 (2021), pp. 247–281
The paper deals with the causality perspective of the Enterprise Architecture (EA) frameworks. The analysis showed that there is a gap between the capabilities of EA frameworks and the behavioural characteristics of the real world domain (enterprise management activities). The contribution of research is bridging the gap between enterprise domain knowledge and EA framework content by the integration of meta-models as part of EA structures. Meta-models that cover not only simple process flows, but also business behaviour, i.e. causality of the domain, have been developed. Meta-models enable to create a layer of knowledge in the EA framework, which ensures smart EA development, allows validation of developer decisions. Two levels of the enterprise causal modelling were obtained. The first level uses the Management Transaction (MT) framework. At the second level, deep knowledge was revealed using a framework called the Elementary Management Cycle (EMC). These two causal frameworks were applied here to justify the causal meta-models of the EA. The new concepts Collapsed Capability, Capability Type and Capability Role which meaningfully complement MODAF with causal knowledge are introduced. Strategic Viewpoint (StV) modelling using causal meta-models is described in detail and illustrated in the case study. The example provided shows a principled way that causal knowledge supports the verification and validation of EA solutions. The presented method provides an opportunity to move the EA development to smart platforms.
Pub. online:1 Jan 2019Type:Research ArticleOpen Access
Volume 30, Issue 3 (2019), pp. 455–480
The paper deals with the causality driven modelling method applied for the domain deep knowledge elicitation. This method is suitable for discovering causal relationships in domains that are characterized by internal circular causality, e.g. control and management, regulatory processes, self-regulation and renewal. Such domains are organizational systems (i.e. enterprise) or cyber-social systems, also biological systems, ecological systems, and other complex systems. Subject domain may be of different nature: real-world activities or documented content. A causality driven approach is applied here for the learning content analysis and normalization of the knowledge structures. This method was used in the field of education, and a case study of learning content renewal is provided. The domain here is a real world area – a learning content is about. The paper is on how to align the existing learning content and current (new) knowledge of the domain using the same causality driven viewpoint and the described models (frameworks). Two levels of the domain causal modelling are obtained. The first level is the discovery of the causality of the domain using the Management Transaction (MT) framework. Secondly, a deep knowledge structure of MT is revealed through a more detailed framework called the Elementary Management Cycle (EMC). The algorithms for updating the LO content in two steps are presented. Traceability matrix indicates the mismatch of the LO content (old knowledge) and new domain knowledge. Classification of the content discrepancies and an example of the study program content analysis is presented. The main outcome of the causality driven modelling approach is the effectiveness of discovering the deep knowledge when the relevant domain causality frameworks are applicable.