J.A. Lehto

Bio: J.A. Lehto is an academic researcher from Nokia Networks. The author has contributed to research in topics: Software system & Information system. The author has an hindex of 1, co-authored 1 publications receiving 7 citations.

Defining Complexity Factors for the Architecture Evaluation Framework

Abstract: The design and implementation of telecommunication systems is an incremental and iterative process, and system architectures may need to be revised and refined several times during their lifetime. Formal evaluation facilitates the identification of the weak points, where improvements are due in these architectures. In the domain of telecommunications, such evaluation can be based on the Architecture Evaluation Framework (AEF). During the evaluation, a deep understanding of the processes within a system is needed. Meanwhile, the systems being designed are usually complex systems encompassing a large number of components with an intricate pattern of interaction between them. As a result, it is extremely difficult to understand, predict and control the behavior of such systems. Theoretical studies in the field of complex systems describe potential reasons of system complexity, and explain its possible outcomes, as reflected in system structure and behavior. This knowledge may be utilized in architecture evaluation, in order to deepen the understanding of the interactions imposed by the architecture, as well as to extend the understanding of the involved architectural tradeoffs. For this, the complexity factors should be taken into account during the evaluation. However, no such factors are involved in the current version of the AEF. In this paper, the attempt is made to identify how the knowledge about properties of complex systems could be utilized for the evaluation of information system architectures. Based on the theoretical advances in the field of complex systems, a list of the complexity factors to be included in the AEF is compiled. These factors are going to be further refined, as the AEF is employed for evaluating real-world architectures.

Enterprise Architecture Analysis and Network Thinking: A Literature Review

Abstract: Previous works in enterprise architecture (EA) literature has mostly dealt with EA principles, qualitative aspects like EA value and benefits, modeling efforts like Archimate, and methodologies for EA implementation like The Open Group Architecture Framework (TOGAF) and others. Today, these are all common subjects in EA literature. In this paper, we are going in a complementary direction, aiming to contribute towards fostering a set of EA analysis methods based on network measures, considering the enterprise as a complex network. Thus, we present a central question: What is known about the application of network measures in order to analyze components and relationships in the EA context? To answer this question, we perform a broad literature review and create a state-of-the-art description of EA network analysis, applied measures and its main achievements. We also provide a research agenda for the field.

Business Information Driven Approach for EA Development in Practice

Abstract: In this paper, we extrapolate findings of using the Genre and Ontology based Business Information Architecture Framework (GOBIAF) as a methodology to approach enterprise architecture (EA) development from business perspective. GOBIAF seems to contribute as the first business critical information driven framework for EA development, addressing the importance on integrating (information creation) context to (information) content. GOBIAF was developed for and applied in a knowledge intensive, heterogeneous, and geographically dispersed environment in process industries. In the context, GOBIAF increased our knowledge of complex relationships between business, information, and technical domains. Further, GOBIAF provided needed structure for evaluating and developing difficult and heterogeneous issues in relation to organizational strategies.

Combining Network Measures and Expert Knowledge to Analyze Enterprise Architecture at the Component Level

Abstract: Enterprise architecture (EA) network analysis has been attracting researchers' attention lately. The main source of information is the structural components, including the relations among them and how they might be structurally arranged. These relations are studied to generate valuable information for EA professionals. However, to the best of our knowledge, ours is the first attempt to combine structural information with a second source of information: expert's tacit knowledge. We believe combining these sources employing two new methods - what we call cognitive-structural diagnosis analysis and attribute check analysis - can refine the expert's knowledge about the architecture. To demonstrate these methods' feasibility, we apply them with two application architecture datasets collected in two different organizations. We also offer a classification schema for enterprise architecture network analysis at the component level, our focus. Our conclusions indicate that the cognitive- structural diagnosis analysis method minimizes analysis subjectivity while validating important components and also suggesting important structural ones to be further analyzed by experts. The attribute check analysis offers further contributions by helping in the investigation of particular attributes of applications in important architectural positions.

Contextualizing Planning Support (Systems) : Co-designing to fit the dynamics of spatial strategy making

Abstract: Rapid advancements in computer technologies have had a significant impact on the field of spatial planning. However, their added value during the strategic stages of this process remains limited. This thesis takes spatial strategy making under the loupe to examine the dynamics involved in these highly complex and communicative stages. Planning support in the form of serious games is designed together with planning actors as a means of facilitating inter-actor communication and of involving actors in the model building process. The main conclusion of the thesis is that skilled facilitation is needed that structures group processes involving more flexible support, with dedicated support given to individual work.

Network Science Applied to Enterprise Architecture Analysis: Towards the Foundational Concepts

Abstract: Earlier research has identified network analysis techniques, methods, and models used to analyze structural aspects of an enterprise architecture (EA) modeled as a network or graph. However, there is still no common set of conceptual elements for such research that could allow one to identify the information requirements needed to perform this type of analysis. In the present research, we organize foundational conceptual elements in a meta-model as a step towards fostering the development of this research field and creating alignment among researchers. As a second contribution, we classify the existing knowledge about network analysis in an EA context through a systematic literature review, according to the proposed meta-model; this results in a library of 74 network analysis initiatives (e.g., metrics or methods) for EA, which we evaluate reasoning about their efficacy and utility and also surveying experts. Our work thus identifies and systematizes the state of art of network science as a toolset to be applied in the EA context.