Marzieh Bakhshandeh

Using Ontologies for Enterprise Architecture Integration and Analysis

Enterprise architecture facilitates the alignment between different domains, such as business, applications and information technology. These domains must be described with description languages that best address the concerns of its stakeholders. However, current model-based enterprise architecture techniques are unable to integrate multiple descriptions languages either due to the lack of suitable extension mechanisms or because they lack the means to maintain the coherence, consistency and traceability between the representations of the multiple domains of the enterprise. On the other hand, enterprise architecture models are often designed and used for communication and not for automated analysis of its contents. Model analysis is a valuable tool for assessing the qualities of a model, such as conformance and completeness, and also for supporting decision making. This paper addresses these two issues found in model-based enterprise architecture: (1) the integration of domain description languages, and (2) the automated analysis of models. This proposal uses ontology engineering techniques to specify and integrate the different domains and reasoning and querying as a means to analyse the models. The utility of the proposal is shown through an evaluation scenario that involve the analysis of an enterprise architecture model that spans multiple domains.

Using ontologies to capture the semantics of a (business) process for digital preservation

IT-supported business processes and computationally intensive science (called e-science) have become increasingly ubiquitous in the last decades. Along with this trend comes the need to make at least the most important of these processes available for the long term, to allow later analysis of their execution, or even a re-execution. As such, the preservation of scientific experiments and their results enables others to reproduce and verify the results as well as build on the result of earlier work. All but the simplest processes require to be described by a multitude of information objects, as well as their interconnections and relations, to be successfully preserved. To enable a semantic description of these objects in a structured manner, we developed a formal meta-model that can be utilised in the digital preservation of a process. The meta-model describes classes of elements and their relations, in the form of ontologies, with a core ontology describing the generic concepts, and extension mechanisms to map supplementary ontologies describing more specific aspects. In this paper, we present the overall architecture and individual ontologies, and motivate their usefulness via the application to use cases from different domains.

A Modular Ontology for the Enterprise Architecture Domain

Enterprise architecture supports the analysis, design and engineering of business-oriented systems through multiple views. Each view expresses the elements and relationships of a system from the perspective of specific system concerns relevant to one or more of its stakeholders. As a result, each view needs to expressed in the architecture description language that best suits its concerns. Therefore, an enterprise architecture may be described using a set of different languages. However, current enterprise architecture modelling languages display two issues in this setting. First, they lack mechanisms to integrate multiple architecture description languages. This issue hinders the specification of views using different languages. Second, enterprise architecture models lack quantitative analysis support. This paper describes an ontology-based approach in order to have a modular ontology for the enterprise architecture domain, to specify and integrate multiple architecture modelling languages and to analyse the resulting integrated models. The approach relies on transformations between an upper-domain ontology based on the ArchiMate language and on a set of domain-specific ontologies to deal with the specific architecture modelling languages. The resulting models are quantifiable in the sense they provide the means to assess the consistency of the enterprise architecture models and to analyse their structure. The applicability of the approach is shown through a case study and the correctness of the ontology is shown by a set of competency questions.

Using Ontologies to Integrate Multiple Enterprise Architecture Domains

A goal of enterprise architecture is to align the business with the underlying support systems. An enterprise architecture description encompasses an heterogeneous spectrum of domains, such as business processes, application components, metrics, people and technological infrastructure. Architectural views express the domain elements and their relationships from the perspective of the system stakeholders. As a result, a view needs to be expressed using a domain language that addresses the specific concerns of its stakeholders. However, enterprise architecture description languages are often based on generic or broad meta-models that cross-cut distinct architectural domains. But describing each domain through a specialized language and then integrating it with the other domains raises challenges at the level of traceability and consistency. This paper proposes using ontologies to specify different enterprise architecture domains and to integrate and analyse these models. This goal is realized through a domain-independent language that is extended by domain-specific languages, each focussing on a set of specific domain concerns. The approach contributes to the alignment of the different domains while ensuring traceability between then concepts. The proposal is demonstrated through an evaluation scenario that uses ArchiMate as the domain-independent language extended with a set of domain-specific languages. The demonstration shows that the architecture domains can be integrated and analysed through the use of ontologies.

Representation and analysis of enterprise models with semantic techniques: an application to ArchiMate, e3value and business model canvas

Enterprise models assist the governance and transformation of organizations through the specification, communication and analysis of strategy, goals, processes, information, along with the underlying application and technological infrastructure. Such models cross-cut different concerns and are often conceptualized using domain-specific modelling languages. This paper explores the application of graph-based semantic techniques to specify, integrate and analyse multiple, heterogeneous enterprise models. In particular, the proposal described in this paper (1) specifies enterprise models as ontological schemas, (2) uses transformation mapping functions to integrate the ontological schemas and (3) analyses the integrated schemas with graph querying and logical inference. The proposal is evaluated through a scenario that integrates three distinct enterprise modelling languages: the business model canvas, e3value, and the business layer of the ArchiMate language. The results show, on the one hand, that the graph-based approach is able to handle the specification, integration and analysis of enterprise models represented with different modelling languages and, on the other, that the integration challenge resides in defining appropriate mapping functions between the schemas.

An Ontological Matching Approach for Enterprise Architecture Model Analysis

Enterprise architecture aligns business and information technology through the management of different elements and domains. Performing an integrated analysis of EA models using automated techniques is necessary when EA model representations grow in complexity, in order to support, for example, benchmarking of business processes or assessing compliance with requirements. Moreover, heterogeneity challenges arise from the frequent usage of multiple modelling languages, each based on a specific meta-model that cross-cuts distinct architectural domains. The motivation of this paper is, therefore, to investigate to what extent ontology matching techniques can be used as a means to improve the execution of automated analysis of EA model representations, based on the syntax, structure and semantic heterogeneities of these models. For that, we used AgreementMakerLight, an ontology matching system, to evaluate the matching of EA models based on the ArchiMate and BPMN languages.

Analysis of Federated Business Models: An Application to the Business Model Canvas, ArchiMate, and e3value

Enterprise models contribute to the understanding, communication and analysis of how business processes are performed, the goals they achieve, the information they use, as well as the applications that support the business, and the underlying technological infrastructure. The analysis of these different domains requires combining different enterprise models, often described with different domain specific modelling languages. This paper explores the application of computational semantic techniques to specify, integrate and analyse multiple enterprise models. The models are individually specified and federated using ontological schemas, and analysed using computational inference and graph analysis. The paper describes (1) how to specify enterprise models as ontological schemas, (2) how to integrate the ontological schemas using transformation maps, and (3) how to analyse the integrated models. This solution is demonstrated through the specification, integration and analysis of a business model landscape comprising three enterprise modelling languages: the Business Model Canvas, e3value, and Archi Mate.

Validating Value Network Business Models by Ontologies

Different meta-models allow modeling the business of an organization from different perspectives. The Business Model Canvas focus is close to the strategy of the organization. E3value allows modeling of value networks and ArchiMate allows alignment from business models to IT infrastructure. When models of these three meta-models coexist for a certain value network, they must be consistent. Currently, there is no way to validate such consistency automatically. We propose a solution, using ontologies and ontology mapping techniques (OWL, OWL.DL, SPARQL) that helps to validate instantiated models automatically, based on a set of mapping rules between the three meta-models. In this work, the mappings between Business Model Canvas, e3value and ArchiMate are identified and formalized through ontologies. The formalized mapping is then applied to a case study and exploited, together with reasoning techniques.

Ontology-based enterprise architecture model analysis

An enterprise architecture provides views on heterogeneous domains, such as business processes, people, business rules, application components, and technological infrastructure. These views are defined according to specific concerns and need to be expressed with an adequate description language. This entails integrating the description languages as a means to address the multiple concerns but raises the challenge of keeping the models coherent, consistent and traceable. This work describes an application of ontology engineering to enterprise architecture. The contribution is an extensible architecture description language that includes an upper ontology that can be integrated with multiple domain-specific ontologies, each focusing on different concerns. The resulting integrated models can be automatically analysed.

Ontology-Based Approach for Heterogeneity Analysis of EA Models

The different needs and domains of enterprises and how they employ EA modelling languages and tools can give rise to heterogeneity at the syntactical, structural and semantical levels. In particular, models dealing with the process perspective are becoming increasingly complex and hetereogeneous. This raises difficulties in managing and reusing EA models.