Strategic Reasoning for Enterprise Architectures: The SIENA Modeling Framework

PhD candidate Evellin Cristine Souza Cardoso

2 marzo 2018
Versione stampabile

Time: h 10:00 am
Location: Room Ofek, via Sommarive 5: Polo Ferrari 1

PhD candidate

  • Evellin Cristine Souza Cardoso

Abstract of Dissertation

This thesis contributes to the area of Enterprise Modeling by proposing the SIENA modeling framework for the representation of strategic enterprise architectures and automated reasoning with such models.

In this work, we provide the SIENA language that provides abstractions for capturing enterprise’s motivational elements (i.e. goals of different shades like mission, vision, strategic, tactical and operational goals) and their connections with behavioral elements (i.e., operations, business processes, commitments and activities) through which they are operationalized.

The SIENA language also introduces the distinguishing feature of dimensional refinement operators, a new operator that can be used for the refinement of strategic goals in terms of time, location and products/services dimensions. SIENA language is also accompanied by modeling guidelines for the construction of its models. Besides the SIENA language, we also propose a business process language called Azzurra which is founded on the primitives of commitments and protocols for the representation of business processes. The representation of business processes in terms of commitments is a distinguishing feature of our approach.

Further, our framework also supports the design of business processes specified using the Azzurra language from SIENA operational goals. As one of the greatest advantages of conducting enterprise modeling is to gain the ability of performing automated analysis using enterprise models, we also propose a formal reasoning technique for the automated generation of strategic plans subject to constraints to satisfy enterprise’s strategic goals.

The overall approach is validated by means of a number of different activities, including self-evaluation, experimentation and in-depth case studies with novices.