Monitoring morphisms to support sustainable interoperability of enterprise systems

Dissertation to obtain the Master degree in Electrical Engineering and Computer ScienceNowadays, organizations are required to be part of a global collaborative world. Sometimes this is the only way they can access new and wider markets, reaching new opportunities, skills and sharing assets, e.g. tools, lessons learnt. However, due to the different sources of enterprise models and semantics, organizations are experiencing difficulties in exchanging vital information via electronic and in a seamlessly way. To solve this issue, most of them try to attain interoperability by establishing peer-to-peer mappings with different business partners, or in optimized networks using neutral data standards to regulate communications. Moreover, the systems are more and more dynamic, changing frequently to answer new customer’s requirements, causing new interoperability problems and a reduction of efficiency. This dissertation proposes a multi-agent system to monitor existing enterprise systems, by being capable of detecting morphism changes. With this, network harmonization breakings are timely detected, and possible solutions are suggested to regain the interoperable status, thus enhancing robustness for reaching sustainability of business networks

Semantic adaptability for the systems interoperability

In the current global and competitive business context, it is essential that enterprises adapt their knowledge resources in order to smoothly interact and collaborate with others. However, due to the existent multiculturalism of people and enterprises, there are different representation views of business processes or products, even inside a same domain. Consequently, one of the main problems found in the interoperability between enterprise systems and applications is related to semantics. The integration and sharing of enterprises knowledge to build a common lexicon, plays an important role to the semantic adaptability of the information systems. The author proposes a framework to support the development of systems to manage dynamic semantic adaptability resolution. It allows different organisations to participate in a common knowledge base building, letting at the same time maintain their own views of the domain, without compromising the integration between them. Thus, systems are able to be aware of new knowledge, and have the capacity to learn from it and to manage its semantic interoperability in a dynamic and adaptable way. The author endorses the vision that in the near future, the semantic adaptability skills of the enterprise systems will be the booster to enterprises collaboration and the appearance of new business opportunities

A Tentative Framework for Risk and Opportunity Detection in A Collaborative Environment Based on Data Interpretation

This article deals with the question of risk and opportunity identification based on data management as one main step of the convergence of artificial intelligence and industrial engineering. Two main subjects are addressed in this article: (i) the data management framework that could be the backbone for the whole approach, and (ii) the modeling theoretical background that could be used as a basement for the definition of a formal system for risk and opportunity modeling. The general principles presented in the article are used to define outlooks and to organize them as milestone of a roadmap