GSO: Designing a Well-Founded Service Ontology to Support Dynamic Service Discovery and Composition

A pragmatic and straightforward approach to semantic service discovery is to match inputs and outputs of user requests with the input and output requirements of registered service descriptions. This approach can be extended by using pre-conditions, effects and semantic annotations (meta-data) in an attempt to increase discovery accuracy. While on one hand these additions help improve discovery accuracy, on the other hand complexity is added as service users need to add more information elements to their service requests. In this paper we present an approach that aims at facilitating the representation of service requests by service users, without loss of accuracy. We introduce a Goal-Based Service Framework (GSF) that uses the concept of goal as an abstraction to represent service requests. This paper presents the core concepts and relations of the Goal-Based Service Ontology (GSO), which is a fundamental component of the GSF, and discusses how the framework supports semantic service discovery and composition. GSO provides a set of primitives and relations between goals, tasks and services. These primitives allow a user to represent its goals, and a supporting platform to discover or compose services that fulfil them

Sustainable operations of industrial symbiosis: an enterprise input-output model integrated by agent-based simulation

Industrial symbiosis (IS) is a key for implementing circular economy. Through IS, wastes produced by one company are used as inputs by other companies. The operations of IS suffers from uncertainty barriers since wastes are not produced upon demand but emerge as secondary outputs. Such an uncertainty, triggered by waste supply-demand quantity mismatch, influences IS business dynamics. Accordingly, companies have difficulty to foresee potential costs and benefits of implementing IS. The paper adopts an enterprise input-output model providing a cost–benefit analysis of IS integrated to an agent-based model to simulate how companies share the total economic benefits stemming from IS. The proposed model allows to explore the space of cooperation, defined as the operationally favourable conditions to operate IS in an economically win-win manner. This approach, as a decision-support tool, allows the user to understand whether the IS relationship is created and how should the cost-sharing policy be. The proposed model is applied to a numerical example. Findings show that cost-sharing strategies are dramatically affected by waste supply-demand mismatch and by the relationship between saved and additional costs to run IS. Apart from methodological and theoretical contributions, the paper proposes managerial and practical implications for business strategy development in IS