In this paper, we present a domain-specific, open access, reference ontology (ROMAIN) for the maintenance management domain. We use a hybrid approach, based on a top-down alignment to an open source top-level ontology, the Basic Formal Ontology (BFO)

Digital revolution produces massive, heterogeneous and isolated data. These latter remain underutilized, unsuitable for integrated querying and knowledge discovering. Hence the importance of this survey on data integration which identifies challenging issues and trends. First, an overview of the different generations and basics of data integration is given. Then, semantic data integration is focused, since it semantically links data allowing wider insights and decision-making. More than thirty works are reviewed. The goal is to help analysts to identify relevant criteria to compare then choose among semantic data integration approaches, focusing on the category (materialized, virtual or hybrid) and querying techniques.

Managing complex disaster situations is a challenging task because of the large number of actors involved and the critical nature of the events themselves. In particular, the different terminologies and technical vocabularies that are being exchanged among Emergency Responders (ERs) may lead to misunderstandings. Maintaining a shared semantics for exchanged data is a major challenge. To help to overcome these issues, we elaborate a modular suite of ontologies called POLARISCO that formalizes the complex knowledge of the ERs. Such a shared vocabulary resolves inconsistent terminologies and promotes semantic interoperability among ERs. In this work, we discuss developing POLARISCO as an extension of Basic Formal Ontology (BFO) and the Common Core Ontologies (CCO). We conclude by presenting a real use-case to check the efficiency and applicability of the proposed ontology.

Disaster response is a highly collaborative and critical process that requires the involvement of multiple emergency responders (ERs), ideally working together under a unified command, to enable a rapid and effective operational response. Following the 9/11 and 11/13 terrorist attacks and the devastation of hurricanes Katrina and Rita, it is apparent that inadequate communication and a lack of interoperability among the ERs engaged on-site can adversely affect disaster response efforts. Within this context, we present a scenario-based terrorism case study to highlight the challenges of operational disaster command and response. In this article, which is based on the French emergency response doctrine, we outline a semantics-based common operational command system that is designed to guarantee an efficient information flow among ERs. Our focus is on offering to all ERs, a real-time operational picture of the situation in order to enable multilevel coordination among firefighters, police, healthcare units, public authorities, and other stakeholders. Our approach consolidates information to promote timely sharing of data among ERs. The proposed system is based on an ontology that has been developed to represent the different types of knowledge on the part of ERs, providing a shared vocabulary that covers a variety of interoperability concerns.

Purpose: With the rising concern of safety, health and environmental performance, eco-labeled product and service are becoming more and more popular. However, the long and complex process of eco-labeling sometimes demotivates manufacturers and service providers to be certificated. The purpose of this paper is to propose a decision support platform aiming at further improvement and acceleration of the eco-labeling process in order to democratize a broader application and certification of eco-labels, also to consolidate the credibility and validity of eco-labels. Design/methodology/approach: This decision support platform is based on a comprehensive knowledge base composed of various domain ontologies that are constructed according to an official eco-label criteria documentation. Findings: Through standard Resource Description Framework and Web Ontology Language ontology query interface, the assets of the decision support platform will stimulate domain knowledge sharing and can be applied into other applications. A case study of laundry detergent eco-labeling process is also presented in this paper. Originality/value: The authors present a reasoning methodology based on inference with Semantic Web Rule Language (SWRL) rules which allows decision making with explanation.