Enabling Bidirectional Interoperability between BIM and BPS through Lightweight Topological Models

Building Performance Simulation (BPS) tools have become prevalent in the Architecture, Engineering, Construction, and Operation (AECO) sector to assess building performance for various purposes. However, some challenges persist in achieving full interoperability between BPS and Building Information Modeling (BIM). This paper proposes a different approach to BIM-BPS interoperability based on creating space-based Topological Models (TM) for data exchange using Visual Programming (VP) algorithms. The VP approach allows for complex geometrical operations, the automatic reflection of changes made to the BIM model in the BPS model, and easy synchronous modification of these models to encourage design exploration. The proposed workflow is tested on the heritage building of the Faculty of Engineering in Bologna, Italy, with the aim of establishing the basis for developing a Digital Twin (DT) of the building for optimising its energy management. This approach can also be used for the early-stage analysis of new constructions, providing a comprehensive view of building performance

Contribution to the elaboration of a decision support system based on modular ontologies for ecological labelling

With the rising concern of sustainability and environmental performance, eco-labeled products and services are becoming more and more popular. In addition to the financial costs, the long and complex process of eco-labeling sometimes demotivates manufacturers and service providers to be certificated. In this research work, we propose a decision support process and implement 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. The decision support platform is based on a comprehensive knowledge base composed of various domain ontologies that are constructed according to official eco-label criteria documentation. Traditional knowledge base in relational data model is low interoperable, lack of inference support and difficult to be reused. In our research, the knowledge base composed of interconnected ontologies modules covers various products and services, and allows reasoning and semantic querying. A domain-centric modularization scheme about EU Eco-label laundry detergent product criteria is introduced as an application case. This modularization scheme separates the entity knowledge and rule knowledge so that the ontology modules can be reused easily in other domains. We explore a reasoning methodology based on inference with SWRL (Semantic Web Rule Language) rules which allows decision making with explanation. Through standard RDF (Resource Description Framework) and OWL (Web Ontology Language) ontology query interface, the assets of the decision support platform will stimulate domain knowledge sharing and can be applied into other application. In order to foster the reuse of ontology modules, we also proposed a usercentric approach for federate contextual ontologies (mapping and integration). This approach will create an ontology federation by a contextual configuration that avoid the “OWL:imports” disadvantages. Instead of putting mapping or new semantics in ontology modules, our approach will conserve the extra contextual information separately without impacting original ontologies or without importing all ontologies’ concepts. By introducing this contextualization, it becomes easier to support more expressive semantics in term of ontology integration itself, then it will also facilitate application agents to access and reuse ontologies. To realize this approach, we elaborate a new plug-in for the Protégé ontology editor

Big Data Integration Solutions in Organizations: A Domain-Specific Analysis

Big Data Integration (BDI) process integrates the big data arising from many diverse data sources, data formats presents a unified, valuable, customized, holistic view of data. BDI process is essential to build confidence, facilitate high-quality insights and trends for intelligent decision making in organizations. Integration of big data is a very complex process with many challenges. The data sources for BDI are traditional data warehouses, social networks, Internet of Things (IoT) and online transactions. BDI solutions are deployed on Master Data Management (MDM) systems to support collecting, aggregating and delivering reliable information across the organization. This chapter has conducted an exhaustive review of BDI literature and classified BDI applications based on their domain. The methods, applications, advantages and disadvantage of the research in each paper are tabulated. Taxonomy of concepts, table of acronyms and the organization of the chapter are presented. The number of papers reviewed industry-wise is depicted as a pie chart. A comparative analysis of curated survey papers with specific parameters to discover the research gaps were also tabulated. The research issues, implementation challenges and future trends are highlighted. A case study of BDI solutions implemented in various organizations was also discussed. This chapter concludes with a holistic view of BDI concepts and solutions implemented in organizations

Contribution à l’élaboration d’un système d’aide à la décision basé sur les ontologies modulaires pour la labellisation écologique.

L’usine du futur et les performances environnementales sont de nos jours au cœur des préoccupations. Les produits et services éco-labellisés sont de plus en plus populaires. En plus des coûts financiers engendrés, les processus d’éco-labellisation sont longs et complexes, ce qui démotive parfois les fabricants et les fournisseurs de services à demander des certifications. Dans ce contexte, ce travail de recherche, propose une démarche et une plateforme d’aide à la décision visant à améliorer et à accélérer ce processus afin de démocratiser l’accès à la certification écologique. Les bases de connaissances traditionnelles étant généralement peu interopérables, difficiles à être réutilisées et ne supportant pas les inférences, la plate-forme proposée repose sur une base de connaissances composée de diverses ontologies de domaine construites selon la documentation officielle européenne sur les écolabels. Cette base est composée de modules d'ontologies interconnectées couvrant divers produits et services. Elle permet d’automatiser le raisonnement sur ces connaissances et de les interroger en tenant compte de la sémantique. Un schéma de modularisation orienté suivant le domaine et la catégorie du produit, et portant sur les critères d’écolabels européens des produits détergents est utilisé comme cas d'application. Afin de permettre une réutilisation aisée des modules d'ontologie pour différents groupes de produits, ce schéma de modularisation fait la distinction entre la connaissance de base du domaine et les connaissances variables concernant les critères de labélisation de chaque groupe. La méthode de raisonnement utilisée exploite les mécanismes d'inférence sur des règles SWRL, et fournit des résultats argumentés pour l’aide à la décision. La modélisation adoptée pour la représentation des connaissances n’est pas uniquement dédiée à la plateforme proposée. Elle permet également une exploitation des connaissances via des outils du Web sémantique. Afin de favoriser la réutilisation des modules d'ontologie, une approche de contextualisation pour la fédération d’ontologies a été proposée. Elle permet de pallier les inconvénients de "OWL: imports". Contrairement aux approches existantes, où il est nécessaire de réaliser soit un mapping, soit d’ajouter des relations sémantiques modifiant les modules d’ontologies de base, notre approche n’affecte pas et ne nécessite pas l’importation de tous les concepts de ces ontologies. Pour faciliter la mise en œuvre de cette approche, nous proposons un nouveau plug-in pour l'éditeur d'ontologie « Protégé ».With the rising concern of sustainability and environmental performance, eco-labeled products and services are becoming more and more popular. In addition to the financial costs, the long and complex process of eco-labeling sometimes demotivates manufacturers and service providers to be certificated. In this research work, we propose a decision support process and implement 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. The decision support platform is based on a comprehensive knowledge base composed of various domain ontologies that are constructed according to official eco-label criteria documentation. Traditional knowledge base in relational data model is low interoperable, lack of inference support and difficult to be reused. In our research, the knowledge base composed of interconnected ontologies modules covers various products and services, and allows reasoning and semantic querying. A domain-centric modularization scheme about EU Eco-label laundry detergent product criteria is introduced as an application case. This modularization scheme separates the entity knowledge and rule knowledge so that the ontology modules can be reused easily in other domains. We explore a reasoning methodology based on inference with SWRL (Semantic Web Rule Language) rules which allows decision making with explanation. Through standard RDF (Resource Description Framework) and OWL (Web Ontology Language) ontology query interface, the assets of the decision support platform will stimulate domain knowledge sharing and can be applied into other application. In order to foster the reuse of ontology modules, we also proposed a usercentric approach for federate contextual ontologies (mapping and integration). This approach will create an ontology federation by a contextual configuration that avoid the “OWL:imports” disadvantages. Instead of putting mapping or new semantics in ontology modules, our approach will conserve the extra contextual information separately without impacting original ontologies or without importing all ontologies’ concepts. By introducing this contextualization, it becomes easier to support more expressive semantics in term of ontology integration itself, then it will also facilitate application agents to access and reuse ontologies. To realize this approach, we elaborate a new plug-in for the Protégé ontology editor