A Semantic Data Model to Represent Building Material Data in AEC Collaborative Workflows

The specification of building material is required in multiple phases of engineering and construction projects towards holistic BIM implementations. Building material information plays a vital role in design decisions by enabling different simulation processes, such as energy, acoustic, lighting, etc. Utilization and sharing of building material information between stakeholders are some of the major influencing factors on the practical implementation of the BIM process. Different meta-data schemas (e.g. IFC) are usually available to represent and share material information amongst partners involved in a construction project. However, these schemas have their own constraints to enable efficient data sharing amongst stakeholders. This paper explains these constraints and proposes a methodological approach for the representation of material data using semantic web concepts aiming to support the sharing of BIM data and interoperability enhancements in collaboration workflows. As a result, the DICBM (https://w3id.org/digitalconstruction/BuildingMaterials) ontology was developed which improves the management of building material information in the BIM-based collaboration process.:Abstract 1. Introduction and Background 1.1 Building Information Modeling for collaboration 1.2 Information management in AEC using semantic web technologies 2 DICBM: Digital Construction Building Material Ontology 2.1 Building Material Data in IFC 2.2 Overview of the building material ontology 2.3 Integration of external ontology concepts and roles 2.4 Material Definition 2.5 Material, Material Type, and Material Property 2.6 Data Properties in DICBM 3 Conclusions Acknowledgments Reference

Knowledge Guided Integration of Structured and Unstructured Data in Health Decision Process

Data in the health domain is continuously increasing. It is collected from several sources, has several formats and is characterized by its sensibility (protection of personal health data). These characteristics make the management and the expert interaction with the collected data, in order to facilitate decision-making in Health Information Systems (HIS) a challenging field. In this paper, we propose a Knowledge guided integration of structured and unstructured data for health decision process. The knowledge is represented by domain ontology, which allows the integration of structured and unstructured data, stored in NoSQL format. Our motivation is to combine the confirmed advantages of ontologies and NoSQL databases both in data integration and decision aided processes. The proposed ontology has been implemented and evaluated using quality metrics. The approach was evaluated and results show response time optimization, compared with traditional approaches, and improvement of data relevance

Semantic and Virtual Reality-Enhanced Configuration of Domestic Environments: The Smart Home Simulator

This paper introduces the Smart Home Simulator, one of the main outcomes of the D4All project. This application takes into account the variety of issues involved in the development of Ambient Assisted Living (AAL) solutions, such as the peculiarity of each end-users, appliances, and technologies with their deployment and data-sharing issues. The Smart Home Simulator - a mixed reality application able to support the configuration and customization of domestic environments in AAL systems - leverages on integration capabilities of Semantic Web technologies and the possibility to model relevant knowledge (about both the dwellers and the domestic environment) into formal models. It also exploits Virtual Reality technologies as an efficient means to simplify the configuration of customized AAL environments. The application and the underlying framework will be validated through two different use cases, each one foreseeing the customized configuration of a domestic environment for specific segments of users

Factories of the Future

Engineering; Industrial engineering; Production engineerin