41,882 research outputs found
BIM-to-BRICK: Using graph modeling for IoT/BMS and spatial semantic data interoperability within digital data models of buildings
The holistic management of a building requires data from heterogeneous
sources such as building management systems (BMS), Internet-of-Things (IoT)
sensor networks, and building information models. Data interoperability is a
key component to eliminate silos of information, and using semantic web
technologies like the BRICK schema, an effort to standardize semantic
descriptions of the physical, logical, and virtual assets in buildings and the
relationships between them, is a suitable approach. However, current data
integration processes can involve significant manual interventions. This paper
presents a methodology to automatically collect, assemble, and integrate
information from a building information model to a knowledge graph. The
resulting application, called BIM-to-BRICK, is run on the SDE4 building located
in Singapore. BIM-to-BRICK generated a bidirectional link between a BIM model
of 932 instances and experimental data collected for 17 subjects into 458 BRICK
objects and 1219 relationships in 17 seconds. The automation of this approach
can be compared to traditional manual mapping of data types. This scientific
innovation incentivizes the convergence of disparate data types and structures
in built-environment applications
Charting Past, Present, and Future Research in the Semantic Web and Interoperability
Huge advances in peer-to-peer systems and attempts to develop the semantic web have revealed a critical issue in information systems across multiple domains: the absence of semantic interoperability. Today, businesses operating in a digital environment require increased supply-chain automation, interoperability, and data governance. While research on the semantic web and interoperability has recently received much attention, a dearth of studies investigates the relationship between these two concepts in depth. To address this knowledge gap, the objective of this study is to conduct a review and bibliometric analysis of 3511 Scopus-registered papers on the semantic web and interoperability published over the past two decades. In addition, the publications were analyzed using a variety of bibliometric indicators, such as publication year, journal, authors, countries, and institutions. Keyword co-occurrence and co-citation networks were utilized to identify the primary research hotspots and group the relevant literature. The findings of the review and bibliometric analysis indicate the dominance of conference papers as a means of disseminating knowledge and the substantial contribution of developed nations to the semantic web field. In addition, the keyword co-occurrence network analysis reveals a significant emphasis on semantic web languages, sensors and computing, graphs and models, and linking and integration techniques. Based on the co-citation clustering, the Internet of Things, semantic web services, ontology mapping, building information modeling, bioinformatics, education and e-learning, and semantic web languages were identified as the primary themes contributing to the flow of knowledge and the growth of the semantic web and interoperability field. Overall, this review substantially contributes to the literature and increases scholars’ and practitioners’ awareness of the current knowledge composition and future research directions of the semantic web field. View Full-Tex
Interoperability in IoT through the semantic profiling of objects
The emergence of smarter and broader people-oriented IoT applications and services requires interoperability at both data and knowledge levels. However, although some semantic IoT architectures have been proposed, achieving a high degree of interoperability requires dealing with a sea of non-integrated data, scattered across vertical silos. Also, these architectures do not fit into the machine-to-machine requirements, as data annotation has no knowledge on object interactions behind arriving data. This paper presents a vision of how to overcome these issues. More specifically, the semantic profiling of objects, through CoRE related standards, is envisaged as the key for data integration, allowing more powerful data annotation, validation, and reasoning. These are the key blocks for the development of intelligent applications.Portuguese Science and Technology Foundation (FCT) [UID/MULTI/00631/2013
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