Linked Data for Smart Homes: Comparing RDF and Labeled Property Graphs

The need to integrate siloed data in the built environment led to a gaining interest in semantic web technologies in the Architecture, Engineering and Construction (AEC) sector. Especially for smart home developments, the integration of information about the building, users and Internet of Things (IoT) devices could be valuable. The Resource Description Framework (RDF) is the standard model for the semantic web, however, labeled property graphs (LPG) also proved to be effective in linking data. This research used the Open Smart Home Dataset and a dataset representing a kitchen to compare the two graph models both qualitatively and quantitatively. The comparison shows that native labeled property graphs are less complex and outperform the atomic RDF in complex graph traversals. However, RDF shows qualitative advantages for multi-domain and multi-stakeholder environments, such as the use of ontologies and HTTP URIs, making it a more stable interoperability format.</p

Een model voor verkoop van callopties op bezittingen in de (ICT-)industrie

In dit artikel is een model beschreven waarmee callopties kunnen worden verkocht op reële – niet-financiële – goederen. Dit model is gebaseerd op de Opties voor Opties-theorie van Baken (2001) en het binomiale optiewaarderingsmodel. Met de verkoop van callopties op bezittingen genereert de verkoper additionele inkomsten door ontvangst van een optiepremie en verplicht hij zich tot levering van de bezittingen, mits de koper van de calloptie zijn verworven recht uitoefent. Om ervoor te zorgen dat het model breed toepasbaar is, zijn bij het ontwerp van het model gevalstudies verricht naar mogelijke praktijkvoorbeelden bij KPN. Onderzocht is welke variabelen de theoretische waarde van een calloptie bepalen en wat de kritische succesfactoren zijn bij de verkoop van callopties op materiële bezittingen

Semantic web technologies as enablers for truly connected mobility within smart cities

Most car manufacturers predict that in the first half of the next decade there will be fully autonomous vehicles on our roads. Such vehicles would have to communicate in order to mitigate problems caused by single-viewpoint approach. So there are a lot of researches and developments when it comes to communication layer of V2X (Vehicle-to-Everything), but there is still a lot to be done when it comes to data layer of this communication. This is why we propose using Semantic Web Technologies (SWT) to fill in gaps within data layer of V2X communication. By using SWT (Semantic Web Technologies) and Linked data, we plan to interconnect various data sources, in order to provide homogeneous way for connected autonomous vehicles (CAV) to access relevant information. Such information is currently contained in three distinctive type of sources. These are: Geo-stationary Static data sources (Maps, City models), Geostationary Dynamic data sources (IoT devices) and Non-geostationary Dynamic sources (Vehicles). Using SWT, our goal is to develop ontology(s), in such a way that in-vehicle algorithms can extract and process information about environment they are in, while taking into account available network bandwidth

Valuation Model for Adding Energy Resource into Autonomous Energy Cluster

ABSTRACT With the availability of distributed generation (DG), clusters that can autonomously manage their energy profile are emerging in the power grid. These autonomous clusters manage their load profiles by orchestrating their energy resources, such as DG, storage, flexible energy consuming appliances, etc. The performance of such an autonomous cluster depends on the composition of its energy resources. In this paper, we study how the performance of a cluster is affected by adding energy resources such as generating units, storage systems or consuming appliances. First, we characterize the energy resources by parameters that describe their relevant properties. Afterwards, we describe a comprehensive set of performance indicators of a cluster that capture the economical, environmental, and social aspects. We present a model that shows how the energy resources influence the performance indicators of the cluster. We have tested our model with a case study, revealing its effectiveness to evaluate the value added by an energy resource to a cluster

A Visual Support Tool for Decision-Making over Federated Building Information

Interconnecting building information on multiple scales and lifecycle stages enables designers to improve their decision-making and tackle ecological, societal, and economical challenges. However, this information is often generated in different software tools, saved in different file formats, using a stakeholder’s own domain language, and is stored in decentral storage locations. This paper presents a tool that integrates data from different stakeholders into a single viewpoint. The tool – LBDviz – combines a browser-based IFC viewer and semantic web technologies to combine geometry with other data that falls outside the scope of the IFC schema. The tool is tested in multiple case studies. These case studies range from requirement checking during the design phase, generating design feedback during the operational phase, and maintaining building performance in a sustainable and economically viable manner. The results of these studies can be reused in future designs, stimulating a more circular design process. The method used in LBDviz enables the interconnection of data within and without the architectural design domain and reduces data interoperability challenges in many lifecycle phases of a construction project

Semantic Web Technologies for Indoor Environmental Quality: A Review and Ontology Design

Indoor environmental quality (IEQ) affects occupants’ satisfaction, health, productivity, comfort, and well-being. IoT developments enable better monitoring of IEQ parameters; however, integrating the various types of heterogeneous data from both the IoT and BIM domains is cumbersome and capital intensive, and therefore, limits the potential of smart buildings. Semantic web technologies can reduce heterogeneity issues, which is necessary to facilitate complex IEQ models. An ontology integrating data related to a building’s topology and its static and dynamic properties is still lacking. The outline of this research is twofold. First, a systematic literature review was conducted to find state-of-the-art semantic web technologies related to building topology, static properties, and dynamic properties from the IoT and BIM domains. By graphically reviewing various ontologies, their valuable patterns, commonalities, and best practices were revealed. Secondly, those results were used to develop a new ontology that integrates topological building information with static and dynamic properties. This Building Performance Ontology (BOP) provides a generic upper-level description of properties and two lower-level ontologies representing observations and actuation. The ontology results in intuitive queries and is both horizontally and vertically extensible. Multiple levels of detail are introduced to ensure practical applicability and efficient patterns based on the data modeler’s needs. BOP opens up a new range of research opportunities in the IEQ domain