Integration of environmental data in BIM tool & linked building data

Environmental assessment is a critical need to ensure building sustainability. In order to enhance the sustainability of building, involved actors should be able to access and share not only information about the building but also data about products and especially their environmental assessment. Among several approaches that have been proposed to achieve that, semantic web technologies stand out from the crowd by their capabilities to share data and enhance interoperability in between the most heterogeneous systems. This paper presents the implementation of a method in which semantic web technologies and particularly Linked Data have been combined with Building Information Modelling (BIM) tools to foster building sustainability by introducing products with their environmental assessment in building data during the modelling phase. Based on Linked Building Data (LBD) vocabularies and environmental data, several ontologies have been generated in order to make both of them available as Resource Description Framework (RDF) graphs. A database access plugin has been developed and installed in a BIM tool. In that way, the LBD generated from the BIM tool contains, for each product a reference to its environmental assessment which is contained in a triplestore

Semantic web learning technology design: addressing pedagogical challenges and precarious futures

Semantic web technologies have the potential to extend and transform teaching and learning, particularly in those educational settings in which learners are encouraged to engage with ‘authentic’ data from multiple sources. In the course of the ‘Ensemble’ project, teachers and learners in different disciplinary contexts in UK Higher Education worked with educational researchers and technologists to explore the potential of such technologies through participatory design and rapid prototyping. These activities exposed some of the barriers to the development and adoption of emergent learning technologies, but also highlighted the wide range of factors, not all of them technological or pedagogical, that might contribute to enthusiasm for and adoption of such technologies. This suggests that the scope and purpose of research and design activities may need to be broadened and the paper concludes with a discussion of how the tradition of operaismo or ‘workers’ enquiry’ may help to frame such activities. This is particularly relevant in a period when the both educational institutions and the working environments for which learners are being prepared are becoming increasingly fractured, and some measure of ‘precarity’ is increasingly the norm

Template-based ontology population for Smart Environments configuration

Smart Environment is one of several domains in which Semantic Web technologies are applied nowadays. Ontologies, in particular, are used as core modeling languages for representing devices, systems and environments. Developing such ontologies, that typically involve several device descriptions (individuals) and related information, i.e., individuals of classes contributing to the device model, is often done by a manual, time consuming, and error-prone approach. Flexible and semi-automatic tools are therefore needed to enhance ontology population and to enable end-users to fruitfully configure their Smart Environments without the intervention of an ontology expert. This paper presents a template based approach, which increases accuracy, ease of use, and time-effectiveness of the ontology population process by reducing the amount of user-given information of about an order of magnitude, with respect to the fully manual approach. User-required information only pertains device features (e.g., name, location, etc.) and never implies knowledge of Semantic Web technologies, thus enabling end-user configuration of smart homes and buildings. Experimental results with a prototypical implementation confirm the viability of the approach on a real-world use cas

Benchmarking RDF Storage Engines

In this deliverable, we present version V1.0 of SRBench, the first benchmark for Streaming RDF engines, designed in the context of Task 1.4 of PlanetData, completely based on real-world datasets. With the increasing problem of too much streaming data but not enough knowledge, researchers have set out for solutions in which Semantic Web technologies are adapted and extended for the publishing, sharing, analysing and understanding of such data. Various approaches are emerging. To help researchers and users to compare streaming RDF engines in a standardised application scenario, we propose SRBench, with which one can assess the abilities of a streaming RDF engine to cope with a broad range of use cases typically encountered in real-world scenarios. We offer a set of queries that cover the major aspects of streaming RDF engines, ranging from simple pattern matching queries to queries with complex reasoning tasks. To give a first baseline and illustrate the state of the art, we show results obtained from implementing SRBench using the SPARQLStream query-processing engine developed by UPM

SRBench: A streaming RDF/SPARQL benchmark

We introduce SRBench, a general-purpose benchmark primarily designed for streaming RDF/SPARQL engines, completely based on real-world data sets from the Linked Open Data cloud. With the increasing problem of too much streaming data but not enough tools to gain knowledge from them, researchers have set out for solutions in which Semantic Web technologies are adapted and extended for publishing, sharing, analysing and understanding streaming data. To help researchers and users comparing streaming RDF/SPARQL (strRS) engines in a standardised application scenario, we have designed SRBench, with which one can assess the abilities of a strRS engine to cope with a broad range of use cases typically encountered in real-world scenarios. The data sets used in the benchmark have been carefully chosen, such that they represent a realistic and relevant usage of streaming data. The benchmark defines a concise, yet omprehensive set of queries that cover the major aspects of strRS processing. Finally, our work is complemented with a functional evaluation on three representative strRS engines: SPARQLStream, C-SPARQL and CQELS. The presented results are meant to give a first baseline and illustrate the state-of-the-art

Leveraging Semantic Web Technologies for Managing Resources in a Multi-Domain Infrastructure-as-a-Service Environment

This paper reports on experience with using semantically-enabled network resource models to construct an operational multi-domain networked infrastructure-as-a-service (NIaaS) testbed called ExoGENI, recently funded through NSF's GENI project. A defining property of NIaaS is the deep integration of network provisioning functions alongside the more common storage and computation provisioning functions. Resource provider topologies and user requests can be described using network resource models with common base classes for fundamental cyber-resources (links, nodes, interfaces) specialized via virtualization and adaptations between networking layers to specific technologies. This problem space gives rise to a number of application areas where semantic web technologies become highly useful - common information models and resource class hierarchies simplify resource descriptions from multiple providers, pathfinding and topology embedding algorithms rely on query abstractions as building blocks. The paper describes how the semantic resource description models enable ExoGENI to autonomously instantiate on-demand virtual topologies of virtual machines provisioned from cloud providers and are linked by on-demand virtual connections acquired from multiple autonomous network providers to serve a variety of applications ranging from distributed system experiments to high-performance computing

User interaction and uptake challenges to successfully deploying Semantic Web technologies

The Semantic Web community could benefit greatly from 'eating its own dog food' in order to better understand the challenges and opportunities of a Semantic Web from the user perspective. In this paper we describe the deployment of Semantic Web applications and services at the 3rd European Semantic Web Conference (ESWC2006), before presenting results of an evaluation into how these technologies were experienced by delegates. Based on themes identified in the evaluation we highlight seven user interaction and uptake challenges raised by the conference experience, and discuss how these may generalize to the widespread deployment of Semantic Web technologies

Improving Ontology Recommendation and Reuse in WebCORE by Collaborative Assessments

In this work, we present an extension of CORE [8], a tool for Collaborative Ontology Reuse and Evaluation. The system receives an informal description of a specific semantic domain and determines which ontologies from a repository are the most appropriate to describe the given domain. For this task, the environment is divided into three modules. The first component receives the problem description as a set of terms, and allows the user to refine and enlarge it using WordNet. The second module applies multiple automatic criteria to evaluate the ontologies of the repository, and determines which ones fit best the problem description. A ranked list of ontologies is returned for each criterion, and the lists are combined by means of rank fusion techniques. Finally, the third component uses manual user evaluations in order to incorporate a human, collaborative assessment of the ontologies. The new version of the system incorporates several novelties, such as its implementation as a web application; the incorporation of a NLP module to manage the problem definitions; modifications on the automatic ontology retrieval strategies; and a collaborative framework to find potential relevant terms according to previous user queries. Finally, we present some early experiments on ontology retrieval and evaluation, showing the benefits of our system