Technical evaluation of the mEducator 3.0 linked data-based environment for sharing medical educational resources

mEducator 3.0 is a content sharing approach for medical education, based on Linked Data principles. Through standardization, it enables sharing and discovery of medical information. Overall the mEducator project seeks to address the following two different approaches, mEducator 2.0, based on web 2.0 and ad-hoc Application Programmers Interfaces (APIs), and mEducator 3.0, which builds upon a collection of Semantic Web Services that federate existing sources of medical and Technology Enhanced Learning (TEL) data. The semantic mEducator 3.0 approach It has a number of different instantiations, allowing flexibility and choice. At present these comprise of a standalone social web-based instantiation (MetaMorphosis+) and instantiations integrated with Drupal, Moodle and OpenLabyrinth systems. This paper presents the evaluation results of the mEducator 3.0 Linked Data based environment for sharing medical educational resources and focuses on metadata enrichment, conformance to the requirements and technical performance (of the MetaMorphosis+ and Drupal instantiations)

Towards evaluation design for smart city development

Smart city developments integrate digital, human, and physical systems in the built environment. With growing urbanization and widespread developments, identifying suitable evaluation methodologies is important. Case-study research across five UK cities - Birmingham, Bristol, Manchester, Milton Keynes and Peterborough - revealed that city evaluation approaches were principally project-focused with city-level evaluation plans at early stages. Key challenges centred on selecting suitable evaluation methodologies to evidence urban value and outcomes, addressing city authority requirements. Recommendations for evaluation design draw on urban studies and measurement frameworks, capitalizing on big data opportunities and developing appropriate, valid, credible integrative approaches across projects, programmes and city-level developments

Sharing Human-Generated Observations by Integrating HMI and the Semantic Sensor Web

Current “Internet of Things” concepts point to a future where connected objects gather meaningful information about their environment and share it with other objects and people. In particular, objects embedding Human Machine Interaction (HMI), such as mobile devices and, increasingly, connected vehicles, home appliances, urban interactive infrastructures, etc., may not only be conceived as sources of sensor information, but, through interaction with their users, they can also produce highly valuable context-aware human-generated observations. We believe that the great promise offered by combining and sharing all of the different sources of information available can be realized through the integration of HMI and Semantic Sensor Web technologies. This paper presents a technological framework that harmonizes two of the most influential HMI and Sensor Web initiatives: the W3C’s Multimodal Architecture and Interfaces (MMI) and the Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) with its semantic extension, respectively. Although the proposed framework is general enough to be applied in a variety of connected objects integrating HMI, a particular development is presented for a connected car scenario where drivers’ observations about the traffic or their environment are shared across the Semantic Sensor Web. For implementation and evaluation purposes an on-board OSGi (Open Services Gateway Initiative) architecture was built, integrating several available HMI, Sensor Web and Semantic Web technologies. A technical performance test and a conceptual validation of the scenario with potential users are reported, with results suggesting the approach is soun

Exploring scholarly data with Rexplore.

Despite the large number and variety of tools and services available today for exploring scholarly data, current support is still very limited in the context of sensemaking tasks, which go beyond standard search and ranking of authors and publications, and focus instead on i) understanding the dynamics of research areas, ii) relating authors ‘semantically’ (e.g., in terms of common interests or shared academic trajectories), or iii) performing fine-grained academic expert search along multiple dimensions. To address this gap we have developed a novel tool, Rexplore, which integrates statistical analysis, semantic technologies, and visual analytics to provide effective support for exploring and making sense of scholarly data. Here, we describe the main innovative elements of the tool and we present the results from a task-centric empirical evaluation, which shows that Rexplore is highly effective at providing support for the aforementioned sensemaking tasks. In addition, these results are robust both with respect to the background of the users (i.e., expert analysts vs. ‘ordinary’ users) and also with respect to whether the tasks are selected by the evaluators or proposed by the users themselves

Services and the Web of Data: an unexploited symbiosis

The Web of Data is certainly a great success for data publication but the state of the art of the applications processing linked data is however not that outstanding. In this paper we highlight an unexploited symbiosis between Semantic Web Services and the Web of Data that could give birth to new families of highly advanced Web applications

D7.3 Training materials

This Deliverable gives a detailed description of the comprehensive training programme and of the open educational content that the University of Padua has accomplished up to now for the project "Linked Heritage: Coordination of standard and technologies for the enrichment of Europeana" (CIP Best Practice Network). The final version of D7.3 will be released by the end of the project, when all the Learning Objects will be finished