Tracing the use of Communication Technologies in Higher Education

This chapter presents a comprehensive view of the main activities and findings of a research project entitled TRACER-Portuguese Public Higher Education Use of Communication Technologies, which focused on how the information about the use of Communication Technologies in Higher Education Institutions  can be collected, systematized, processed, and deployed to stakeholders. The project was carried out between 2011 and 2014 and its main results are a consolidated proposal of an analysis model to address the use of Communication Technologies in Higher Education institutions, as well as the U-TRACER® tool. This Web-based tool provides support to the process of collecting, processing, and deployment of data related with the use of Communication Technologies in a specific Higher Education or in a group of institutions, based on institutional or geographical criteria.

On the application of contextual IoT service discovery in Information Centric Networks

The continuous flow of technological developments in communications and electronic industries has led to the growing expansion of the Internet of Things (IoT). By leveraging the capabilities of smart networked devices and integrating them into existing industrial, leisure and communication applications, the IoT is expected to positively impact both economy and society, reducing the gap between the physical and digital worlds. Therefore, several efforts have been dedicated to the development of networking solutions addressing the diversity of challenges associated with such a vision. In this context, the integration of Information Centric Networking (ICN) concepts into the core of IoT is a research area gaining momentum and involving both research and industry actors. The massive amount of heterogeneous devices, as well as the data they produce, is a significant challenge for a wide-scale adoption of the IoT. In this paper we propose a service discovery mechanism, based on Named Data Networking (NDN), that leverages the use of a semantic matching mechanism for achieving a flexible discovery process. The development of appropriate service discovery mechanisms enriched with semantic capabilities for understanding and processing context information is a key feature for turning raw data into useful knowledge and ensuring the interoperability among different devices and applications. We assessed the performance of our solution through the implementation and deployment of a proof-of-concept prototype. Obtained results illustrate the potential of integrating semantic and ICN mechanisms to enable a flexible service discovery in IoT scenarios.