Towards a Semantic Web of Everything

Abstract

Environments, people, objects, processes, and data are increasingly interconnected according to the Internet of Things (IoT), progressively shaping the so-called Internet of Everything (IoE). This novel paradigm requires intelligence in information processing and management at all scales, from the World Wide Web to nano-networks. Such heterogeneity exacerbates the well-known interoperability issues of IoT architectures and applications. In the last decade, the Semantic Web of Things (SWoT) has promoted the integration of knowledge representation (KR) and reasoning capabilities into IoT contexts. Annotations referring to shared knowledge graphs are associated to devices, objects, and phenomenons to describe them in rich, structured, and interoperable ways. Unambiguous semantics enables automated reasoning procedures to infer implicit knowledge and to provide crucial resource/service discovery capabilities in volatile contexts. The evolution of the IoT toward the IoE demands a consequent advancement of the SWoT towards a Semantic Web of Everything (SWoE), where semantic technologies support interactions at multiple scales. In the SWoE, inference procedures must be available locally on tiny autonomous devices, despite strict processing, memory, and energy constraints, as the availability of more powerful companion nodes acting as semantic facilitators is not always granted. Furthermore, capillary distribution of data processing towards the field improves efficiency, timeliness, privacy and security. Unfortunately, reasoning engine designs are currently oriented to the Web or powerful mobile devices such as tablets and smartphones. Novel approaches are needed for the SWoE to include inexpensive embedded sensors and boards for wearable devices or manufacturing and medical equipment. The talk presents the SWoE vision, recalling standard and non-standard reasoning services which can be exploited as basic building blocks. SWoE-oriented reasoning engine architectures are subsequently outlined, with emphasis on multiplatform support and resource efficiency. Finally, research results will be outlined in a range of pervasive computing scenarios, including semantics-enhanced machine learning, Social Internet of Things based on LDP-CoAP (Linked Data Platform on the Constrained Application Protocol), information fusion in vehicular networks, and semantic smart contracts for blockchain platforms.

Biography

Floriano Scioscia received the M.S. degree in information technology engineering and Ph.D. degree in information engineering from the Polytechnic University of Bari, Bari, Italy, in 2006 and 2010, respectively. Since 2018 he is an Assistant Professor at the Technical University of Bari, Bari, Italy. His research interests include pervasive computing and the Internet of Things, knowledge representation and reasoning systems, intelligent cyber-physical systems and knowledge representation for digital ledger technologies. He has co-authored over 90 papers in international peer-reviewed edited books, journals, and conferences. Dr. Scioscia was the recipient of Best Paper Awards at the ISUOG 2006, ICEC-2007 and SEMAPRO-2010 conferences, national award for his Ph.D. thesis from the Italian Association for Artificial Intelligence (AIxIA) and Google IoT Technology Research Award in 2016.