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The amount of audio, video and image data on the Web is immensely growing, which leads to data management problems based on the hidden character of Multimedia. Therefore the interlinking of semantic concepts and media data with the aim to bridge the gap between the Internet of documents and the Web of Data has become a common practice. However, the value of connecting media to its semantic meta data is limited due to lacking access methods and the absence of an adapted query language specialized for media assets and fragments. This thesis aims to extend the standard query language for the Semantic Web (SPARQL) with media specific concepts and functions. The main contributions of the work are an exhaustive survey on Multimedia query languages of the last 3 decades, the SPARQL extension specification itself and an approach for the efficient evaluation of the new query concepts. Additionally I elaborate and evaluate a meta data based media fragment similarity approach, which provides a basis for further language extensions.
The main research question of this thesis is to develop a theory that would provide foundations for the development of Web of Things (WoT) systems. A theory for WoT shall provide a model of the ‘things’ WoT agents relate to such that these relations determine what interactions take place between these agents. This thesis presents a knowledge-based approach in which the semantics of WoT systems is given by a transformation (an homomorphism) between a graph representing agent interactions and a knowledge graph describing ‘things’. It focuses on three aspects of knowledge graphs in particular: the vocabulary with which assertions can be made, the rules that can be defined over this vocabulary and its serialization to efficiently exchange pieces of a knowledge graph. Each aspect is developed in a dedicated chapter, with specific contributions to the state-of-the-art.
The need for a unified vocabulary to describe ‘things’ in WoT and the Internet of Things (IoT) has been identified early on in the literature. Many proposals have been consequently published, in the form of Web ontologies. In Ch. 2, a systematic review of these proposals is being developed, as well as a comparison with the data models of the principal IoT frameworks and protocols. The contribution of the thesis in that respect is an alignment between the Thing Description (TD) model and the Semantic Sensor Network (SSN) ontology, two standards of the World Wide Web Consortium (W3C). The scope of this thesis is generally limited to Web standards, especially those defined by the Resource Description framework (RDF).
Web ontologies do not only expose a vocabulary but also rules to extend a knowledge graph by means of reasoning. Starting from a set of TD documents, new relations between ‘things’ can be “discovered” this way, indicating possible interactions between the servients that relate to them. The experiments presented in Ch. 3 were done on the basis of this semantic discovery framework on two use cases: a building automation use case provided by Intel Labs and an industrial control use case developed internally at Siemens. The relations to discover often involve anonymous nodes in the knowledge graph: the chapter also introduces a novel skolemization algorithm to correctly process these nodes on a well-defined fragment of the Web Ontology Language (OWL).
Finally, because this semantic discovery framework relies on the exchange of TD documents, Ch. 4 introduces a binary format for RDF that proves efficient in serializing TD assertions such that even the smallest WoT agents, i.e. micro-controllers, can store and process them. A formalization for the semantics-preserving compaction and querying of TD documents is also introduced in this chapter, at the basis of an embedded RDF store called the µRDF store. The ability of all WoT agents to query logical assertions about themselves and their environment, as found in TD documents, is a first step towards knowledge-based intelligent systems that can operate autonomously and dynamically in a decentralized way. The µRDF store is an attempt to illustrate the practical outcomes of the theory of WoT developed throughout this thesis.