Interoperability and Semantic Technologies 2015-16

The course is organised in three parts. In the first part, it starts arguing about the difference between pair-wise system integration and multi-later system interoperability. It introduces the four levels at which the interoperability problem has to be attacked (i.e., legal, organisational, semantic, technical) using the European Interoperability Framework from the ISA program [1] as a case study. It discusses the two ways interoperability can be achieved: standards and translations. It bring examples of long lasting (and low impact) standardisation processes from the Open Geographic Consortium [2] (e.g., GML, OCG web services) and it compares it to the high impact de facto standard of Google KML [3]. It shows how semantic technologies allowed translation-based interoperability on the Web presenting the case of schema.org and google knowledge graph. In the second part, it presents semantic technologies for interoperability. These technologies are very important nowadays because the allow to treat the "variety " dimension of Big Data. It introduces RDF [4]- a flexible data model to (virtually) represent heterogenous data. It describes OWL [5]- a flexible ontological language to model heterogenous data sources in an open world where information cannot be assumed to be complete. It illustrates SPARQL [6]- a query language for RDF. It shows how to put all the pieces together in order to achieve interoperability among heterogenous information systems using principles from ontology-based data integration [7]. The third part covers the realm of interoperability among systems that process streaming data. These systems are ver