Opening by Elmar Kiesling, TU Wien and Tassilo Pellegrini, UAS St. Pölten
Ten years into Linked Data there are still many unresolved challenges towards arriving at a truly machine-readable and decentralized stage that would make the promised vision of a Web of Data come true. In this talk we will review the current state of affairs and highlight the key technical and non-technical challenges to the success of LOD. Finally, we will outline potential solution strategies.
Vienna University of Economics and Business
http://www.wu.ac.at/infobiz/en/
Dr. Javier D. Fernández is a post-doctoral research fellow at Vienna University of Economics and Business (WU). His current research focuses on efficient management of Big Semantic Data, privacy-aware Big Data technologies and archiving and querying dynamic Linked Data.
In this presentation, I will show through a number of examples how Linked Open Data, and especially DBpedia, have contributed to AI by making it possible to create intelligent, open domain applications, i.e. applications which do not have a fixed domain, or for which this domain is not known in advance. This was made evident through a number of high profile applications (e.g. IBM Watson), but is also now being used for a wide variety of cases, including when having to process streams of ill-described content not restricted to a specific application domain.
Professor of Informatics, Researcher and Developer
NUI Galway
https://www.nuigalway.ie
I’m a Professor of Informatics specialised in data analytics and semantic technologies at the Insight Centre for Data Analytics of the National University of Ireland Galway.
