Embedding learning, a.k.a. representation learning, has been shown to be able to model large-scale semantic knowledge graphs.
Building discovery services for scientific and scholarly content on top of a semantic data model
This talk provides a summary and reflection on how we think that Semantic Technologies are an effective way to do enterprise metadata management at web scale – essentially, being able to bring some order to the chaos resulting from multiple applications working on similar data domains.
Turning Chaos into Clarity
This talk presents our experience with the evolution of semantic technologies in scientific libraries. Starting with semantic document representations and the use of semantic technologies to cross-link digital libraries, the talk will put its main focus on the question how deep web content can be brought to the surface.
Have you ever thought about the relationships between fast food and data? You may well think that fast food chains make a strong use of large sets of data, and you will be probably right. And what about the slow food concept? How much is it related to our data-intensive world? After this talk you may run the risk of looking at data in your computer and seeing food, and viceversa.
In this session, we will cover the importance of relations and relativity of physical objects around smart sensors and devices, and how modeling them in a unified world could help enrich observations and data that’s not possible otherwise when trying them as simply distinct units. I will also cover how information security will completely change because of the adoption of IoT.
The rapidly increasing release of open data from local and national governments around the world provides an opportunity to understand social, economic, and environmental issues within and among cities and countries.
Opening-Keynote September 5, 2014
Linked Data at the BBC: Connecting Content around the Things that matter to our Audiences