GraphLab Platform – Overview and History by Simon Bin
GraphLab is a graph-based distributed computation framework. It was developed from 2009 at Carnegie Mellon University. At that time it was competing with Hadoop on Graph processing. The typical example algorithm demonstrated with it is the PageRank calculation. It still appears today in the Spark GraphX documentation as a filler for the computation step. We will look at the architecture, sample code and what happened to GraphLab today.
Versioning of Arbitrary RDF Data (PhD progress report) by Marvin Frommhold
A major challenge of B2B Data Networks is efficient synchronization of data between the participants, this is especially true for Linked Data based networks. The exchange of the differences only has thereby proved to be very bandwidth and memory-friendly. Unfortunately, there is a lack of robust and highly efficient versioning and synchronization protocols for Linked Data which hinders a wide adoption of Linked Data in B2B communication. For this reason we develop a versioning system for arbitrary RDF data as part of the LUCID and LEDS research projects. The system will be a feature of the eccenca Linked Data Suite. A big challenge in versioning of RDF data is blank node support. Our approach creates patches which allow to address blank nodes without the need to make changes to the original dataset. This forms the foundation for a comprehensive versioning of any RDF data which enables efficient data exchange in a distributed network.
About the AKSW Colloquium
This event is part of a series of events about Semantic Web technology. Please see http://wiki.aksw.org/Colloquium for further information about previous and future events. As always, Bachelor and Master students are able to get points for attendance and there is complimentary coffee and cake after the session.