Research Topics of jan hidders

Graph Analytics

The analysis of graphs has become important in many domains such as social media, marketing, the life sciences, telecommunication, counter-terrorism and crime fighting. Here the graphs are often so big that specialized techniques and algorithms are necessary to compute the analysis, for example by distributing them in a Spark-cluster. Data analysis tasks on real-world web-scale datasets often involve analysing properties of the graphs represented by those datasets.

Graph Databases and RDF Stores

Graph databases can be seen as a special case of NoSQL databases, however they usually have very specific different implementation techniques and application domains that are different from other NoSQL databases. For example graph database play an important role in graph analytics for domains such as social media, the life sciences, telecommunication and crime fighting.

Large-scale and Distributed Data Processing Platforms

Many platforms for big data processing have emerged in recent years, and many are still emerging with different platforms focussing on different types of data processing such as memory-based data processing, graph processing or stream-based processing.

NoSQL Databases

In recent year all new types of database have emerged for different reasons such a scalability, flexibility and usability. The underlying reasons are that much has changed in the underlying hardware and the way that databases are used. Some notable changes are: