Home // Integration of Graph-Analytics Operators within the KNIME-Analytics Platform
Type of thesis: Masterarbeit / location: Leipzig / Status of thesis: Finished theses
The graph-based storage and processing of large amounts of data is becoming increasingly important. In our work we encounter large networks of interactions between genes, proteins and processes in the life sciences, chemical compounds and their reactions in chemistry or information graphs in the business domain. A particularly prominent example Facebook offers its users access to information of the social network through a graph search.
In a current project at the University of Leipzig, a novel graph-processing platfom (GRADOOP) is developed, which simplifies the entire process of creating a graph, its processing and analysis with the help of standardized operators and workflows. These workflows are then efficiently executed and distributed by using Apache Flink.
In this Master thesis we would like to investigate how we could integrate gradoop operators into the workflowbased data analytics tool KNIME. KNIME provides a visual programming paradigm to develop analytics workflows that are executed on Big Data Infrastructures such as Hive or Spark.
Department of computer science
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