Prof. Dr. Felix Naumann
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ProLOD++ Profiling and Mining Linked Open Data

ProLOD++ is a web-based profiling tool, which allows you to analyze Linked Open Data (LOD) and thus helps you to gain a deeper understanding of the underlying structure and semantics. You can try it out here or find the code on github (CC-BY-SA).

LOD is data published on the Web adhering to a set of design principles. There is a notable growth of such LOD sources, which provide a wealth of information. Usually, these data sets are very large (millions of facts) and often heterogeneous (e.g. have a loose structure or are poorly formatted, etc.). This heterogeneity causes potential data quality issues. ProLOD++ helps to identify these problems.

ProLOD++ is able to process arbitrary LOD sources by analyzing N-Triple files containing all information of a dataset. Currently, the access to this automated analysis is not publicly available, i.e., you cannot upload NT files to be analyzed. However, if you are interested in profiling a specific data set, feel free to contact us. Also, you are welcome to play with the data sources we already uploaded, e.g., DBpedia and LinkedMDB. Your feedback is appreciated.



Anja Jentzsch, Christian Dullweber, Pierpaolo Troiano, Felix Naumann. Exploring Linked Data Graph Structures. In Proceedings of Posters and Demos Session, ISWC 2015, Bethlehem, PA, USA, October 2015.

Ziawasch Abedjan, Toni Gruetze, Anja Jentzsch, Felix Naumann. Profiling and Mining RDF Data with ProLOD++.In Proceedings of the IEEE International Conference on Data Engineering (ICDE), Demo, Chicago, IL, 2014.

Christoph Böhm, Felix Naumann, Ziawasch Abedjan, Dandy Fenz, Toni Grütze, Daniel Hefenbrock, Matthias Pohl, David Sonnabend. Profiling linked open data with ProLOD. In Workshops Proceedings of the 26th International Conference on Data Engineering (ICDE), Long Beach, CA, pages 175-178, 2010.