LODatio+ is a search engine to locate data sources on the Linked Open Data cloud that contain resources of specific types and using specific properties. For a certain information need, LODatio+ will not only return the matching data sources but also provide query recommendations to generalize or to further narrow down the information need.

LODatio+ is running as part of the MOVING EU project. It is maintained by the Knowledge Discovery group at Kiel University and ZBW – Leibniz information center for economics in Kiel. It has been initially designed by Thomas Gottron and Ansgar Scherp at the Institute for Web Science and Technologies (WeST) at the University of Koblenz-Landau. LODatio+ currently provides an index of the Billion Triple Track of the Semantic Web Challenge 2014.

How to use

You can use LODatio+ by formulating your information need as a SPARQL query using only types and properties. The example queries provided can help you get familiar with these queries. For each query, LODatio+ will provide you with a ranked list of data sources on the Linked Open Data cloud that contain data matching the types and properties specified in the query. Please note, the current prototype is limited to retrieve only the top 10,000 data sources.


Query size estimation
LODatio+ gives you an estimated number of how many data sources provide you with how many resources satisfying your information need.
The results are ranked by the number of matching resources they contain. Thus, those data sources which provide more resources matching your information need are ranked higher.
Result snippets
The result snippets displayed with each data source give a preview of what kind of instance data you can expect at this source. LODatio+ lists up to three example instances.
Did you mean?
If your query provides too little or even no result, LODatio+ suggest generalizations of your query which will give you more result.
Related queries
If your query provides you with too many data sources, you might want to narrow down the result set and further specialize your query. LODatio+ makes suggestions for such queries that will restrict the result set size without leading to an empty result set.

How it works

LODatio+ makes use of a schema-level index computed over the distributed RDF data on the Linked Open Data cloud. The index stores the schematic information together with references to the original location of the RDF data. Further meta data is attached to the schema-level index to display examples, estimating the size of the result set, and advanced functions such as ranking, query generalization (Did you mean?) and query specification (Related queries). For more detailed information you may refer to the publications.


Till Blume, Falk Böschen, Lukas Galke, Ahmed Saleh, Ansgar Scherp, Matthias Schulte-Althoff, Chrysa Collyda, Vasileios Mezaris, Alexandros Pournaras, Christos Tzelepis, Peter Hasitschka, Vedran Sabol, Aitor Apaolaza, Markel Vigo, Tobias Backes, Peter Mutschke, Thomas Gottron: D3.1 Technologies for MOVING data processing and visualisation v1.0, April 2017

Thomas Gottron, Malte Knauf, Ansgar Scherp, Johann Schaible: ELLIS: Interactive Exploration of Linked Data on the Level of Induced Schema Patterns. SumPre@ESWC 2016

Thomas Gottron, Malte Knauf, Ansgar Scherp: Analysis of schema structures in the Linked Open Data graph based on unique subject URIs, pay-level domains, and vocabulary usage. Distributed and Parallel Databases 33(4): 515-553 (2015)

Thomas Gottron, Ansgar Scherp, Stefan Scheglmann: Providing Alternative Declarative Descriptions for Entity Sets Using Parallel Concept Lattices. ESWC 2014: 364-379

T. Gottron, A. Scherp, B. Krayer, and A. Peters, "Get the Google Feeling: Supporting Users in Finding Relevant Sources of Linked Open Data at Web-scale", in Semantic Web Challenge, Submission to the Billion Triple Track, 2012.

M. Konrath, T. Gottron, S. Staab, and A. Scherp, "Schemex--efficient construction of a data catalogue by stream-based indexing of linked data", Journal of Web Semantics, 2012.

M. Konrath, T. Gottron, and A. Scherp, "Schemex--Web-scale Indexed Schema Extraction of Linked Open Sata", in Semantic Web Challenge, Submission to the Billion Triple Track, 2011.


Team members
Marius Leka
Henrik Schmidt
Till Blume
Dr. Iacopo Vagliano
Prof. Dr. Ansgar Scherp
Prof. Dr. Ansgar Scherp (asc@informatik.uni-kiel.de )