Databugger

(announced by Dimitris Kontokostas)

We are pleased to announce the release of the beta version of Databugger, a test-driven data debugging framework for the Web of Data.

Databugger is inspired by test-driven development and can run automatically generated (based on a schema) and manually generated test cases against an endpoint. All test cases are executed as SPARQL queries using a pattern-based transformation approach.

We provide a reusable set of 32,293 SPARQL automatically generated test-cases [1] for 297 (out of 361) LOV vocabularies [2].

For more information on our methodology please refer to our report [3] or directly test your dataset [4] (note that Databugger relies on SPARQL 1.1 property paths, thus a triple-store like Virtuoso 7 will be able to run all test cases).

A simple call for automated-only testing is: $ bin/databugger -d http://example.com -e http://example.com/sparql -g http://example.com/graph -s foaf,dc,dcterms,skos

You can use any vocabulary defined in LOV and the framework will automatically dereference, download and use it. For more advanced usages consult to the project's Github page [4].

The next version of Databugger will provide a GUI for browsing existing test cases and generating manual test cases. We also plan to make it interoperable with recent work from DBpedia GSoC [5].

Please note that this is a work in progress and any feedback is highly appreciated. We gratefully acknowledge the support of the DBpedia [6] community and AKSW research group [7].

On behalf of the Databugger team, Dimitris Kontokostas

[1] https://github.com/AKSW/Databugger/tree/master/data/archive/WWW_2014 [2] http://lov.okfn.org [3] http://svn.aksw.org/papers/2014/WWW_Databugger/public.pdf [4] https://github.com/AKSW/Databugger [5] http://dbpedia.med.auth.gr/metamin/public/tests/item/dbt:20130617/all (demo) [6] http://dbpedia.org [7] http://aksw.org