(We apologize for multiples copies)
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