RDFUnit: an RDF Unit-Testing suite

RDFUnit is a test driven data-debugging framework that 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.

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For more information on our methodology please refer to our report:

Test-driven evaluation of linked data quality. Dimitris Kontokostas, Patrick Westphal, Sören Auer, Sebastian Hellmann, Jens Lehmann, Roland Cornelissen, and Amrapali J. Zaveri in Proceedings of the 23rd International Conference on World Wide Web.

RDFUnit in a Nutshell

  • Test case: a data constraint that involves one or more triples. We use SPARQL as a test definition language.
  • Test suite: a set of test cases for testing a dataset
  • Status: Success, Fail, Timeout (complexity) or Error (e.g. network). A Fail can be an actual error, a warning or a notice
  • Data Quality Test Pattern (DQTP): Abstract test cases that can be intantiated into concrete test cases using pattern bindings
  • Pattern Bindings: valid replacements for a DQTP variable
  • Test Auto Generators (TAGs): Converts RDFS/OWL axioms into concrete test cases

As shown in the figure, there are two major sources for creating test cases. One source is stakeholder feedback from everyone involved in the usage of a dataset and the other source is the already existing RDFS/OWL schema of a dataset. Based on this, there are several ways in which test cases can be created:

  • Using RDFS/OWL constraints directly: Test cases can be automatically created via TAGs in this case.
  • Enriching the RDFS/OWL constraints: Since many datasets provide only limited schema information, we perform automatic schema enrichment. These schema enrichment methods can take an RDF/OWL dataset or a SPARQL endpoint as input and automatically suggest schema axioms with a certain confidence value by analysing the dataset. In our methodology, this is used to create further test cases via TAGs. It should be noted that test cases are explicitly labelled, such that the engineer knows that they are less reliable than manual test cases.
  • Re-using tests based on common vocabularies: Naturally, a major goal in the Semantic Web is to re-use existing vocabularies instead of creating them from scratch for each dataset. We detect the used vocabularies in a dataset, which allows to re-use test cases from a test case pattern library.
  • Instantiate existing DQTPs: The aim of DQTPs is to be generic, such that they can be applied to different datasets. While this requires a high initial effort of compiling a pattern library, it is beneficial in the long run, since they can be re-used. Instead of writing SPARQL templates themselves, an engineer can select and instantiate the correct DQTP. This does not necessarily require SPARQL knowledge, but can also be achieved via a textual description of a DQTP, examples and its intended usage.
  • Write own DQTPs: In some cases, test cases cannot be generated by any of the automatic and semi-automatic methods above and have to be written from scratch by an engineer. These DQTPs can then become part of a central library to facilitate later re-use.

Publications

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News

AKSW Colloquium, 15th August, 3pm, RDF query relaxation ( 2016-08-10T11:03:58+02:00 Michael Roeder)

2016-08-10T11:03:58+02:00 Michael Roeder

On the 15th of August at 3 PM, Michael Röder will present the paper “RDF Query Relaxation Strategies Based on Failure Causes” of Fokou et al. in P702. Read more about "AKSW Colloquium, 15th August, 3pm, RDF query relaxation"

Article accepted in Journal of Web Semantics ( 2016-08-02T09:54:24+02:00 by Lorenz Bühmann)

2016-08-02T09:54:24+02:00 by Lorenz Bühmann

We are happy to announce that the article “DL-Learner – A Framework for Inductive Learning on the Semantic Web” by Lorenz Bühmann, Jens Lehmann and Patrick Westphal was accepted for publication in the Journal of Web Semantics: Science, Services and Agents on … Continue reading → Read more about "Article accepted in Journal of Web Semantics"

AKSW Colloquium, 18.07.2016, AEGLE and node2vec ( 2016-07-18T14:56:44+02:00 TommasoSoru)

2016-07-18T14:56:44+02:00 TommasoSoru

On Monday 18.07.2016, Kleanthi Georgala will give her Colloquium presentation for her paper “An Efficient Approach for the Generation of Allen Relations”, that was accepted at the European Conference on Artificial Intelligence (ECAI) 2016. Read more about "AKSW Colloquium, 18.07.2016, AEGLE and node2vec"

AKSW Colloquium, 04.07.2016. Big Data, Code Quality. ( 2016-06-29T12:34:35+02:00 by Ivan Ermilov)

2016-06-29T12:34:35+02:00 by Ivan Ermilov

On the upcoming Monday (04.07.2016), AKSW group will discuss topics related to Semantic Web and Big Data as well as programming languages and code quality. Read more about "AKSW Colloquium, 04.07.2016. Big Data, Code Quality."

Accepted Papers of AKSW Members @ Semantics 2016 ( 2016-06-27T12:50:01+02:00 by Sandra Bartsch)

2016-06-27T12:50:01+02:00 by Sandra Bartsch

This year’s SEMANTiCS conference which is taking place between September 12 – 15, 2016 in Leipzig recently invited for the submission of research papers on semantic technologies. Read more about "Accepted Papers of AKSW Members @ Semantics 2016"