An Evaluation Dataset for Linked Data Profiling

  • Andrejs Abele
  • John P. McCrae
  • Paul Buitelaar
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10318)


Since the beginning of the Linked Open Data initiative, the number of published Linked Data datasets has gradually increased. However, the reuse of datasets is hindered by a lack of descriptive and reliable metadata about the nature of the data, such as their topic coverage. Manual curation of metadata is however costly and hard to maintain, because of which we advocate a Linked Data profiling approach that will be able to automatically extract topics from datasets as metadata. One of the main challenges in developing this is the lack of evaluation data, i.e. manually curated metadata (topics) for datasets. In this paper we describe such an evaluation dataset and the framework that enabled its creation.


Linked Data Linked Data profiling Topic extraction Metadata Evaluation dataset 



This work was supported by Science Foundation Ireland under grant number SFI/12/RC/2289 (Insight) and by the European Union under grant number H2020-644632 (MixedEmotions).


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Insight Centre for Data AnalyticsNational University of Ireland, GalwayGalwayIreland

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