FERASAT: A Serendipity-Fostering Faceted Browser for Linked Data

  • Ali KhaliliEmail author
  • Peter van den Besselaar
  • Klaas Andries de Graaf
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10843)


Accidental knowledge discoveries occur most frequently during capricious and unplanned search and browsing of data. This type of undirected, random, and exploratory search and browsing of data results in Serendipity – the art of unsought finding. In our previous work we extracted a set of serendipity-fostering design features for developing intelligent user interfaces on Semantic Web and Linked Data browsing environments. The features facilitate the discovery of interesting and valuable facts in (linked) data which were not initially sought for. In this work, we present an implementation of those features called FERASAT. FERASAT provides an adaptive multigraph-based faceted browsing interface to catalyze serendipity while browsing Linked Data. FERASAT is already in use within the domain of science, technology & innovation (STI) studies to allow researchers who are not familiar with Linked Data technologies to explore heterogeneous interlinked datasets in order to observe and interpret surprising facts from the data relevant to policy and innovation studies. In addition to an analysis of the related work, we describe two STI use cases in the paper and demonstrate how different serendipity design features are addressed in those use cases.


Faceted Browsing Ferase Semantic Web Unsought Finding Serendipity 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



We would like to thank our colleagues from the Knowledge Representation and Reasoning research group at Vrije Universiteit Amsterdam for their helpful comments during the development of our Linked Data-based faceted browser. This work was supported by a grant from the European Union’s 7th Framework Programme provided for the project RISIS (GA no. 313082).


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© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Computer Science, Faculty of ScienceVrije Universiteit AmsterdamAmsterdamThe Netherlands
  2. 2.Department of Organization Science, Faculty of Social SciencesVrije Universiteit AmsterdamAmsterdamThe Netherlands

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