Using Nanopublications to Detect and Explain Contradictory Research Claims

Imran Asif, Ilaria Tiddi, Alasdair J. G. Gray

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)
127 Downloads (Pure)


We tackle the problem of automatically detecting conflicting claims in research outputs. This has become even more urgent in recent years, with the increasing volume of scientific publications available. Researchers are struggling to keep pace with the literature, and to efficiently make comparisons between the results of different published studies. We hypothesise that the difficult and time-consuming process of searching and comparing results across research publications can be facilitated using machine-readable, standardised knowledge representation methods. To this end, we propose to exploit Nanopublications as the standard framework to represent the claims in research studies, and use provenance data expressed by the model as an indicator of the source of the contradiction between different claims. We evaluate this idea over the Cooperation Databank (CoDa); a repository of social science studies. Our results show that the use of provenance information can be a good factor to identify the cause of conflicting claims, and that our method can support scientists in comparing literature in a more automated way.
Original languageEnglish
Title of host publication17th IEEE International Conference on eScience (eScience 2021)
ISBN (Electronic)9781665403610
Publication statusPublished - 26 Oct 2021
Event17th IEEE International Conference on eScience 2021 - Worldwide Online Conference
Duration: 20 Sept 202123 Sept 2021


Conference17th IEEE International Conference on eScience 2021
Abbreviated titleeScience 2021
Internet address


  • Automatic claim Detection
  • Knowledge Modelling
  • Nanopublications
  • Social Science

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Artificial Intelligence
  • Computer Networks and Communications
  • Hardware and Architecture
  • Information Systems and Management
  • Safety, Risk, Reliability and Quality


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