Using nanopublications to detect and explain contradictory research claims

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.