SuperMat: Construction of a linked annotated dataset from superconductors-related publications

Authors:
  • MEMiren Garbine Esparza Echevarria
    Miren Garbine Esparza Echevarria
  • LFLuca Foppiano
    Luca Foppiano
  • SDSae Dieb
    Sae Dieb
  • ASAkira Suzuki
    Akira Suzuki
  • PCPedro Baptista de Castro
    Pedro Baptista de Castro
  • SISuguru Iwasaki
    Suguru Iwasaki
  • AUAzusa Uzuki
    Azusa Uzuki
  • MGMiren Garbine
    Miren Garbine
  • EEEsparza Echevarria
    Esparza Echevarria
  • YMYan Meng
    Yan Meng
  • KTKensei Terashima
    Kensei Terashima
  • LRLaurent Romary
    Laurent Romary
Preprint
Publisher website
Google Scholar
Abstract
A growing number of papers are published in the area of superconducting materials science. However, novel text and data mining (TDM) processes are still needed to efficiently access and exploit this accumulated knowledge, paving the way towards data-driven materials design. Herein, we present SuperMat (Superconductor Materials), an annotated corpus of linked data derived from scientific publications on superconductors, which comprises 142 articles, 16052 entities, and 1398 links that are characterised into six categories: the names, classes, and properties of materials; links to their respective superconducting critical temperature (Tc); and parametric conditions such as applied pressure or measurement methods. The construction of SuperMat resulted from a fruitful collaboration between computer scientists and material scientists, and its high quality is ensured through validation by domain experts. The quality of the annotation guidelines was ensured by satisfactory Inter Annotator Agreement (IAA) between the annotators and the domain experts. SuperMat includes the dataset, annotation guidelines, and annotation support tools that use automatic suggestions to help minimise human errors.