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

https://mdr.nims.go.jp/datasets/8aa85f51-da22-4b24-97f9-2799a35b3936

## File

- [main.pdf](https://mdr.nims.go.jp/filesets/35ff6ef5-6c4c-42fd-bf5c-618189b691ad/download) ([Detail](https://mdr.nims.go.jp/filesets/35ff6ef5-6c4c-42fd-bf5c-618189b691ad.md))

## Id

8aa85f51-da22-4b24-97f9-2799a35b3936

## Local identifier



## Visibility

open_to_public

## State

published

## Created at

2021-08-05T16:24:13.233019Z

## Updated at

2022-10-02T16:49:22.044307Z

## Published at

2021-08-12T16:20:02.148439Z

## Doi

https://doi.org/10.48505/nims.3038

## First published url

https://hal.inria.fr/hal-03101177

## Date published

2021-01-07

## Recorded date published

07/01/2021

## Resource type

journal_article

## Manuscript type

authors_original

## Collection



## Title

- title: 'SuperMat: Construction of a linked annotated dataset from superconductors-related
    publications '
  title_type: original
  lang: en

## Description

- description: " 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. "
  description_type: abstract
  lang: en

## Creator

- name: FOPPIANO, Luca
  role: author
  orcid: https://orcid.org/0000-0002-6114-6164
- name: DIEB, Sae
  role: author
- name: SUZUKI, Akira
  role: author
- name: BAPTISTA DE CASTRO, Pedro
  role: author
- name: IWASAKI, Suguru
  role: author
- name: UZUKI, Azusa
  role: author
- name: ESPARZA ECHEVARRIA, Miren Garbine
  role: author
- name: MENG, Yan
  role: author
- name: TERASHIMA, Kensei
  role: author
- name: TAKANO, Yoshihiko
  role: author
- name: ISHII, Masashi
  role: author

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## Keyword

- subject: superconductors
  schema: not_defined
- subject: tdm
  schema: not_defined
- subject: dataset
  schema: not_defined
- subject: annotation
  schema: not_defined
- subject: annotation guidelines
  schema: not_defined

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## Fileset

- id: 35ff6ef5-6c4c-42fd-bf5c-618189b691ad
  filename: main.pdf
  content_type: application/pdf
  size: 906012
  md5: 6533d0153f355311154617915e63446f

## Thumbnail

fileset_id: 35ff6ef5-6c4c-42fd-bf5c-618189b691ad
filename: main.pdf