# Structuring Superconductor Data with Ontology: Reproducing Historical Datasets as Knowledge

https://mdr.nims.go.jp/datasets/1c244352-c36a-4683-ab82-04e4fa7339bb

## File

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- [Schema.pdf](https://mdr.nims.go.jp/filesets/445e37a1-20c9-45ec-b88d-803c82b00dfc/download) ([Detail](https://mdr.nims.go.jp/filesets/445e37a1-20c9-45ec-b88d-803c82b00dfc.md))
- [S1.png](https://mdr.nims.go.jp/filesets/87076c71-f9c7-4e42-b923-e8973850ea9d/download) ([Detail](https://mdr.nims.go.jp/filesets/87076c71-f9c7-4e42-b923-e8973850ea9d.md))
- [S2.png](https://mdr.nims.go.jp/filesets/19209e8a-9981-4615-b81d-f9cf80148adc/download) ([Detail](https://mdr.nims.go.jp/filesets/19209e8a-9981-4615-b81d-f9cf80148adc.md))
- [S3.png](https://mdr.nims.go.jp/filesets/a393240f-5484-4130-8f2c-7efff6b9982f/download) ([Detail](https://mdr.nims.go.jp/filesets/a393240f-5484-4130-8f2c-7efff6b9982f.md))

## Id

1c244352-c36a-4683-ab82-04e4fa7339bb

## Local identifier



## Visibility

open_to_public

## State

published

## Created at

2023-07-04T00:47:37.673356Z

## Updated at

2024-01-05T13:11:32.832373Z

## Published at

2023-07-04T04:30:17.389220Z

## Doi



## First published url

https://doi.org/10.1080/27660400.2023.2223051

## Date published

2023-12-31

## Recorded date published

2023-12-31

## Resource type

journal_article

## Manuscript type

vor

## Collection



## Title

- title: 'Structuring Superconductor Data with Ontology: Reproducing Historical Datasets
    as Knowledge'
  title_type: original
  lang: en

## Description

- description: Applying historical human-readable databases to recent data-driven
    science is a natural concept. However, this cannot be realized by simply converting
    a database into a tabular format because the meaning of each table column and
    the relationships between columns need to be rewritten in a machine-readable format.
    In particular, eliminating implicit notations that can only be understood by experts
    in the fields covered by each database and making them machine-readable under
    a unified academic system is necessary when integrating data across fields with
    a view to solving specific social issues and social implementation. In this study,
    we constructed a superconducting materials ontology for SuperCon, a legacy superconductor
    database that was recently republished as a datasheet, based on the well-known
    Basic Formal Ontology (BFO) top ontology, and designed a schema for material composition,
    structure, properties, and processes, among others. Using this schema, we constructed
    and published the Resource Description Framework (RDF) for each instance in the
    SuperCon datasheet. We also discuss the machine-readable format of data common
    to materials science discovered in this process.
  description_type: abstract
  lang: eng

## Creator

- name: Masashi Ishii
  role: author
  orcid: https://orcid.org/0000-0003-0357-2832
  organization: National Institute for Materials Science (NIMS)
  department: Center for Basic Research on Materials
- name: Koichi Sakamoto
  role: author
  organization: National Institute for Materials Science
  department: Center for Basic Research on Materials
  ror: https://ror.org/026v1ze26

## Contact agent



## Publisher

organization: Informa UK Limited

## Managing organization



## Keyword

- subject: ontology
  schema: not_defined
- subject: RDF
  schema: not_defined
- subject: SuperCon
  schema: not_defined
- subject: superconducting material
  schema: not_defined
- subject: knowledge base
  schema: not_defined

## Rights

- identifier: https://creativecommons.org/licenses/by-nc/4.0/

## Other identifier(s)



## Data origin

- data_origin_type: other

## Embargo



## Journal

- title: 'Science and Technology of Advanced Materials: Methods'
  issn: '27660400'
  volume: '3'
  issue: '1'
  start_page: 2223051
  end_page: 2223051

## Conference



## Related item



## Funding

- identifier: JPMXP1122715503
  funder_name: MEXT
  description: Digital Transformation Initiative Center for Magnetic Materials

## Instrument



## Instrument operator



## Instrument managing organization



## Measurement method



## Specimen



## Chemical composition



## Structure for specimen



## Structural feature for specimen



## Specific property for specimen



## Process for specimen treatment



## Computational method



## Energy level/transition state



## Software



## Custom property



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## Thumbnail

fileset_id: cb9a2d12-ade2-4640-9575-f07c661d2187
filename: Structuring superconductor data with ontology reproducing historical datasets
  as knowledge bases.pdf