# PoLyInfoと機械学習

https://mdr.nims.go.jp/datasets/780eb64f-0a46-4dc1-8b1b-2281a423e555

## File

- [Front-Line-5P-ISHII-著者版.pdf](https://mdr.nims.go.jp/filesets/8f70754b-93ab-4a8b-b282-29385aba6284/download) ([Detail](https://mdr.nims.go.jp/filesets/8f70754b-93ab-4a8b-b282-29385aba6284.md))

## Id

780eb64f-0a46-4dc1-8b1b-2281a423e555

## Local identifier



## Visibility

open_to_public

## State

published

## Created at

2023-02-03T01:27:50.373874Z

## Updated at

2023-11-17T04:35:07.553917Z

## Published at

2023-08-01T04:58:32.526929Z

## Doi

https://doi.org/10.48505/nims.4213

## First published url

https://main.spsj.or.jp/c5/kobunshi/kobu2023/2302.html#68

## Date published

2023-02-01

## Recorded date published



## Resource type

journal_article

## Manuscript type

accepted_manuscript

## Collection



## Title

- title: PoLyInfoと機械学習
  title_type: original
  lang: ja
- title: PoLyInfo and Machine Learning
  title_type: alternative
  lang: en

## Description

- description: 近年、高分子分野においても、マテリアルズ・インフォマティクスへの関心が高まっている。一方で、高分子の多様性を反映して、系統的なデータの少なさや、データの統合が困難なことが問題になっている。ここでは、世界的な高分子データベースを俯瞰した上でのPoLyInfoの位置づけ、インフォマティクスの観点で見た特徴、関連の成果等をまとめる。
  description_type: abstract
  lang: jpn
- description: In recent years, there has been growing interest in materials informatics
    and machine learning in the field of polymers. On the other hand, reflecting the
    variety of polymers, the lack of systematic data and the difficulty of integrating
    data in a single format to cover such data have become a problem. The National
    Institute for Materials Science has collected polymer data from papers over a
    long period of time and published them in a database called "PoLyInfo". Here,
    we summarize the position of PoLyInfo in the global polymer database, the characteristics
    of PoLyInfo from the viewpoint of informatics, and related results. In particular,
    it will provide an overview of what is needed to extract the process-structure-property
    combination that is necessary for machine-readable representation of materials,
    with a view toward the future target of polymer informatics.
  description_type: abstract
  lang: en

## Creator

- name: 石井 真史
  role: author
  orcid: https://orcid.org/0000-0003-0357-2832
  organization: 物質・材料研究機構
  department: 統合型材料開発・情報基盤部門/材料データプラットフォームセンター/材料データベースグループ
  ror: https://ror.org/026v1ze26

## Contact agent



## Publisher

organization: 高分子

## Managing organization



## Keyword

- subject: MI
  schema: not_defined
- subject: PoLyInfo
  schema: not_defined
- subject: 機械学習
  schema: not_defined
- subject: 高分子
  schema: not_defined
- subject: データベース
  schema: not_defined
- subject: マテリアルズインフォマティクス
  schema: not_defined
- subject: Process-Structure-Property
  schema: not_defined

## Rights

- identifier: http://rightsstatements.org/vocab/InC/1.0/

## Other identifier(s)



## Data origin

- data_origin_type: other

## Embargo

start_date: 2023-02-01
end_date: 2023-08-01

## Journal

- title: 高分子
  issn: '21859825'
  volume: '72'
  issue: '2'
  start_page: 68
  end_page: 72

## Conference



## Related item



## Funding

- identifier: JPMXP1122714694
  funder_name: 文部科学省
  description: "データ創出・活用型マテリアル研究開発プロジェクト事業\r\nData Creation and Utilization-Type Material
    Research and Development Project"

## 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



## Fileset

- id: 8f70754b-93ab-4a8b-b282-29385aba6284
  filename: Front-Line-5P-ISHII-著者版.pdf
  content_type: application/pdf
  size: 568559
  md5: a06fd633edebf8c334f7ec3f7e09c213

## Thumbnail

fileset_id: 8f70754b-93ab-4a8b-b282-29385aba6284
filename: Front-Line-5P-ISHII-著者版.pdf