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ISHII, Masashi
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MDR XAFS DB Readme
Description/Abstract:
This MDR XAFS DB is an integrated database of XAFS spectral data provided by the participating institutions in this project. The metadata...
Keyword:
collection - MDR XAFS DB
and
XAFS
Resource Type:
Other
Data origin:
other
Author:
ISHII, Masashi
and
SHIMIZU, Miharu
Date Uploaded:
14/06/2022
Date Modified:
19/06/2023
NIMS Materials Data Repositoryにおける研究データへのDOI登録運用
Description/Abstract:
NIMSでは材料データリポジトリ (MDR) を2020年より運用し、研究データセットの登録・公開を推進している。各データセットが有効に利活用・引用されるように検討しながら登録方法やメタデータを定め、DataCite DOIを付与している。ある研究コミュニティによる1700...
Keyword:
data repository
,
FAIR
,
DOI
,
data platform
, and
open science
Resource Type:
Presentation
Author:
MATSUDA, Asahiko
,
TANABE, Kosuke
,
ISHII, Masashi
,
ONODERA, Chie
,
HIROSAWA, Chieko
,
KUWAJIMA, Isao
,
KADOHIRA, Takuya
, and
TANIFUJI, Mikiko
Date Uploaded:
08/06/2022
Date Modified:
08/06/2022
Automatic Identification and Normalisation of Physical Measurements in Scientific Literature
Description/Abstract:
We present Grobid-quantities, an open-source application for extracting and normalising measurements from scientific and patent literatur...
Keyword:
machine learning
,
physical quantities
, and
tdm
Resource Type:
Conference Proceeding
Author:
FOPPIANO, Luca
,
ROMARY, Laurent
,
ISHII, Masashi
, and
TANIFUJI, Mikiko
Journal:
DocEng '19: Proceedings of the ACM Symposium on Document Engineering 2019
Date Uploaded:
15/01/2021
Date Modified:
01/07/2021
SuperMat: Construction of a linked annotated dataset from superconductors-related publications
Description/Abstract:
A growing number of papers are published in the area of superconducting materials science. However, novel text and data mining (TDM) pro...
Keyword:
annotation
,
annotation guidelines
,
dataset
,
superconductors
, and
tdm
Resource Type:
Article
Author:
FOPPIANO, Luca
,
DIEB, Sae
,
SUZUKI, Akira
,
BAPTISTA DE CASTRO, Pedro
,
IWASAKI, Suguru
,
UZUKI, Azusa
,
ESPARZA ECHEVARRIA, Miren Garbine
,
MENG, Yan
,
TERASHIMA, Kensei
,
TAKANO, Yoshihiko
, and
ISHII, Masashi
Date Uploaded:
07/01/2021
Date Modified:
01/07/2021
Machine extraction of polymer data from tables using XML versions of scientific articles
Description/Abstract:
In this study, we examined machine extraction of polymer data from tables in scientific articles. The extraction system consists of five ...
Keyword:
XML
,
informatics
,
machine extraction
,
polymer data
, and
table
Resource Type:
Dataset
Data origin:
informatics and data science
Author:
OKA, Hiroyuki
,
YOSHIZAWA, Atsushi
,
SHINDO, Hiroyuki
,
MATSUMOTO, Yuji
, and
ISHII, Masashi
Date Modified:
25/02/2021
Proposal for Automatic Extraction Framework of Superconductors Related Information from Scientific Literature
Description/Abstract:
The automatic collection of materials information from research papers using Natural Language Processing (NLP) is highly required for rap...
Keyword:
Machine Learning
,
Material Informatics
,
NLP
,
Superconductors
, and
TDM
Resource Type:
Conference Proceeding
Author:
FOPPIANO, Luca
,
Thaer, M. Dieb
,
SUZUKI, Akira
, and
ISHII, Masashi
Date Uploaded:
05/02/2020
Date Modified:
02/02/2022
Leveraging Segmentation of Physical Units through a Newly Open Source Corpus
Description/Abstract:
The identification of physical measurements is a recurrent need in materials informatics (MI). For example, the extraction of superconduc...
Resource Type:
Dataset
Data origin:
informatics and data science
Author:
FOPPIANO, Luca
,
TANIFUJI, Mikiko
,
ISHII, Masashi
,
DIEB M. Thear
, and
SUZUKI, Akira
Date Uploaded:
25/10/2019
Date Modified:
15/06/2020
Automatic Identification and Normalisation of Physical Measurements in Scientific Literature
Resource Type:
Presentation
Author:
TANIFUJI, Mikiko
,
ISHII, Masashi
,
ROMARY, Laurent
, and
FOPPIANO, Luca
Date Uploaded:
18/10/2019
Date Modified:
15/06/2020
Leveraging Segmentation of Physical Units through a Newly Open Source Corpus
Description/Abstract:
The identification of physical measurements is a recurrent task in material informatics (MI). Quantities and units are contained in unstr...
Keyword:
measurements
,
physical quantities
,
quantities
, and
segmentation
Resource Type:
Presentation
Author:
SUZUKI, Akira
,
TANIFUJI, Mikiko
,
DIEB M. Thear
,
ISHII, Masashi
, and
FOPPIANO, Luca
Date Uploaded:
18/10/2019
Date Modified:
15/06/2020
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MDR XAFS DB
1
The history of DICE and NIMS Digital Library
1
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physical quantities
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National Institute for Materials Science
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Rights Statement Sim
Creative Commons BY Attribution 4.0 International
4
Creative Commons BY-NC-SA Attribution-NonCommercial-ShareAlike 4.0 International
2
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Data origin
informatics and data science
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Author
ISHII, Masashi
[remove]
9
FOPPIANO, Luca
6
TANIFUJI, Mikiko
5
SUZUKI, Akira
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DIEB M. Thear
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Journal
DocEng '19: Proceedings of the ACM Symposium on Document Engineering 2019
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