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Filtering by: Keyword Superconductors Remove constraint Keyword: Superconductors Visibility open Remove constraint Visibility: open

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SuperCon RDF Ver. 1.0

Description/Abstract:

"SuperCon RDF" is an RDF version of the datasheets published in this collection based on the SuperCon Ontology (https://doi.org/10.48505/...

Keyword:

Ontology, RDF, SPARQL, Semantic Web, SuperCon, and Superconductors

Resource Type:

Dataset

Data origin:

informatics and data science

Author:

Masashi Ishii

Date Uploaded:

11/04/2023

Date Modified:

19/07/2023
SuperCon Ontology

Description/Abstract:

"SuperCon Ontology" is the basic conceptual structure of SuperCon RDF (https://doi.org/10.48505/nims.3872), which is published in this co...

Keyword:

Ontology, RDF, SPARQL, Semantic Web, SuperCon, and Superconductors

Resource Type:

Dataset

Data origin:

informatics and data science

Author:

Masashi Ishii

Date Uploaded:

11/04/2023
MDR SuperCon Datasheet Ver.220808

Description/Abstract:

MDR SuperCon Datasheet is a re-edited datasheet of SuperCon, a superconductivity database that was originally published as the MatNavi da...

Keyword:

Metallic, Organic, Oxide, SuperCon, Superconductors, and Tc

Resource Type:

Dataset

Data origin:

experiments

Date Uploaded:

15/12/2022

Date Modified:

16/12/2022
MDR SuperCon Datasheet Readme

Description/Abstract:

The readme (SuperCon_ReadMe_en.pdf) describes the contents of the SuperCon datasheet in detail. It references the functionality of the Su...

Keyword:

Metallic, Organic, Oxide, Readme, SuperCon, and Superconductors

Resource Type:

Other

Date Uploaded:

14/12/2022

Date Modified:

16/12/2022
MDR SuperCon Datasheet
User Collection

Description/Abstract:

The MDR SuperCon Datasheet is a datasheet re-edited from SuperCon, which was originally published as the MatNavi database. To use it, ple...

Keyword:

Metallic, SuperCon, Superconductors, Oxide, Organic, and Tc

Resource Type:

Dataset

License:

Creative Commons BY Attribution 4.0 International

Date Created:

2022

0Collections

2Works
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

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Type of work

Dataset3
Publication2
Collection1

Collection

MDR SuperCon Datasheet2

Keyword

Superconductors[remove]6
SuperCon5
Metallic3
Organic3
Oxide3
more Keywords »

Language

English1

Publisher

National Institute for Materials Science3

Resource type

Dataset4
Conference Proceeding1
Other1

Visibility

open[remove]6

Rights Statement Sim

CC-BY-4.02
Creative Commons BY Attribution 4.0 International2
In Copyright1

Data origin

informatics and data science2
experiments1

Date

20191

Author

Masashi Ishii2
FOPPIANO, Luca1
ISHII, Masashi1
SUZUKI, Akira1
Thaer, M. Dieb1

Editor

Materials Database Group2

National Institute for Materials Science

Research Network and Facility Services Division (RNFS)
Materials Data Platform

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