The materials data ecosystem: materials data science and its role in data-driven materials discovery

TL;DR

This paper discusses the role of materials data science within the materials data ecosystem, emphasizing its importance in data-driven discovery and proposing a three-tier system for data management and knowledge extraction.

Contribution

It introduces a three-tier system for classifying, curating, and extracting knowledge from materials data, advancing the infrastructure for data-driven materials discovery.

Findings

Materials data science is crucial for data-driven discovery.

A three-tier system enhances data classification, curation, and knowledge extraction.

Materials data has become a significant approach since 2011.

Abstract

Since its launch in 2011, Materials Genome Initiative (MGI) has drawn the attention of researchers from across academia, government, and industry worldwide.As one of the three tools of MGI, the materials data, for the first time, emerged as an extremely significant approach in materials discovery. Data science has been applied in different disciplines as an interdisciplinary field to extract knowledge from the data. The concept of materials data science was utilized to demonstrate the data application in materials science. To explore its potential as an active research branch in the big data age, a three-tier system was put forward to define the infrastructure of data classification, curation and knowledge extraction of materials data.