About this Abstract |
Meeting |
2023 TMS Annual Meeting & Exhibition
|
Symposium
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AI/Data Informatics: Computational Model Development, Validation, and Uncertainty Quantification
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Presentation Title |
A Data Facilitation Platform for Materials Science Literature Mining |
Author(s) |
Vipul Gupta, Florian Pyczak, Ingo Schmitt |
On-Site Speaker (Planned) |
Vipul Gupta |
Abstract Scope |
Recent developments in the field of data mining (DM) have received considerable attention from the materials science community due to its ability to accelerate the design of new materials. Experimental datasets of materials are published in scientific literature. Mining such literature thus enables the possibility of evaluating the combined experimental datasets synergistically.
The selection of relevant, machine-readable data is essential for DM. However, digital libraries that act as data sources typically allow only generic searches. Highly specific searches are not possible, such as retrieval of literature that has exclusively TiAl-Creep datasets. Moreover, these digital libraries usually provide data in a human-readable format. This work presents a system that facilitates a generic search-based ingestion of literature from digital libraries, followed by the selection of DM relevant literature. Besides phrase, facet, and full-text search capabilities, the selection mechanism also allows dataset-aware literature retrieval through figure caption and domain knowledge taxonomy-based semantic searches. |
Proceedings Inclusion? |
Planned: |
Keywords |
Machine Learning, Computational Materials Science & Engineering, Modeling and Simulation |