Reproducible Semantic Data Management Workflow for Materials Data Science: Generating Knowledge Graphs with Robust FAIRifcation Pipelines

Scholarly Commons @ Case Western Reserve University 2026 Open access

Read full text
Authors: Kyle R Henrikson, Van D. Tran, Meredith Francis, Isabella Giammattei, Quynh D. Tran, Laura S. Bruckman, Erika I. Barcelos, Roger H. French
Cited by: 0

Abstract

Combining data from multiple sources is crucial for efficient knowledge aggregation in materials data science. FAIR data from ontology and Linked Data principles enable this. Semantic data management streamlines data exchange and aggregation, ensuring information is available and extractable. FAIRLinked and GraphDB provide solutions for consolidating, hosting, and extracting meaningful insight from multimodal data.

Fields of Study & Subjects

Research Data Management Practices Semantic Web and Ontologies Scientific Computing and Data Management

Publication details

Journal / source
Scholarly Commons @ Case Western Reserve University
Publication date
14 January 2026
Language
EN