Scott McClellan

According to our database, Scott McClellan authored at least 13 papers between 2021 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Human-in-the-Loop and AI: Crowdsourcing Metadata Vocabulary for Materials Science.

Jane Greenberg, Scott McClellan, Addy Ireland, Robert Sammarco, Colton Gerber, Christopher B. Rauch, Mat Kelly, John A. Kunze, Yuan An, Eric Toberer

CoRR, December, 2025

2024

Enhancing semantic interoperability across materials science with HIVE4MAT.

Jane Greenberg, Kio Polson, Scott McClellan, Xintong Zhao, Alex Kalinowski, Yuan An

Proceedings of the First International Workshop on Semantic Materials Science: Harnessing the Power of Semantic Web Technologies in Materials Science co-located with the 20th International Conference on Semantic Systems (SEMANTiCS 2024), 2024

Towards MatCore: A Unified Metadata Standard for Materials Science.

Jane Greenberg, Pámela Bóveda-Aguirre, John Allison, Pietro Asinari, Maria Chan, Anand Chandrasekaran, Elif Ertekin, Emmanouel Garoufallou, Giulia Galli, Paolo Giannozzi, Feliciano Giustino, Gerhard Goldbeck, Hendrik Heinz, Arthi Jayaraman, Vincenzo Lordi, Kristin A. Persson, Gian-Marco Rignanese, Aidan Thompson, Eric Toberer, Scott McClellan, Ellad B. Tadmor

Proceedings of the Metadata and Semantic Research - 18th Research Conference, 2024

2023

Building Community Consensus for Scientific Metadata with YAMZ.

Jane Greenberg, Scott McClellan, Christopher B. Rauch, Xintong Zhao, Mat Kelly, Yuan An, John A. Kunze, Rachel Orenstein, Claire Porter, Vanessa Meschke, Eric Toberer

Data Intell., 2023

Characterizing Semantic Ambiguity of the Materials Science Ontologies.

Scott McClellan, Yuan An, Xintong Zhao, Xia Lin, Jane Greenberg

CoRR, 2023

Metadata for Scientific Experiment Reporting: A Case Study in Metal-Organic Frameworks.

Xintong Zhao, Kyle Langlois, Jacob Furst, Scott McClellan, Xiaohua Hu, Yuan An, Diego A. Gómez-Gualdrón, Fernando J. Uribe-Romo, Jane Greenberg

Proceedings of the Metadata and Semantic Research - 17th Research Conference, 2023

When LLM Meets Material Science: An Investigation on MOF Synthesis Labeling.

Xintong Zhao, Kyle Langlois, Jacob Furst, Scott McClellan, Rob Fleur, Yuan An, Xiaohua Hu, Fernando J. Uribe-Romo, Diego A. Gómez-Gualdrón, Jane Greenberg

Proceedings of the IEEE International Conference on Big Data, 2023

Investigating Data Reusability in Density Functional Theory Studies.

Rob Fleur, Addy Ireland, Xintong Zhao, Scott McClellan, Eric Paltoo, Tianyu Su, Channyung Lee, Yuan An, Xiaohua Hu, Elif Ertekin, Jane Greenberg

Proceedings of the IEEE International Conference on Big Data, 2023

2022

Building Open Knowledge Graph for Metal-Organic Frameworks (MOF-KG): Challenges and Case Studies.

Yuan An, Jane Greenberg, Xintong Zhao, Xiaohua Hu, Scott McClellan, Alexander Kalinowski, Fernando J. Uribe-Romo, Kyle Langlois, Jacob Furst, Diego A. Gómez-Gualdrón, Fernando Fajardo-Rojas, Katherine Ardila

CoRR, 2022

Materials Science Ontology Design with an Analytico-Synthetic Facet Analysis Framework.

Jane Greenberg, Scott McClellan, Xintong Zhao, Elijah J. Kellner, David Venator, Haoran Zhao, Jiacheng Shen, Xiaohua Hu, Yuan An

Proceedings of the Metadata and Semantic Research - 16th Research Conference, 2022

Exploring Pre-Trained Language Models to Build Knowledge Graph for Metal-Organic Frameworks (MOFs).

Yuan An, Jane Greenberg, Xiaohua Hu, Alexander Kalinowski, Xiao Fang, Xintong Zhao, Scott McClellan, Fernando J. Uribe-Romo, Kyle Langlois, Jacob Furst, Diego A. Gómez-Gualdrón, Fernando Fajardo-Rojas, Katherine Ardila, Semion Saikin, Corey A. Harper, Ron Daniel Jr.

Proceedings of the IEEE International Conference on Big Data, 2022

2021

Modeling Ephraim Chambers' Knowledge Structure from a Naive Standpoint.

Scott McClellan, Mat Kelly, Jane Greenberg

CoRR, 2021

Knowledge Graph-Empowered Materials Discovery.

Xintong Zhao, Jane Greenberg, Scott McClellan, Yong-Jie Hu, Steven Lopez, Semion Saikin, Xiaohua Hu, Yuan An

Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021