Welcome to the MatSci YAMZ
The collaborative dictionary for materials science metadata. Designed for researchers and professionals, YAMZ provides a shared space to define, discuss, and refine key terms used across the materials science community. By contributing definitions, commenting, and voting, you help build a living, community-driven vocabulary that promotes clarity, interoperability, and shared understanding in materials research.
Get Started
Ready to explore the language of materials science? Use the search bar to discover terms, browse definitions, and see how the community describes key concepts in materials metadata. You can also contribute by refining existing entries or adding new terms to expand the shared vocabulary.
Explore the growing dictionary of materials science metadata:
Search for definitions across materials, properties, and processes.
See how experts describe and organize key scientific concepts.
Compare community contributions and discover related terms.
Learn from real-world examples and evolving terminology in the field.
Explore the growing dictionary of materials science metadata:
Search for definitions across materials, properties, and processes.
See how experts describe and organize key scientific concepts.
Compare community contributions and discover related terms.
Learn from real-world examples and evolving terminology in the field.
Engage with the community by critiquing definitions, appraising or debating terms, and contributing to consensus on materials science metadata.
Support the growth of the materials science metadata community by:
Reviewing and critiquing existing definitions for clarity and precision.
Appraising and discussing differing viewpoints to strengthen shared understanding.
Providing references or datasets that enrich term accuracy and context.
Collaborating toward consensus to advance standardization in materials science metadata.
Who We Are
MatSci YAMZ is a community-driven initiative from Drexel University's Metadata Research Center that standardizes the complex language of materials science to accelerate global discovery. By integrating expert crowdsourcing with human-in-the-loop AI, the platform provides a collaborative “Metadata Zoo” where researchers define, discuss, and vote on terminology in real time. This ensures that scientific data adheres to FAIR principles — making it Findable, Accessible, Interoperable, and Reusable for both human researchers and machine-learning applications.
Mission Statement
The mission of MatSci-YAMZ is to strengthen the semantic infrastructure across materials science by providing a collaborative, AI-supported space for defining and refining disciplinary terminology. The MatSci-YAMZ hybrid model integrates crowdsourcing and human-in-the-loop AI, and enables researchers to collaboratively build and vote on persistent controlled vocabulary terms. MatSci-YAMZ supports semantic transparency and advances metadata standards development, interdisciplinary communication, and AI-ready research.
Our Team
Jane Greenberg is the Alice B. Kroeger Professor and Director of the Metadata Research Center at the College of Computing & Informatics, Drexel University. Her research activities focus on metadata, knowledge organization/semantics, linked data, data science, and information economics. She serves on the advisory board of the Dublin Core Metadata Initiative (DCMI) and the steering committee for the NSF Northeast Big Data Innovation Hub (NEBDIH).
Robert Sammarco and Jane Greenberg presented “Human-in-the-Loop and AI: Crowdsourcing Metadata Vocabulary for Materials Science” at the Metadata and Semantics Research Conference held in Thessaloniki, Greece, December 15–19. They presented findings on a recent proof of concept study which investigated the functionality of the MatSci-YAMZ application.
