Event Description
Hosted by the Metadata Research Center, College of Computing & Informatics, Drexel University, as part of the National Science Foundation (NSF) HDR Institute for Data Driven Dynamical Design (ID4).
AI-ready data refers to the high-quality and well-prepared data that
is optimized for use in artificial intelligence (AI) applications.
AI-ready data increasingly encompasses the inclusion of metadata and
ontologies to enhance the value and usability of data. Metadata provides
essential context and information about the data, and ontologies offer
structured semantic representation of a particular domain. These
additional layers of information help data scientists,data scientists,
researchers, and AI systems understand, interpret, and apply appropriate
algorithms and models for analysis. Metadata and ontologies enable
consistent data integration, interoperability, and knowledge sharing
across systems, while facilitating more knowledgeable AI applications.
Additionally, these systems are proving vital for supporting the FAIR
(Findable, Accessible, Interoperable, and Reusable) principles and
reproducible computational research (RCR).
Despite these capacities, approaches for developing, implementing,
and sustaining metadata and ontologies within AI-ready data pipelines
remain inconsistent, cumbersome, and lack sufficient support. Challenges
underlie the full data lifecycle from data creation, collection, and
research, to longer-term aims of data preservation, archiving, reuse and
support for research reproducibility. Collective, community driven
efforts are needed to address current obstacles and maximize the value
and reliability of data. The AI-Ready Data: Navigating the Dynamic Frontier of Metadata and Ontologies
workshop is a step toward addressing this challenge. This workshop will
bring together a community of individuals with expertise across the
data lifecycle to discuss issues, share solutions, and chart a path
forward for addressing key challenges in preparing AI-ready data for
scientific research.
Specific workshop goals are to:
- Collectively define the state of AI-ready data challenges in the metadata and ontology space
- Share current successes and solutions leveraging metadata standards and ontologies.
- Contribute to a road map to accelerate the preparation of data for artificial intelligence (AI) applications.
Current topics:
- What is AI ready data
- Research Bottlenecks: Data Life Cycle Challenges and Solutions with Scientific Data
- Metadata and Ontologies: Human in the Loop in the Era of LLMs
- Annotation: Large-scale Data and Balancing Human and Machine Driven Approaches
- Standards Development, Adoption, and Implementation: Realities and Fictions
- Knowledge Graphs
- Ontology Guided Knowledge Extraction: Leveraging Scholarly Big Data for Scientific Discovery
- Future Directions with Metadata and Knowledge Organization Systems
The workshop's Poster Session will be held on Monday, April 15 (4 p.m. to 5:30 p.m. in the 10th floor lobby, 3675 Market St) and is open to the Drexel community.
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