title: ai4lam Metadata/Discovery WG Monthly Meeting
February 9, 2021#
9 AM California | 12 PM Washington DC | 5 PM UK | 6 PM Oslo & Paris
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Topic: AI-LAM Metadata Working Group
Time: This is a recurring meeting. Meet anytime
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Attending
- _Name (institution) _ 
- Tim Thompson (Yale) 
- Jeremy Nelson (Stanford) 
- David Lowe (Texas A&M) 
Regrets
**Notetaker (alpha by first name): **
#
Helpful Links
Project Documents and Data#
Agenda Topics#
- Updates and announcements (5-10 mins.) - ai4lam Community Call (Jeremy) 
- Moving forward with metadata requirements for AI models and datasets (Tim) - March meeting: presentation and discussion with Kat Thornton on using Wikidata for Emulation as a Service Infrastructure. 
- Articles for reading and discussion (see Action Items, below). 
- Development of competency questions to guide data modeling. 
- Research existing ontologies. 
- Tools? 
 
 
- Report on Knowledge Graphs for AI: Wikidata and Beyond (presentation by Markus Krötzsch) 
Meeting Notes#
- CFP: _Cataloging & Classification Quarterly _on AI & subject classification 
- Jeremy: update on ai4lam Community Call - Training coming up in March/April 
- Jeremy gave an update on models metadata effort & possible metadata session @ next FF conference. 
- Next community call next week: focus on NER 
 
- Tim: Moving forward with metadata requirements for AI models and datasets - Next meeting in March will have a presentation by Kat Thornton on using Wikidata 
- March meeting - reading and discussion on articles listed under Action Item 
- Research questions ontologies 
 
- Tim: Knowledge Graphs for AI: Wikidata and Beyond by Markus Krötzsch - First 30 minutes overview of Wikidata and how to use 
- Last 15 minutes most useful - Issues around scalability, works at the current scale 
- AI applications use Knowledge Graphs, hard to tell if Google uses Wikidata in search results, 
- Machine learning vs. Machine Knowing - Self-driving cars 
- Intelligent assistant 
- Expert systems 
- Playing Go 
 
- ML algorithms are just a small part of ML-base systems 
- Important AI systems have significant non-ML components 
- Even simple systems are hard to understand 
 
 
- David: Issues with participation in Challenge WG, on AI interest and activity - CNI group - approach for more, broader group of people with decision-making positions 
- Presentation on the challenge, big deal, push for more equitability AI 
- Challenge WG, challenge a big deal and needs to be thought-out. WG currently doing lit review, scope, and what is involved. 
- Single problem or work on a single data-set? Scoping, sponsorship 
 
Action Items#
- Reading list for March meeting: - Mitchell, M., Wu, S., Zaldivar, A., Barnes, P., Vasserman, L., Hutchinson, B., Spitzer, E., Raji, I. D., & Gebru, T. (2019). Model Cards for Model Reporting. Proceedings of the Conference on Fairness, Accountability, and Transparency, 220–229. https://doi.org/10.1145/3287560.3287596 
- Noy, N. F., & McGuinness, D. L. (n.d.). Ontology Development 101: A Guide to Creating Your First Ontology. 25. https://protege.stanford.edu/publications/ontology_development/ontology101.pdf 
- Thornton, K., Cochrane, E., Ledoux, T., Caron, B., & Wilson, C. (2017). Modeling the Domain of Digital Preservation in Wikidata. 10. https://phaidra.univie.ac.at/view/o:931058 
 
