MANUFACTURING community of practice: Difference between revisions
From NCOR Wiki
Jump to navigationJump to search
mNo edit summary |
mNo edit summary |
||
Line 15: | Line 15: | ||
'''MANUFACTURING Community of Practice''' | '''MANUFACTURING Community of Practice''' | ||
[http://ontology.buffalo.edu/smith Barry Smith], [http://ncor.us National Center for Ontological Research] | :[http://ontology.buffalo.edu/smith Barry Smith], [http://ncor.us National Center for Ontological Research] | ||
[https://www.linkedin.com/in/jmilinovich/ John Milinovich], Pinterest | :[https://www.linkedin.com/in/jmilinovich/ John Milinovich], Pinterest | ||
[https://www.linkedin.com/in/bill-regli-083552/ William Regli], DARPA | :[https://www.linkedin.com/in/bill-regli-083552/ William Regli], DARPA | ||
[https://www.nist.gov/people/ram-d-sriram Ram Sriram], NIST | :[https://www.nist.gov/people/ram-d-sriram Ram Sriram], NIST | ||
[https://www.energy.gov/eere/amo/articles/welcome-dr-sudarsan-rachuri Ruchari Sudarsan], DOE | :[https://www.energy.gov/eere/amo/articles/welcome-dr-sudarsan-rachuri Ruchari Sudarsan], DOE | ||
'''Existing ontologies or taxonomies from manufacturing and related domains''' | '''Existing ontologies or taxonomies from manufacturing and related domains''' |
Revision as of 16:11, 30 September 2017
Open Knowledge Networks (OKN)
- What is the state-of-the-art for open knowledge networks in MANUFACTURING?
- What are some driving research questions that will benefit from MANUFACTURING OKN?
- What are some driving commercial or consumer questions that will benefit from MANUFACTURING OKN
- What are the gaps, why do they exist, and how do we address them?
- How is MANUFACTURING different from other practices (biomedical, health, GEO, finance, self-driving vehicles, etc)?
- What do we share with other domains? How can we benefit from this synergy?
MANUFACTURING Community of Practice
- John Milinovich, Pinterest
- William Regli, DARPA
- Ram Sriram, NIST
- Ruchari Sudarsan, DOE
Existing ontologies or taxonomies from manufacturing and related domains
Existing (mostly public) Datasets
Use cases
Use cases span the following broad areas:
- Manufacturing Capabilities (of companies, of manufacturing equipment, of sensors, ...)
- Use case: classification of suppliers, screening to select suitable suppliers (risk mitigation in supply-chain management -- for example when accepted bidder might drop out)
- In progress: scraping information on the webpages of manufacturing companies and mapping terms identified to ontologies to enable reasoning (Farhad Ameri, Collaborative agreement between NIST and Texas State)
- Can we create wikipedia-like pages for each company from this activity?
- Manufacturing Readiness Levels (MRL) of interest also to DOD
- Manufacturing Processes
- Manufactured Products
- So far what exists are primarily NLP-based attempts to identify emerging trends in customer needs or markets for example from the study of Amazon reviews of products
- Standard for the Exchange of Product Model Data (STEP)
- Can we convert this activity into an ontology-based OKN?
- Materials
- On-going AFRL work (Clare Paul, Wright-Patt) to create a MatOnto, a large materials science ontology growing out of the Materials Genome Initiative
- Workforce development
- (from OKN Finance CoP) Creating many economic datasets based on social media, e.g., “i lost my job” to approximate something about the labor market.
- Patents
- Use case: to enable enhanced patent search resolving terminological inconsistencies
- Focus on the patent system
- Retrieval of patent information
- Comparison of International Patent Classification (IPC) with MeSH
- Robots
- Probably not enough data in the public domain to enable a useful OKN for robot use in manufacturing at this stage
Examples of questions the OKN methods might be able to answer
- One goal is to develop automatically short reports / wikipedia article specific to the question being queried
Methodology: Federation with mappings or coordinated development?
- Role of Industry Ontology Foundry
What open data already exist?
- What are the questions that are being asked to the data? How is the answer currently discovered? Which datasets are consulted to find the answer?