Workshop Data on Autonomous Methodologies for Accelerating X-ray Measurements
Resources
18 resources available
-
README
TEXT/PLAIN -
cards
TEXT/CSV -
g1-b1-goals-lab
IMAGE/JPEG -
g1-b2-goals-xrd
IMAGE/JPEG -
g1-b3-challenges-analysis
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g1-b4-solutions-analysis
IMAGE/JPEG -
g1-b5-challenges-AI-lab
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g1-b6-solutions-AI-lab
IMAGE/JPEG -
g1-b7-challenges-hardware
IMAGE/JPEG -
g1-b8-solutions-hardware
IMAGE/JPEG -
g2-b1-goals-lab
IMAGE/JPEG -
g2-b2-goals-xrd
IMAGE/JPEG -
g2-b3-challenges-analysis
IMAGE/JPEG -
g2-b4-solutions-analysis
IMAGE/JPEG -
g2-b5-challenges-AI-lab
IMAGE/JPEG -
g2-b6-solutions-AI-lab
IMAGE/JPEG -
g2-b7-challenges-hardware
IMAGE/JPEG -
g2-b8-solutions-hardware
IMAGE/JPEG
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Complete Metadata
| @type | dcat:Dataset |
|---|---|
| accessLevel | public |
| bureauCode |
[
"006:55"
]
|
| contactPoint |
{
"fn": "Zachary Trautt",
"hasEmail": "mailto:zachary.trautt@nist.gov"
}
|
| description | The National Institute of Standards and Technology and the International Centre for Diffraction Data co-hosted a workshop on 17-18 October 2023 to identify and prioritize the goals, challenges, and opportunities for critical and emerging technology needs within industry, with an emphasis on leveraging artificial intelligence, data-driven methodologies, and high-throughput and automated workflows for accelerating x-ray-based structural analysis for materials development and manufacturing. Participants, predominantly from industry, gathered in-person at ICDD headquarters in Newtown Square, Pennsylvania. The data collected during this workshop is published in this data publication. This data is interpreted in the workshop report, which cites this dataset.Certain equipment, instruments, software, or materials, commercial or non-commercial, are identified in this dataset. Such identification does not imply recommendation or endorsement of any product or service by NIST, nor does it imply that the materials or equipment identified are necessarily the best available for the purpose. |
| distribution |
[
{
"title": "README",
"mediaType": "text/plain",
"downloadURL": "https://data.nist.gov/od/ds/mds2-3498/README.txt"
},
{
"title": "cards",
"mediaType": "text/csv",
"downloadURL": "https://data.nist.gov/od/ds/mds2-3498/cards.csv"
},
{
"title": "g1-b1-goals-lab",
"mediaType": "image/jpeg",
"downloadURL": "https://data.nist.gov/od/ds/mds2-3498/g1-b1-goals-lab.JPG"
},
{
"title": "g1-b2-goals-xrd",
"mediaType": "image/jpeg",
"downloadURL": "https://data.nist.gov/od/ds/mds2-3498/g1-b2-goals-xrd.JPG"
},
{
"title": "g1-b3-challenges-analysis",
"mediaType": "image/jpeg",
"downloadURL": "https://data.nist.gov/od/ds/mds2-3498/g1-b3-challenges-analysis.JPG"
},
{
"title": "g1-b4-solutions-analysis",
"mediaType": "image/jpeg",
"downloadURL": "https://data.nist.gov/od/ds/mds2-3498/g1-b4-solutions-analysis.JPG"
},
{
"title": "g1-b5-challenges-AI-lab",
"mediaType": "image/jpeg",
"downloadURL": "https://data.nist.gov/od/ds/mds2-3498/g1-b5-challenges-AI-lab.JPG"
},
{
"title": "g1-b6-solutions-AI-lab",
"mediaType": "image/jpeg",
"downloadURL": "https://data.nist.gov/od/ds/mds2-3498/g1-b6-solutions-AI-lab.JPG"
},
{
"title": "g1-b7-challenges-hardware",
"mediaType": "image/jpeg",
"downloadURL": "https://data.nist.gov/od/ds/mds2-3498/g1-b7-challenges-hardware.JPG"
},
{
"title": "g1-b8-solutions-hardware",
"mediaType": "image/jpeg",
"downloadURL": "https://data.nist.gov/od/ds/mds2-3498/g1-b8-solutions-hardware.JPG"
},
{
"title": "g2-b1-goals-lab",
"mediaType": "image/jpeg",
"downloadURL": "https://data.nist.gov/od/ds/mds2-3498/g2-b1-goals-lab.JPG"
},
{
"title": "g2-b2-goals-xrd",
"mediaType": "image/jpeg",
"downloadURL": "https://data.nist.gov/od/ds/mds2-3498/g2-b2-goals-xrd.JPG"
},
{
"title": "g2-b3-challenges-analysis",
"mediaType": "image/jpeg",
"downloadURL": "https://data.nist.gov/od/ds/mds2-3498/g2-b3-challenges-analysis.JPG"
},
{
"title": "g2-b4-solutions-analysis",
"mediaType": "image/jpeg",
"downloadURL": "https://data.nist.gov/od/ds/mds2-3498/g2-b4-solutions-analysis.JPG"
},
{
"title": "g2-b5-challenges-AI-lab",
"mediaType": "image/jpeg",
"downloadURL": "https://data.nist.gov/od/ds/mds2-3498/g2-b5-challenges-AI-lab.JPG"
},
{
"title": "g2-b6-solutions-AI-lab",
"mediaType": "image/jpeg",
"downloadURL": "https://data.nist.gov/od/ds/mds2-3498/g2-b6-solutions-AI-lab.JPG"
},
{
"title": "g2-b7-challenges-hardware",
"mediaType": "image/jpeg",
"downloadURL": "https://data.nist.gov/od/ds/mds2-3498/g2-b7-challenges-hardware.JPG"
},
{
"title": "g2-b8-solutions-hardware",
"mediaType": "image/jpeg",
"downloadURL": "https://data.nist.gov/od/ds/mds2-3498/g2-b8-solutions-hardware.JPG"
}
]
|
| identifier | ark:/88434/mds2-3498 |
| issued | 2024-09-17 |
| keyword |
[
"Artificial Intelligence",
"Autonomous Laboratories",
"Diffraction",
"Machine Learning",
"Materials Synthesis and Characterization",
"Robotics"
]
|
| landingPage | https://data.nist.gov/od/id/mds2-3498 |
| language |
[
"en"
]
|
| license | https://www.nist.gov/open/license |
| modified | 2023-11-03 00:00:00 |
| programCode |
[
"006:045"
]
|
| publisher |
{
"name": "National Institute of Standards and Technology",
"@type": "org:Organization"
}
|
| theme |
[
"Information Technology:Data and informatics",
"Materials"
]
|
| title | Workshop Data on Autonomous Methodologies for Accelerating X-ray Measurements |
