The Materials Commons 2.0�A Collaboration Platform and Information Repository for the Global Materials Community ��

Staff: Glenn Tarcea,

Domain Scientists: Brian Puchala, Tracy Berman,

and John Allison

The University of Michigan

Supported by DOE

Materials Commons 2.0

• August 2016 - MC 1.0
• April 2020 - MC 2.0
• Over 650 Registered Users
• Nearly 4 Million files uploaded
• Over 26TB of Data
• Nearly 870,000 Sample and Process Attributes
• New Features and Updates released monthly
• Over 80 Published Datasets
• More than 14,000 views
• Nearly 7000 downloads

FAIR

• FAIR Data is a way to help with data reuse of scientific data
• FAIR stands for (F)indablity, (A)ccessibility, (I)nteroperability, and (R)eusability
• Many repositories talk of FAIR compliance as its become a new buzzword to describe their services
• FAIR is an important part to helping with scientific data

Typical Published Dataset

• Here is a typical published dataset
• It contains a tile, some descriptives, and 1 or more files to download

FAIR - Not Understandable

• Your typical dataset and repository might be FAIR compliant but it doesn’t really help with data reuse
• To get to data reuse researchers need to be able to understand your data
• How was it collected
• What are the important attributes
• Were there processing steps
• What are the relationships
• Where to start
• What are the important files/meta data
• etc..
• Getting to understandability is both a social problem and a technical problem

Understandable?

• Social Issues
• Researchers are not incentivized to make their publish data understandable
• References to the paper are insufficient
• A lot of published data has information encoded in ways that make sense to the researcher
• How they name their directories and files
• Column names in a spreadsheet
• Names of attributes
• Etc…
• We need community participation as well as help from the funding agencies to fully solve the social issues
• Technical Issues
• We need tools that
• Help a researcher organize and present their data
• Create their data in standardized formats
• Communicate to a wider audience
• We can’t just publish files, we need to give other researchers looking at the data the tools to understand it
• And tools to reuse it

Materials Commons - UFAIR

• In Materials Commons we are working to bring more of the pieces together that help with the data re-use part
• How?
• By Integrating tools such as OpenVisus and Paraview
• By Creating Workflows to generate starting projects and data in well known formats
• By giving researchers ways to present that data in ways that helps to provide context and importance
• By tracking data re-use and helping with attribution
• By providing a space for different communities to work together creating standards that make sense for them
• We have some of the pieces described above. A big push for us for the foreseeable future is improving these, filling in gaps, and taking this vision a step or two closer to reality

Findability

• The Data Explorer includes a query interface
• Zoom in and answer questions about particular samples and processes
• See ranges and values for parameters
• Find processes and samples by filtering your data
• Save your queries for reuse

Findability

• View your data, workflow and file relationships
• Compare different samples and see what is different

Queries Enabled By Our Data Model

Scientific knowledge is encoded in the process data:

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• Sectioning creates new samples, but the created samples have the same composition and hardness.

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• Measurements on one sample (A, B, C, D, or E) can be applied to all samples.

Accessibility

Interoperability

• Use your favorite libraries in the Jupyter Notebook
• Visualize your data in the Jupyter notebook or on MaterialsCommons.org
• Work with remote and local data and keep it up to date

Interoperability

• Visualize your data in OpenVisus

Upcoming Feature - Paraview

Outreach and Integration -NSDF/OSN

• The National Science Data Fabric is creating a platform agnostic testbed for democratizing data delivery
• PRISMS Center provides the Materials Science requirements
• Materials Commons is integrating with NSDF to provide easy access to our data

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• NSDF Testbed for OSN/NRP integration
• Materials Commons datasets available in the NRP environment
• Allows for easy access to Materials Commons published data in the OSG/NRP environment
• Future plans include allowing data from OSN/NRP to be automatically added to Materials Commons

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CHESS

• Goals
• Remote visualization of data
• Automatic import into Materials Commons
• High Speed Link To/From CHESS
• Automated data movement

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Reusability

• Home page provides a wealth of information
• You can easily import a dataset into your own project
• Access to download using globus, individual files, or a zipfile
• Automatically added to Google Datasets Search
• Easily import data into your project

Bringing it together

Tools for improving our scientific understanding

• Develop tools to improve our scientific understanding
• Fit into scientific workflow
• Interatomic Potential Fitting
• CASM->ML->DFT/FE
• Visualization Tools
• Paraview
• Improved OpenVisus Integration
• Import data from common formats to apply our query interface to
• Community Specific Tools

Curation and Publishing

• Curation tools for dataset publishers and editors
• Publish with an “embargo” period
• External Editors have a special link to review
• Data Citation Support
• Data Citation Counts
• Tracking published data used in other Materials Commons projects
• Publishing to Social Media
• Custom Dataset Pages

Wrap up

• Materials Commons is being actively developed
• We see lots of opportunities to extend the platforms reach
• Our focus for the next 3 year is expanding its reach through partnerships, improving the publication process, and custom tools for the scientific community and our users

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