July 26-27, 2023 • Online Course

Course Curriculum

The course will include four virtual modules, with supporting materials. Registrants receive access to all course materials.

Course Modules

Module 1: Introduction

Instructors: Charles Ward, David Elbert

Live Instruction Time: Wednesday, July 26, 9:00 a.m. – 12:00 p.m., EDT

This module will focus on an overview of the FAIR Data Principles, as well as their relation to the Materials Genome Initiative (MGI) and the MGI Materials Innovation Infrastructure (MII).

Learning Objectives

• Understand the motivation for adopting the FAIR data principles including the reproducibility of research; the acceleration of discovery, development, and transition; the conservation of resources; the avoidance of "vendor lock"; and the fulfilling funding agency requirements
• Gain a historical perspective on prior efforts in materials
• Explore the 15 guiding principles and sub-principles and methods for implementation
• Examine challenges for implementation within the materials community 

Format: Live instruction with group example discussions

Module 2: Recommended Practices for Materials Data Generators: Fundamentals and Principles for Data Curation

Instructors: Kareem Aggour, Logan Ward

Live Instruction Time: Wednesday, July 26, 1:00 p.m. – 4:00 p.m., EDT

This module will consider data provenance, open data formats, and more. This module will also cover the tools for making data manupulating eaiser and how to cope with data. 

Learning Objectives:

• Describe your own type of data
• Explore simple databases (i.e. MongoDB, SQL, Pandas)
• Access data from APIs
• Assemble the basic parts of an "extract transform load" pipeline
• Orgnaize data and software associated with a data analysis or machine learning project

Format: Live instruction with hands-on activities/integrations

Module 3: Recommended Practices for Materials Data Generators: Scientific Workflow and Applications

Instructors: David Elbert, Brian Puchala, Fatih Sen

Live Instruction Time: Thursday, July 27, 9:00 a.m. – 12:00 p.m., EDT

This module will especially consider workflows during materials data generation. It will include emphasis on data quality (e.g., following error, UQ, etc.)

Learning Objectives:

• Discuss the data life cycle
• Understand the goals and outcomes from implementing the FAIR Data Principles
• Explore available tools, project types, and types of data
• Examine compliance items for academics, laboratories, and industry

Format: Live instruction with hands-on activities/integrations

Module 4: Data Platforms and Tools

Instructors: Brian Puchala, Matthew Jacobsen

Live Instruction Time: Thursday, July 27, 1:00 p.m. – 4:00 p.m., EDT

This module will focus on data platforms and tools of which data generators (and users) can take advantage. Just a few examples of such platforms include: (1) the University of Michigan’s Materials Commons, (2) Chimad/National Institute of Science and Technology’s (NIST) Materials Data Facility (MDF), (3) NIST’s Interatomic Potentials Repository, and (4) Duke University’s NanoMine platform.

Learning Objectives: 

• Discuss the top concerns when planning a new solution
• Examine evaluation criteria
• Understand the available modern data platforms (structured vs unstructured databases)
• Explore data model design and system design

Format: Live instruction with hands-on activities/integrations

For More Information

For more information about this course, please contact: