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Materials Informatics 101

A programmatic approach to science

Zachary del Rosario (He/Him)

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A Programmatic Approach

Programmatic (a): Done using computer code, rather than by hand, especially to support reproducible science

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This workshop is about using informatics tools for programmatic materials science

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Why?

What’s at stake?

What opportunities?

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Why? and Hello!

What’s at stake?

What opportunities?

Hello!

  • Zachary del Rosario (he/him)
  • Faculty at Olin College
  • “I help scientists and engineers reason under uncertainty.”

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Why: What’s at Stake?

Reproducibility, Credibility, Scientific Progress, etc.

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REPRODUCIBILITY

CRISIS

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Crisis in Empirical, Inferential Work

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Crisis in Empirical, Inferential Work

In psychology, medicine, but surely not in serious physical sciences….

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Stodden et al. (2014) PNAS

[Text goes here]

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Stodden et al. (2014) PNAS

[Text goes here]

The journal Science!

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Why it Matters

Openness is crucial to science

  • E.g. “What killed alchemy?”, A. Gelman

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Honest reproducibility is nontrivial

  • Programmatic tools help!

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Why: What Opportunities?

From cat detectors

to serious science

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Only ~$20!

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More Seriously….

Big Tech is using algorithms to spread misinformation, mine your attention, and destroy democracy….

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Can we do anything useful with the same techniques?

del Rosario “Why STEM Students Need to Learn Design Refusal” (2021) Liberal Education

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Yes We Can!

Data Extraction -> Automate tedious tasks

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Data Mining -> Find and understand patterns

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Prediction -> Fill gaps in our knowledge

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Yes, Scientists Are Already Doing This!

HT-DFT +

Data Science

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What We’ll Cover

  • Data Extraction
  • Data Management
  • Data Visualization
  • Basics of Machine Learning

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What We’ll Cover

  • Data Extraction
  • Data Management
  • Data Visualization
  • Basics of Machine Learning

There is so much attention on this topic...

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What We’ll Cover

  • Data Extraction
  • Data Management
  • Data Visualization
  • Basics of Machine Learning

Data Science is so much more than just Machine Learning!

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What We’ll Cover

  • Data Extraction
  • Data Management
  • Data Visualization
  • Basics of Machine Learning

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Quick demo!

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Today’s Exercises

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A True Workshop

This is a workshop…

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… so you’re going to do some hands-on work!

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Workshop Schedule

Extract

Wrangle + Tidy

Friday

Saturday

Visualize

Model

Sunday

Monday

Tabula +

WebPlotDigitizer

Python + Jupyter

Concepts

Execution

Concepts

Execution

Concepts

Fin

Focus

Live

Take-Home

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Exercise and Notebook - In General

  • Live:
    • We’ll do this together, during the 12-2pm block

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  • Take-Home:
    • You’ll do this on your own!
    • Office hours available: 4-5pm (same Zoom)

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Exercise and Notebook - Today

  • Live: Data Extraction
    • Tabula
    • WebPlotDigitizer

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  • Take-Home: Python and Jupyter
    • Working in Jupyter
    • Python basics

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Quick Orientation!

  • Open your browser:

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bit.ly/gatw2021

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Quick Orientation

Live page for in-workshop activities

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Please open this now

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Exercise and Notebook - Today

  • Live: Data Extraction (~12:30 -- 1:30pm)
    • Tabula
    • WebPlotDigitizer
  • Standby for breakout rooms…

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Use the “Ask for Help” tool if you need help!

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Exercise Time!

Let’s get to work on Day 1 (Live)

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