Framework Builder

Step 01 of 04

Who is this framework for?

Different audiences need different structure and depth. Choose the context that best fits your use case.

Student Projects

Academic or coursework data science projects

Organizations

Company-level teams and enterprise data work

Mixed / Any

Flexible — suitable for any data science project

Step 02 of 04

Choose your framework format

Select one or more formats. Each adds a different layer to your framework:

Principles — high-level value statements
Checklist — concrete actionable items
Rubric — score and evaluate decisions

Principles Guide Checklist Evaluation Rubric

Step 03 of 04

How detailed should it be?

Choose the depth of guidance generated for your framework.

Guided Suggestions

Prompts and suggestions to fill in yourself — faster to set up

Full Step-by-Step

Detailed instructions including stakeholder mapping, risk, and accountability

Step 04 of 04

Select your principles

Choose the dimensions that matter most to your project. You can select as many as you need.

Core Ethics

Fairness Ethics Beneficence

Governance

Accountability Transparency Proportionality

Data Protection

Privacy Security Data Quality

Social Impact

Inclusivity Accessibility Context Awareness Impact Assessment

Process & Growth

Adaptability Sustainability Collaboration

Criteria	4 — Excellent	3 — Good	2 — Fair	1 — Poor
Transparency
Fairness
Accountability
Impact Awareness

Who is this framework for?

Choose your framework format

How detailed should it be?

Select your principles

Generated Meta-Framework

Framework Checklist

1 — Define the Goal

2 — Inputs & Resources

3 — Process Steps

4 — Evaluation

Guided Principles Framework

Transparency

Fairness

Accountability

Evaluation Rubric