Reproducible Research: Essentials for Managing Your Data
I Introduction
Workshop Info
Pre-work
Schedule
Meet Your Faculty
II Modules
Module 1: Introduction to Research Data Management
Lecture
Module 2: Version Control with Git
Contents
Learning Objectives
Learning Outcomes
Success Criteria
Self-assessment
Formal assessment
Agenda
Lecture (20 min)
Lecture Agenda
Lecture Slides
Lab (40 min)
Lab Agenda
Prerequisite
Lab Tracks
Wrap-up and Key Takeaways
Reference
Module 3: Organizing Your Data for Machine-Actionability
Lecture
Lab
Sections covered:
1. Organization
2. Requirements
3. Introducing JSON
4. Validating Schemas
5. JSON Syntax
6. Mermaid
7. External Ontology validation
8. Additional challenges
Module 4: Facilitating Discovery of your Datasets using Open Source Platforms and Standards
Lecture
Lab
Module 4 Lab: Discovering Data with GA4GH Standards
Learning objectives
Before you start: checklist
Section A: Discover data through a Beacon Network UI
A.1: Observe the federation
A.2: A clinical query every node can answer
A.3: Reveal the rest, and watch nodes drop out
A.4: Add a genomic variant
What just happened
Section B: Running Beacon v2 API queries
Using Hoppscotch
B.1: Sanity check the endpoint
B.2: List supported filters (and notice two different styles)
B.3: A real, filtered query on Progenetix
B.4: Same query shape, a different Beacon
B.5: A convenience parameter: query by gene
B.6: Same shape on ICHANGE: HIST1H3B + DIPG
Section C: Bento as a discovery platform
What to look for
Mini-task
Same dataset, Beacon lens
Wrap-up
Sponsors
Reproducible Research: Essentials for Managing Your Data 2026
Module 1: Introduction to Research Data Management
Lecture