π Introduction to Conda & FAIR Data Workshop
ποΈ Date & Time
- Sunday, Sep 28, 2025
- 9:00 am - 1:00 pm
π Venue
- Building 1, Level 2, Multi-purpose Room (MPR) (Desert Side)
π₯ Organizers
Didier Barradas Bautista
Visualization Core Laboratory
didier.barradasbautista@kaust.edu.sa
Julien Gorenflot
Research Data Management
julien.gorenflot@kaust.edu.sa
Register
π§ͺ How to Prepare
- Read: GO FAIR Principles
πΌ Bring With You
- Laptop
- ORCID ID
- GitHub account
- Curiosity and questions!
π― Workshop Goals
πΉ Conda Workshop Goals:
- π§° Learn to manage packages and environments with Conda.
- π Build reproducible workflows for data science projects.
- π Use Conda across multiple programming languages.
- π¦ Share project-specific environments for collaboration.
- π Strengthen core data science skills at KAUST and in KSA.
πΉ Learn - on an example: NOMAD - what FAIR data is, and tools that enable to create FAIR data, or convert data to FAIR data:
- π Findable β Metadata, indexing, and persistent identifiers
- ποΈ Accessible β Open formats, licensing, and repositories
- π Interoperable β Standards, vocabularies, and APIs
- π Reusable β Documentation, provenance, and quality
π¨βπ¬ Who Should Attend?
- Researchers, data managers, and graduate students
- Anyone working with scientific data
- No prior experience required!
π What You'll Learn
π§ From Conda
- π§° Create and manage environments
- π¦ Install and update packages
- π Ensure reproducibility
- π Work across languages
- π€ Share setups with others
π§ From FAIR/NOMAD
- π Create a dataset with persistent identifiersΒ
- ποΈ Share a dataset with the community while giving proper credit to contributors (including you)
- π Conversion of data into a standard community-used format
- π Retrieve data and information from a discipline repository.Β Use and design of Electronic Laboratory Notebooks (ELNs) for proper documentation
Agenda
Time | Topic |
---|---|
09:00 | Introduction to Conda |
09:30 | Working with Environments |
10:00 | Using Packages and Channels |
10:30 | Sharing Environments |
11:00 | Introduction to FAIR data and NOMAD |
11:20 | Exploring NOMAD entries, use NOMAD data |
11:40 | Upload data and create datasets |
12:00 | FAIR Data automation and examples |