🌟 Introduction to Conda & FAIR Data Workshop

🎯 Workshop Goals

🔹 Conda Workshop Goals:

• 🧰 Learn to manage packages and environments with Conda.
• 🔁 Build reproducible workflows for data science projects.
• 🌐 Use Conda across multiple programming languages.
• 📦 Share project-specific environments for collaboration.
• 📊 Strengthen core data science skills at KAUST and in KSA.

Learn - on an example: NOMAD - what FAIR data is, and tools that enable to create FAIR data, or convert data to FAIR data:

• 🔍 Findable – Metadata, indexing, and persistent identifiers
• 🗂️ Accessible – Open formats, licensing, and repositories
• 🔗 Interoperable – Standards, vocabularies, and APIs
• 🔁 Reusable – Documentation, provenance, and quality

👨‍🔬 Who Should Attend?

• Researchers, data managers, and graduate students
• Anyone working with scientific data
• No prior experience required!

📚 What You'll Learn

🧠 From Conda

• 🧰 Create and manage environments
• 📦 Install and update packages
• 🔁 Ensure reproducibility
• 🌐 Work across languages
• 📤 Share setups with others

🧠 From FAIR/NOMAD

• 🔍 – Create a dataset with persistent identifiers 
• 🗂️ – Share a dataset with the community while giving proper credit to contributors (including you)
• 🔗 – Conversion of data into a standard community-used format
• 🔁 – Retrieve data and information from a discipline repository. Use and design of Electronic Laboratory Notebooks (ELNs) for proper documentation

Agenda

Agenda:

20 minutes - Introduction to FAIR data and NOMAD

20 minutes - Exploring NOMAD entries, use NOMAD data

20 minutes - Upload data and create datasets

As much as you can give me:

1. Document your research = META data

1. Built-in Electronics Laboratory Notebooks (ELNs)

1. Customize laboratory notebooks

1. Automatize inputs

10 minutes - An example of more advanced application:

1. Parser

1. GUI

1. Connection with other datasets / other examples of ELNs