Hackweeks: Community Learning Events

Organizing and teaching at Geohackweek and Oceanhackweek - innovative workshops fostering collaborative learning in geospatial and ocean data science.

Technologies

  • JupyterHub
  • Docker
  • Conda
  • Git/GitHub
  • CI/CD
  • Zenodo

Overview

Hackweeks are participant-driven workshops that combine intensive learning, community building, and collaborative project work. As an instructor and infrastructure engineer for multiple hackweek events at the UW eScience Institute (2016-2019), I helped create transformative learning experiences for hundreds of scientists.

Event Series

Geohackweek (2016-2019)

Workshop on Geospatial Data Science
Website: geohackweek.github.io

Annual week-long workshop focused on:

  • Remote sensing and geospatial analysis
  • Cloud-based geospatial computing
  • Open-source GIS tools and workflows
  • Collaborative project development

Oceanhackweek (2018-2019)

Workshop on Oceanographic Data Science
Website: oceanhackweek.github.io

Specialized workshop for oceanographic research:

  • Ocean data access and analysis
  • Scientific Python for oceanography
  • Cloud computing for large datasets
  • Marine data visualization

My Roles

Data Sharing & Collaboration Tools Instructor

Taught essential tools for modern collaborative science:

  • Conda: Environment and package management
  • Docker: Containerization for reproducible research
  • Jupyter: Interactive computing and notebooks
  • CI/CD: Continuous integration for scientific software
  • Zenodo: Publishing and citing research software

Infrastructure Engineer

Designed and deployed computing environments:

  • Set up JupyterHub instances for 50-100+ participants
  • Configured Docker images with all required software
  • Managed cloud computing resources
  • Ensured stable performance during tutorials and project work
  • Provided real-time technical support

Hackweek Model

Hackweeks revolutionize scientific training through:

Intensive Learning

  • Tutorials on modern data science tools
  • Hands-on exercises with real datasets
  • Expert instructors from academia and industry

Collaborative Projects

  • Form teams around research questions
  • Apply newly learned skills to real problems
  • Produce tangible outcomes in one week

Community Building

  • Connect researchers across institutions
  • Foster long-term collaborations
  • Create supportive peer networks

Technical Innovation

Scalable Infrastructure

Built robust cloud infrastructure that:

  • Supported 100+ simultaneous users
  • Provided consistent computing environments
  • Enabled complex geospatial and ocean data analysis
  • Maintained uptime throughout week-long events

Reproducible Environments

Created Docker containers and Conda environments that:

  • Ensured all participants had identical setups
  • Eliminated "works on my machine" problems
  • Could be reused after the event
  • Documented exact software versions

Impact & Outcomes

Participant Success

Hackweek participants:

  • Published research using skills learned
  • Built new collaborative networks
  • Contributed to open-source projects
  • Organized their own community events

Model Adoption

The hackweek model has been adopted by:

  • Multiple scientific domains (astronomy, neuroscience, etc.)
  • International research institutions
  • Professional development programs
  • Graduate training initiatives

Publications

Arendt, A. A., et al., including Setiawan, L. (2023). Hackweeks as a Model to Foster Learning and Collaboration in the Geosciences. AGU23.

IOOS Biological Data Training Workshop (2018)

Extended the hackweek model to a specialized workshop:

  • Topic: Management and analysis of marine biological data
  • Role: Infrastructure Engineer and Instructor
  • Innovation: Set up JupyterHub with RStudio Server proxy for multi-language support

Website: ioos.github.io/BioData-Training-Workshop

Community Building Philosophy

Hackweeks embody key principles:

  • Inclusivity: Welcome participants of all skill levels
  • Openness: All materials freely available and open-source
  • Collaboration: Learning through doing together
  • Sustainability: Building lasting community connections

Personal Impact

Organizing and teaching at hackweeks:

  • Deepened my expertise in cloud infrastructure
  • Developed teaching and mentoring skills
  • Built lasting collaborations across institutions
  • Contributed to the open science movement
  • Helped democratize access to advanced data science tools