During this 5-day collaborative workshop event, held in conjunction with CUAHSI and the University of Washington eScience Institute, participants will learn about open source technology, models, and data for conducting state-of-the-art freshwater research. Activities will consist of interactive lectures and facilitated exploration of datasets and hands-on software development.
What is a Hackweek?
The hackweek model has emerged within the data science community as a powerful tool for fostering exchange of ideas in research and computation by providing training in modern data analysis workflows. In contrast to conventional academic conferences or workshops, hackweeks are intensive and interactive, facilitated by three core components: tutorials on state-of-the-art methodology, peer-learning, and on-site project work in a collaborative environment. This setup is particularly powerful for sciences that require not only domain-specific knowledge, but also effective computational workflows to foster rapid exchange of ideas and make discovery. This is an excellent match with the nature of freshwater research where issues are large and complex and the community is diverse and collaborative.
Information for Participants
To best benefit from the program, participants are expected to have some experience with programming in Python and with analysis of freshwater data. Successful applicants will pay a $100 registration fee. Financial support may be available based on need.
Participants are highly encouraged to participate in Water Data Science Cybertraining Webinars, hosted by CUAHSI, leading up to Waterhackweek 2020. During weekly, hour-long webinars, participants will have the opportunity to familiarize themselves with content likely to relevant to Waterhackweek tutorials.
Proposed Topics and Tutorials (Subject to Change)
- Version control (Git, Github)
- Hydroshare CUAHSI Hydrologic Information System (JupyterHub CI)
- Data and model archiving in collaborative research
- Leveraging community water data services, data encodings, and access libraries (ulmo, WOFpy)
- Publication of reproducible models (Landlab + HydroShare)
- Hydrologic Model Construction and Testing of Modeling Hypotheses (SUMMA)
- Model Optimization, Machine Learning (Spotypy)
- Cloud big data (Xarray, Dask)
- Working with spatial datasets
- Google Earth Engine
What to Expect from Waterhackweek 2020
- Peer-learning collaborations
- New skills and tools, including the latest technology and software
- Personalized mentorship from professional data scientists
- Interdisciplinary applications of data tools
- Access to an interactive library of custom tutorials
- Dedicated time and space to explore new ideas