Introducing Jonathan

Meet our resident geographer, YouTube star and now Research Data Specialist, Jonathan Garber, who is passionate about knowledge sharing, travel, and helping to solve data and code crimes to address global challenges.

Hi Jon! Can you please tell us a bit about your career trajectory so far?

Sure! I have worn many hats in my career so far, from physical geographer to sailing instructor, river restorationist, coder, community leader, MDAP team member, and even Youtube sensation.

In my first dream job, I sailed with scouts around my home waters on the Chesapeake Bay in Virginia. This led me to seek a career in geomorphology to make those waters less polluted. Geomorphology is greek for the moving around of dirt by wind, water, and gravity, and has certainly influenced my moves from the Rocky Mountain peaks, to the trout laden streams of the Northeastern US, and to the tropical rivers of Queensland.

During my geography PhD project at The University, I began developing Python programming skills and became interested in the power of open-source programming and its ability to share knowledge, and a wider variety of features, more widely. This interest led me to a job at Research Computing Services as a Python Research Community Coordinator.

In this role, I delivered 35 workshops with over 600 different participants and 20 volunteers and created educational videos to help introduce programming concepts and make coding as accessible as possible. I love using pop culture to help communicate technical concepts!

My keen interest in Python and community building has led me to my second dream job at MDAP where I can embed myself in research projects and share the amazing capability of open source software like Python, R, and cloud computing, and at least one new thing every day from my amazing colleagues!

Tell us about an interesting project at MDAP.

Currently, I am collaborating with Dr Simon Firestone and Dr Caitlin Pfeiffer from Veterinary Biosciences on a project that aims to help managers plan a response to a livestock epidemic through the development of a digital classification tool using AI.

The challenge: livestock epidemics can cost economies billions of dollars and lead to famines. Because these populations are generally tightly segmented and clustered in individual farms, it is very important to know the spatial distribution of different types of farms, in order to understand the transmission pathways.

The data challenge: while government records are available, they are not always current or easy to update in an emergency epidemic situation. However, a veterinary epidemiologist can easily look at an aerial photograph of farm infrastructure and discern the kind of livestock based on that farm. So why not a computer?

With the development of Convolutional Neural Networks, a type of deep neural networking, computers might be able to characterise images in the same ways that a veterinary epidemiologist can. In this collaboration, we are using a small dataset (by Machine Learning standards) to retrain a neural network model to be able to figure out which animals are located on a particular farm, by classifying aerial imagery showing farm infrastructure.

This project has brought together stakeholders from the Victorian and Australian Governments, as well as University researchers, including the MDAP team, who collectively bring skills in veterinary epidemiology, geospatial science, image processing, and data science together. The final product will be used as an operational model by managers for planning a response to livestock epidemics.

What are some of the solvable, difficult, and wicked problems on your horizon?

One side project I have taken on at the MDAP is product managing the Melbourne Coder Network, a new University tool to connect freelance digital experts (developers and designers) to other members of the University community who need coding expertise for their research or administrative projects. This was a difficult problem that soon will be solved!

This has been in collaboration with several other members of the MDAP team and PCI, including designer Jo Condon, lead developer Dr Daniel Russo-Batterham, and developer Dr Robert Turnbull, as well as Prof Andrew Turpin and A/Prof Paul Gruba who have provided content advice.

This has been my first foray into creating a customer-facing digital product. The challenges have been both technical and administrative, including learning Django, CSS, and Bootstrap programming languages, as well as satisfying cybersecurity and privacy requirements. Great care has been taken to fit the app within the University ecosystem and to make it widely usable, and accessible across The University.

The next challenge is growing the app user base, as well as the developer base whereby University students can gain valuable real-world experience while contributing to world class research projects.

Can you tell us about your latest adventure or next planned one outside of MDAP?

Sadly due to the pandemic, most of my planned adventures have been put on hold, but my last true adventure was visiting my partner in India in 2019. We started by taking a holiday in Kerala, the land of appams!

We saw some fantastic art at the Kochi-Muziris Biennale, listened to elephants trumpet their horns in a cliffside hut overlooking the Western Ghats, and saw theyyam rituals late into the night. We also were able to have an amazing weekend in Mumbai where I was introduced to the most vibrant city I have ever visited.

I was also able to compete in the 2018 Sydney to Hobart. We completed the race in four days and stopped by the iconic Wineglass Bay and Flinders Island in Tasmania on the gentle sail back to the mainland.

In the context of a rapidly evolving global environment and UoM’s research strategy, what would you most like to explore, challenge, or innovate in your work in the future?

I decided to come to the University of Melbourne because the PhD research topic was part of an interdisciplinary approach to solving environmental management problems, and I very much value working on interdisciplinary problems with practical management outcomes.

For my next challenge, I would like to understand how savvy data analytics and stewardship help fight climate change, protect and rehabilitate the environment, as well as share knowledge about environmental problems and solutions with stakeholders and the public.

To that end, I look forward to helping research projects design research questions, adapt numerical and digital methods used in other fields, and share work with stakeholders and the broader community. All the while contributing to interdisciplinary applied environmental research, and open science.