
The ARDC is working with the research community to drive research software and provide Australian researchers with a competitive advantage. Each month, we talk to a leading research software engineer (RSE) and share their tips on creating, sustaining and improving software for research.
Dr Saras M Windecker is a Senior Research Officer at The Telethon Kids Institute and an honorary researcher at Curtin University. Saras is actively involved in the open research community and in promoting reproducible research practices. She uses her expertise in statistical modelling and software for applied research in public health and ecology.
What attracted you to this role?
In my current role, I have the privilege of collaborating with various researchers to transform their methods into research software that expands the boundaries of academic work. Although I am still engaged in the primary work of research, I spend a lot of time thinking about building research infrastructure and tools, and creating reusable research pipelines.
I contribute to numerous projects within the Infectious Disease Ecology and Modelling team and in collaboration with the Infectious Disease Dynamics Unit at the University of Melbourne. Throughout the COVID-19 pandemic, infectious disease researchers in these groups developed models and research code to aid decision makers. I work closely with them to build infrastructure that operationalises these models, making them accessible for broader reuse.
In addition to a number of projects that are closed source, I work on a number of open source software projects. The tools we are building are valuable not only to researchers but also to public health decision makers.
Your epiwave
package is gaining traction. What are its key features?
I’m currently focused on developing tools for quantifying epidemic dynamics. One of these projects is epiwave
, an open source package that will allow users to build an infection inference model and estimate time series of daily new infections.
This model is unique because it integrates multiple data sources to estimate the underlying infection dynamics. Besides case incidence, other data sources include hospitalisation numbers, death notifications, and wastewater and serological data. From the estimated time series of daily new infections we can then estimate important epidemic parameters, such as the effective reproduction number over time.
This package will be especially useful when case incidence data – the most commonly used source of information for estimating effective reproduction number – is unreliable or challenging to use but alternative data sources are available. We envision epiwave
as a next-generation surveillance tool that allows public health modellers and decision makers to make the best use of their available data to understand the dynamics of infections in their community.
This model and its implementation in epiwave
are still under development in collaboration with Dr August Hao, Dr Kate Senior and our team lead Professor Nick Golding.
How has this program evolved?
epiwave
is designed from the lessons of 4 years of COVID-19 situational assessment reporting to the Australian federal government. It builds on earlier methods development undertaken during critical moments.
Over the course of the pandemic, our team found that bringing in a range of data sources was helpful in understanding epidemic dynamics. Combining non-traditional data such as social distancing or testing-seeking behaviours as well as classic case-count data resulted in the previous iteration of epiwave
.
It is the foundation for us to develop an approach to data integration to inform decision-makers. Currently, epiwave
is being used to forecast infections and reproduction rates for flu, Respiratory Syncytial Virus (RSV) and COVID-19 as part of the weekly reporting for the Australian Consortium for Epidemic Forecasting and Analytics (ACEFA) forecast hub, led by Dr Freya Shearer.
Running the model on very large datasets has been made easier with access to the ARDC Nectar Research Cloud, which allowed us to access flexible computing resources. Running these analyses on a weekly basis with Nectar also helped with memory constraints on an individual computer and let us model sensitive health data in a secure, efficient environment.
What research software engineering practices do you bring to your team?
I come from a background in ecology and evolutionary biology, and still hold a position as an Associate Editor for the journal Methods in Ecology and Evolution. Throughout my early work, I found I was drawn to thinking about tools and research workflows more broadly than my specific use cases. This interest led me to invest in open research skills that I bring to my team today. Problem solving about how to develop tools, workflows and reproducible research pipelines has been extremely rewarding and transferable between disciplines.
Problem solving about how to develop tools, workflows and reproducible research pipelines has been extremely rewarding and transferable between disciplines.
The other side of working as an RSE is the opportunity to contribute to communities of practice. I have taken on the role of chair of the engagement committee for ACEFA. In this capacity, beyond supporting the development of a number of software projects for communicating and visualising infectious disease model outputs, I’ve led the construction of the technical infrastructure and guided the team on implementing version-controlled workflows for the weekly forecasting.
Which communities are you part of and would you recommend others to join?
- Australian Consortium for Epidemic Forecasting and Analytics (ACEFA)
- Society for Open, Reliable, and Transparent Ecology and Evolutionary biology (SORTEE)
Also, I recently participated in a collaborative workshop convened by the World Health Organisation (WHO) to provide expert advice on developing a central dynamic repository of epidemiological parameters that the global public health community can access, use and contribute to. This work is under active development, and those interested in participating should absolutely get involved in the community.
Keep In Touch
You can connect with Saras via GitHub, X/Twitter and LinkedIn.
If you’d like to be part of a growing community of RSEs in Australia, become a member of RSE-AUNZ – it’s free!
Updates on ARDC-Sponsored Research Software Awards
The ARDC is proud to sponsor awards for research software and research software engineers in all stages of their careers. The goal of the awards is to strengthen the recognition of research software and those who develop and maintain it as being vital to modern research.
The ARDC continues to sponsor a wide range of research software awards for 2024.
Venables Award for New Developers of Open Source Software for Data Analytics Open
The Statistical Society of Australia (SSA) Bill Venables Award is open to early to mid-career researchers/developers of new open source software primarily developed in Australia. A later-career researcher application would be considered if it was a first software project.
Learn more and apply by Friday 1 November. Also read about the:
- 2023 winners:
- Associate Professor Andrew Zammit-Mangion and Matthew Sainsbury-Dale (winners)
- predictNMB team (runner-up)
- 2022 winners, Dr Lydia Lucchesi and Sam Nelson and the Vizumap team.
Eureka Prize for Excellence in Research Software
We are pleased to announce that Professor Gordon Smyth of the Walter and Eliza Hall Institute (WEHI) has won the 2024 Australian Museum Eureka Prize for Excellence in Research Software. Currently head of WEHI’s bioinformatics division, Prof Smyth leads the development of the open-source software limma
, which helps identify and interpret changes in genomic or proteomic material.
Learn more about Prof Smyth, limma
and his award. Also stay tuned for our interviews with the other finalists, the MiniZinc and MRtrix3 team.
The ARDC is funded through the National Collaborative Research Infrastructure Strategy (NCRIS) to support national digital research infrastructure for Australian researchers.
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