Butterworth N1, Kainer D2, Ostwal K3
1Google Australia, Sydney, Australia, 2University of Queensland, ARC COE for Plant Success in Nature and Agriculture, St Lucia , Australia, 3The University of Sydney, Australian Centre for Robotics, Sydney, Australia
Biography:
Nate is the Science Catalyst Program Manager working at Google, uniting the amazing research taking place around the world. He has an Honours in Astrophysics, a PhD in Geophysics, and a long tenure of using research computing infrastructure to help solve tricky science problems. Somewhere along the way he became a Carpentries instructor.
Abstract:
How has the focus of the eResearch community evolved since 2010? As we plan for the next generation of digital research, understanding our past reveals the trajectory of our future. In this presentation we unveil a data-driven analysis of all 1,890 unique abstracts delivered at eResearch Australasia from 2010 to 2025. Using a large language model (Gemini 3.5 Flash) to classify historical program archives, we map the rise, fall, and transformation of key conference paradigms: compute, data, software, and intelligence.
Our findings reveal a stark narrative of technological evolution. The early 2010s keyword darling, "Data Mining," has experienced a complete demise, vanishing from talk titles entirely as vocabulary shifted to general "Machine Learning." However, in 2025, we document a sudden, dramatic divergence: general machine learning topics dropped from 8.3% to just 3.1%, while "AI" and "Generative AI" surged to an unprecedented 22.2% of all presentations. This pivot mirrors a massive resurgence in High-Performance Computing (HPC) topics, which doubled to 13.0% to support generative workloads. Amidst these changes, Data Management and Storage remains our steadfast foundation, comprising 42.6% of recent focus.
We will present interactive trend visualisations, detail the semantic analysis methodology used to bypass archive-length biases, and discuss what these shifting currents tell us about the upcoming demands and trends in the digital ecosystem and AI for Science.
