Rahimi M1, Joughin E1, Bruns Jr L1
1AURIN, University of Melbourne, Australia
Biography:
Masoud Rahimi is a Lead Data Scientist at the Australian Urban Research Infrastructure Network (AURIN), where his work comes down to two things: helping researchers get the data they need and do more with it, through data access, expert consultancy, and technical enablement. Masoud brings a PhD in Information Systems (Spatial) from the University of Melbourne and a genuine interest in what happens when AI meets real-world research problems. He spends most of his time making complex data accessible, legible and useful to researchers, and thinking about how research infrastructure can play a more proactive role in creating societal impact.
Abstract:
Research infrastructure organisations invest heavily in building data capability, yet uptake among researchers often lags far behind what the infrastructure can offer. The gap is not always technical. Researchers frequently struggle to see how a dataset connects to their own question, particularly when the data is novel, complex, or unfamiliar. Documentation and data catalogues help, but they describe what data is, not what it can do.
The Australian Urban Research Infrastructure Network (AURIN) Data Tales takes a different approach. Rather than cataloguing data capabilities, the series demonstrates them by doing: taking a real urban question, applying AURIN's spatial and urban datasets to it, and telling the story of what the data reveals in language that non-specialist audiences can understand.
The specific topics matter less than the pattern they establish. Spanning retail geography, major events, welfare geography, and cultural behaviour, each piece creates visibility for both the data and the research behind it, drawing findings out of academic publications and into conversations where they can influence decisions.
This presentation argues that data storytelling is an underutilised tool in the research infrastructure toolkit. When researchers can see a worked example, they are more likely to engage with the underlying data. When practitioners read a clear, evidence-based narrative, they are more likely to act on research that might otherwise sit on a shelf. AURIN Data Tales offers a model for closing both gaps: between data capability and research use, and between research findings and real-world application.
