Developing a collaborative approach to data and analytics

A screen of data.

Almost 200 researchers from across the world analysed the same dataset.

A Swinburne research team involved in an international study with almost 200 researchers from across the world is pushing for a more collaborative future in scientific research.

In the unique paper published in Nature, titled Variability in the analysis of a single neuroimaging dataset, 70 analysis teams from leading universities and research institutions analysed the same neuroimaging dataset to test the same hypotheses.

Each team independently analysed the same brain imaging dataset, collected from 108 participants performing a monetary decision-making task at Tel Aviv University.

The analysis teams were given up to three months to analyse the data, after which they reported final outcomes for the hypotheses as well as detailed information on the way they analysed the data and intermediate statistical results.

“As the scientific process involves many variables and room for different approaches, there were differences in the outcomes from each team and how they answered the initial research questions,” says Dr Matthew Hughes, Australian National Imaging Fellow and one of the Swinburne research team members.

The study found that about half the tested hypotheses showed consistent results while the other half, varied substantially across research teams. By identifying the sources of discrepancies, this study suggests ways to improve future research.

Researchers require complex methods, big data and detailed analyses when seeking to understand human behaviours and the physical world. The variability in outcomes demonstrated in this study is due to this complex process when obtaining scientific results.

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