‘Rolling out new kit’ for NZ Data Scientists, a user-centred approach

Georgina Rae¹, Jana  Makar¹, Will Armitage¹

¹New Zealand eScience Infrastructure (NeSI), Auckland, New Zealand

The New Zealand eScience Infrastructure (NeSI) helps researchers, institutions and universities conduct successful research endeavours by providing expertise and capability in computational and data intensive research.

As for eResearch Centres around the world, the increase in researchers applying Machine Learning techniques to answer their research questions is driving us to take another look at the services we provide, from more interactive ways to access compute to training offerings, from software packages supported to hardware.

We made a modest initial investment into NVidia’s A100 GPU technology early this year to test out how the latest technology could be useful for local researchers applying Machine Learning techniques to their research.

As an organisation NeSI aims to apply Agile practices and manage our services with a Product Management approach. We took the ‘launch’ for the new A100s as an opportunity to focus on our Product Management practice with some useful learnings. In this session we will share some of our experiences including:

– Importance of having clear goals

– Bringing together a cross-functional team

– Focusing on the users

– The ‘Post-Launch’ phase

Biography:

Georgina is the Science Engagement Manager at NeSI where she ensures that NeSI is building strong relationships with the research sector. Prior to NeSI she has worked in molecular biology and intellectual property. She is passionate about enabling research and is interested in the fundamental shifts required to level up scientific research.