Social Functions

Welcome Reception: 

Title:Can we characterise Aotearoa New Zealand’s research data at scale
Date/Time:Thursday Feb 16
15:30
Room:Upstairs Lounge
Presenters:Nick Jones
Claire Rye
Ai-Lin Soo
Rhys Francis
Luc Betbeder-Matibet
About:This workshop seeks to translate the approach and findings from an Australian sector initiative on the characteristics of research data and its supporting infrastructures at scale, and catalyse a similar initiative in Aotearoa New Zealand. It will benefit individuals in senior management or senior operational staff of research institutions. In particular, those in senior advisory and planning roles in research data infrastructure, research data service owners, individuals from Research Offices and information management. Equally important is participation from those in research roles responsible for data governance and management at larger scales, where their role seeks to meet their wider research community and stakeholder needs.
The ‘Macro View’ of data developed by the Research Data Culture Conversation (www.researchdataculture.org) provides a first ever estimate of the scale of research data retained by Australian research institutions and national research infrastructure facilities for future access. Starting in 2017, this work built a consistent view across institutions, scaling from a few to a whole sector approach over time. The project team will describe how they carried this work forward, some of the insights gained, and how it is facilitating the conversations for change.
To bring this into an Aotearoa New Zealand context, prior to the workshop we will survey New Zealand Universities and Institutions to ask some of the key questions, such as “how much unique data does your institution hold?”, and “given the importance of Indigenous Data Sovereignty in Aotearoa, and Te Tiriti requirements around active protection of taonga, what are the volumes and properties of Indigenous data in institutions?”. This workshop will not only review the emerging ‘Marco View’ of Australian research data, but use first hand data from participating New Zealand Institutions alongside both Australian and New Zealand case studies to explore the process and findings so far. There will be a series of presentations from research institutes on activities underway that support infrastructure at scale.
The objectives of the session are to:
● Review this first ever estimate of Australia’s retained research data;
● Characterise macro level trends in the types of data being retained;
● Define learnings and identify limitations for the macro view; and
● Receive input on defining next steps for Aotearoa New Zealand with regards to research data
Requirements:*Available in Person Only

Conference Dinner: 

Title:Learn how to accelerate your research with Machine Learning on AWS
Date/Time:Thursday Feb 16
11:00 - 15:00
Room:Upstairs Lounge
Presenters:Shivonne Londt
Karl de Borst
About:Take part in a hands on workshop that will introduce you to AWS machine learning services, followed by a deeper dive into using AWS for common machine learning tasks. Amazon SageMaker is the machine learning service on AWS that can help you to build, train, and deploy machine learning models for any use case with fully managed infrastructure, tools and workflows.
Bring your own laptop with a working internet connection and the ability to connect to external websites. We will provide the AWS accounts. No prior machine learning or AWS experience needed - bring an open mind. The workshop will show you how to use a low-code, visual interface to generate predictions from a dataset using Amazon SageMaker Studio. We will move onto using Amazon SageMaker as the development environment for machine learning on AWS and work through some common machine learning tasks, such as preparing, training and deploying machine learning models.
Requirements:*Available in Person Only
Must provide your own laptop with ability to log onto wifi.
This workshop requires registration via workshop selection link by Feb 13th.

 

 

 

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Key dates


Submissions open: 31 Sept

Registration opens: 30 Sept

Submissions close: 31 Oct

Author notifications: 20 Nov

Revised abstracts due: 27 Nov

Revised author notification: 8 Dec

Presenter registration: 8 Dec

Registrations close: 26 Jan

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