Ihaka Lecture Series 2024 - Engaging through data

Please note that we will have some refreshments at 6pm, 30 minutes prior to the lectures in the 303 Foyer (Room B00L2).

Livestreams are available for each lecture - streaming links will be announced below.

Data analysis is no longer confined to individuals working in isolation. Modern connectivity and complexity of problems requires teamwork, reproducibility and collaboration. Similarly, the analytic outputs must be actionable, understandable and intuitive such that wider communities can benefit from the results by engaging with the analyses and data, to participate in the outcome.

The 2024 Ihaka Lecture Series features three speakers that bring together visualisation, teamwork and reproducibility. They share their real-world experience in developing engaging visualisations, bringing people and tools together and a vision for reproducible data analysis.

Speaker: Yihui Xie

Abstract: I first came across Sweave in R around 2007 and fell in love with it immediately. Later I learned about the idea behind Sweave, literate programming, and found it quite interesting, too. Literate programming may not be very useful for programming, but is a perfect paradigm for automated report generation. That is, generating (data analysis) reports automatically from computer code. In 2011, I started developing the R package knitr to explore further the potential of literate programming, which achieved some success (especially with the invention of R Markdown), but when looking back after thirteen years, I couldn't believe that I missed some good ideas that should have been so obvious, and also implemented some ideas so awfully. In this lecture, I'll share some thoughts along the design of a reimagined report generator in R after gaining first-hand experience with R Markdown users in the industry in 2024. I'll also explain the philosophy and rationale behind some decisions when writing this software package.

About the speaker: Yihui Xie (https://yihui.org) is currently an independent consultant on R Markdown and R package development. Previously, he worked as a software engineer at Posit Software, PBC (formerly RStudio, PBC) from 2013 to 2023. He earned his PhD from the Department of Statistics, Iowa State University. As an active R user, he has authored several R packages, such as knitr, bookdown, blogdown, xaringan, animation, tinytex, and pagedown, among which the animation package won the 2009 John M. Chambers Statistical Software Award (ASA). He also co-authored a few other R packages, including shiny, rmarkdown, rticles, and leaflet. He has published five books related to R Markdown, including "Dynamic Documents with R and knitr", "R Markdown: The Definitive Guide", and "R Markdown Cookbook", etc.

LIVESTREAM: TBC

Speaker: Farah Hancock

Abstract: Ever have data which shows something so important you wanted to hit people right in the "feels" with your visualisation? There will always be a need for simple charts, which just show the facts, but sometimes when the numbers are compelling there's a call to think beyond a bar chart and visualise data in a way which evokes emotion.

In this presentation, Farah will look at examples of this sort of data visualisation and walk through the process of the visualisation choices made in two very different projects published on the RNZ.co.nz.

About the speaker: Initially trained as a designer, Farah Hancock worked for many years in the advertising industry in New Zealand and abroad, primarily working on digital campaigns. Experiencing a midlife career crisis she pivoted to journalism and as a visual thinker she inadvertently fell into data journalism when the Covid-19 pandemic started. Since then she’s visualised a range of topics from food exports to bus cancellations, fatal police shootings and political donations. She lives in Tāmaki Makaurau / Auckland and works at RNZ in its investigative In Depth team.

LIVESTREAM: TBC

Speaker: Peter Ellis

Abstract: Managed well, R can be a critical component of a transformation of the effectiveness and efficiency of an analytical team in government. R's competitor in government is not Julia or Python or even SAS, but overwhelmingly Excel. The keys to making the most of R are not the latest and fanciest R packages, but integrating it into a new workflow. That workflow also uses Git and (probably) SQL. It breaks down micro-silos and the "lone genius who understands the spreadsheet", replacing them with teamwork, transparency, reproducible analytical pipelines, peer review, and home-grown R packages and rules for use.

Doing this successfully is difficult and depends on process changes, firm direction from management, and a nuanced understanding of public sector incentives and risk aversion. It means challenging assumptions that public servants, non-IT contractors and management consultants don't write code; and changing recruitment and professional development. In this talk I'll draw on experiences in several countries and very different environments to explore these issues; and see if we can identify the secret sauce to making R bloom in the potentially difficult soil of a public sector bureaucracy.

About the speaker: Peter Ellis is the Director of the Statistics for Development Division at the Pacific Community (SPC), where his team of around 30 statisticians, data scientists and analysts help Pacific Island country and territory statistical offices collect, process, analyse and disseminate data for official statistics. He is an Accredited Statistician with the Statistical Society of Australia. He was previously the Chief Data Scientist at Australian-headquartered management consultancy Nous Group where he led a transformation of its approach to analytics based on R, SQL and Git. Prior roles included the Principal Data Scientist at Stats NZ, General Manager Evidence and Insights at the Social Investment Agency, Manager Sector Performance at Ministry of Business, Innovation and Employment, and Director Program Evaluation for the Australian aid program. His blog is at https://freerangestats.info/.

LIVESTREAM: TBC

For more details, please view the

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Host or Publisher Faculty of Science, University of Auckland