Data makes science possible. Sharing data improves visibility, and makes the research process transparent. This increases trust in the work, and allows for independent reproduction of results. However, a large proportion of data from published research is often only available to the original authors. Despite the obvious benefits of sharing data, and scientists' advocating for the importance of sharing data, most advice on sharing data discusses its broader benefits, rather than the practical considerations of sharing.

This talk is framed as a discussion, and it covers some of pain points of sharing data alongside research. The talk will be framed as a discussion. One of the key messages we are trying to impart is sharing data falls on a continuum, and entering it should come with minimal barriers.

• You don't have to do every single thing to publish your data
• Take small steps - get the data somewhere first, add more detail as you go
• Try and get a DOI from a service like Zenodo or Dryad

• Karthik Ram
• Miles McBain
• Anna Kystalli
• Daniella Lowenberg
• ACEMS International Mobility Programme
• Helmsley Charitable Trust
• Gordon and Betty Moore Foundation
• Sloan Foundation

• making your code citable
• Stodden et al
• Rowhani-Farid & Barnett

• Slides made using xaringan
• Extended with xaringanthemer
• Colours taken + modified from lorikeet theme from ochRe
• Header font is Josefin Sans
• Body text font is Montserrat
• Code font is Fira Mono

Dr. Nicholas Tierney (PhD. Statistics, BPsySci (Honours)) is a Lecturer in Business Analytics and Statistics at Monash University, working with Professors Dianne Cook and Rob Hyndman. His research aims to improve data analysis workflow, and make data analysis more accessible. Crucial to this work is producing high quality software to accompany each research idea. Mostly recently, Nick's work is focussing on exploring longitudinal data (brolgar), and improving how we share data alongside research ( ddd). Other work has focussed on exploring data with the R package visdat, and on creating analysis principles and tools to simplify working with, exploring, and modelling missing data with the package naniar. Nick has experience working with decision trees (treezy), optimisation (maxcovr), Bayesian Data Analysis, and MCMC diagnostics (mmcc.

Nick is a member of the rOpenSci collective, which works to make science open using R, has been the lead organiser for the rOpenSci ozunconf events from 2016-2018 (2016, 2017, 2018), and co-hosts the rstats podcast "Credibly Curious" with Dr. Saskia Freytag. Outside of research, Nick likes to hike, rockclimb, make coffee, bake sourdough, (eventually) knit a hat, take photos, and explore new hobbies.