See below for the speakers presenting in 2026.
Social Investment Agency
University of Auckland
Cary Institute of Ecosystem Studies
University of Auckland
University of Auckland
University of Otago
University of Auckland
University of Auckland
University of Auckland
REANNZ
REANNZ
University of Auckland
University of Auckland
University of Auckland
REANNZ
University of Auckland
University of Auckland
Academic Consulting
University of Auckland
REANNZ
University of Auckland
Victoria University of Wellignton
University of Otago
Victoria University of Wellington
University of Auckland
University of Auckland
University of Auckland
University of Auckland
University of Auckland
REANNZ
University of Auckland
REANNZ
REANNZ
University of Auckland
University of Auckland
Victoria University of Wellington
University of Auckland
University of Auckland
University of Auckland
REANNZ
University of Auckland
Science Media Centre
University of Auckland
Victoria University of Wellington
The Integrated Data Infrastructure (IDI) is a large research database holding de-identified microdata about people and households in New Zealand. The breadth of topics covered and the length of its timeseries make it a world-leading research database. Researchers use the IDI to study health, education, social services, justice, communities, population, income, housing, and the interactions between them. However, the very things that make the IDI a powerful tool for research can also make it a difficult environment for new researchers to begin working with. This workshop will introduce the IDI, explain how researchers are using it, and provide guidance to help new researchers get started. This workshop is aimed at anyone who is interested in hearing more about the IDI and how they might use it for research. Attendees will gain a better understanding of the sort of research possible with the IDI, how the data is accessed and protected, and useful tips and guidance from an experienced IDI user.
Simon Anastasiadis Principal Data Scientist, Social Investment Agency
A data scientist and computational problem solver, Simon has worked with integrated data for over seven years. His experience includes both conducting research with integrated data at the Social Investment Agency and contributing to the development of integrated data processes at Stats NZ. Simon is the author of a range of IDI training materials including introductory projects, training videos, and automation tools.
An overview of research data management requirements, practices, tools and support across the research data lifecycle. Research data or artefatcs are defined as items created, collected or observed in the course of producing original research, regardless of format. This introductory workshop is aimed at researchers, particularly those embarking on their research career or starting a new research project. Attendees will hear about policy, legal and ethical requirements, the FAIR, CARE and Maori Data Sovereignty principles, and develop strategies for data management planning, capturing, organising, sharing, and reusing research data.
Laura Armstrong Senior eResearch Engagement Specialist, University of Auckland
Laura Armstrong is the eResearch Engagement Lead for Waipapa Taumata Rau | University of Auckland. She collaborates to engage with the research community to raise awareness and use of modern technologies and tools to advance research. Areas of focus include enabling researchers to manage research data following best practices, including FAIR, CARE and Māori Data Sovereignty data principles, and providing digital research skills and community building.
Learn how to develop reproducible and sharable workflows using Quarto and Git. We will take you through how to host collaborative research projects as a formatted (and cool looking) HTML on GitHub. With some easy-to-learn version control and markdown syntax, research outputs can be shared as a live link that is consitent with your latest analyses. One benefit of Quarto is flexibility, accepting multiple programming languages (e.g. R, Python, Julia...) and output formats (e.g. docx, pdf, html...).
Quinn Asena Data Scientist, Cary Institute of Ecosystem Studies
Dr Quinn Asena is a Data Scientist in the Forest Futures Lab at the Cary Institute of Ecosystem Studies, working on boreal forest ecology. He completed a PhD at the University of Auckland, NZ, in paleoecology and ecological modelling with George Perry and Janet Wilmshurst. He then worked as a postdoctoral research associate with Jack Williams and Tony Ives at UW-Madison, WI, in developing a state-space modelling approach for estimating biotic interactions and environment-species relationships. Quinn is interested in ecological dynamics and mechanisms that underlie change in ecosystems overtime and space. His main research focus is around biotic interactions and how ecosystems respond to environmental and climate change. Much of his previous research focused on long-term ecological trajectories and palaeoecology. Currently, Quinn is exploring contemporary ecosystem change through process-based models.
Why are you here? What are you presenting? Who are you presenting to? No, this is not the abstract for “Existentialism with Nietzsche”, it’s “Design 101: Presentations, Posters, and PowerPoints for Researchers”! Have you ever seen a research poster or a PowerPoint presentation that was truly terrible and thought, “Wow, I wonder how I could salvage that? I wonder how I can make research approachable through attractive design?” In this session, we will give you tips on what makes good visual design for research. We will walk you through the do’s (and some don’ts) and what to consider when putting together a visual research presentation, whether a poster, a PowerPoint slideshow, or another type of medium.
Ana Avilés Research Services Adviser, Student and Scholarly Services, University of Auckland
Ana Avilés is a Research Services Adviser in Student and Scholarly Services with expertise in research skills development. Ana supports early career researchers and doctoral students with their research communication and dissemination needs.
Economic, societal and environmental impact, or the 'non-academic' impact of research, is becoming an increasingly important part of the research ecosystem. It is standard practice for researchers to be asked by funders to describe the benefits of their research and how they might enable that benefit to be achieved. This session offers a high-level step-by-step guide on how to incorporate impact into your research planning.
Brittany Bennenbroek Research Impact Adviser, University of Auckland
Brittany is the Research Impact Adviser at Waipapa Taumata Rau | University of Auckland, supporting researchers in planning for and evidencing the impact of their work. With a background in science communication, she is passionate about bridging disciplines, fostering meaningful connections, and translating complex ideas into accessible insights that drive real-world change. Brittany plays a key role in strengthening research impact culture, co-developing tools and resources, and developing institutional frameworks to support impactful, engaged research for the public good.
Wikipedia has become one of the most important free and open sources of knowledge, and it’s impossible to ignore the impact it has had on the internet and society as a whole. Researchers, and in particular doctoral candidates, can gain much from engaging with Wikipedia and its sister projects. This session will introduce Wikipedia and how it relates to the world of research. We will explore how researchers can engage with Wikipedia to increase their impact and boost their research metrics, while improving coverage and representation of topics that interest them. Attendees will learn how to edit existing pages, while following best practices. If you’d like to have a go during the workshop please create an account beforehand (click the ‘Create account’ link at the top right on any Wikipedia page. We recommend choosing an anonymous name, and adding your email so you can recover your account if you lose your password).
Tamsin Braisher Wikimedian Editor,
Tamsin is a Wikimedia editor in Dunedin. She writes a lot of women’s biographies on Wikipedia, and manages the New Zealand Thesis Project, which connects information about New Zealand dissertations to their authors, advisors and subjects on Wikidata.
OpenRefine is a powerful, free, open-source tool for working with messy data: cleaning it; transforming it from one format into another; and extending it with web services and external data. This introductory, practical workshop will demonstrate how it can help you to: Understand the structure of a data set and resolve inconsistencies; Split data up into more granular parts; Match local data up to other data sets; Enhance a data set with data from other sources. Setup instructions can be found here
Programming skills are becoming more and more important for researchers to effectively collect, analyse, and translate data into publication-ready insights and figures. But it can be difficult to 'take the plunge' and learn those first steps. This practical, follow-along workshop is aimed at those who are completely new to programming, and introduces the R programming language for data analysis. Participants will learn about the most important concepts for starting with R, including setting up a project in R, basic programming principles, reading in data, summarising and subsetting data, and creating basic plots. We aim to give participants a brief overview of what is possible with R and to inspire them to continue learning. Participants will be expected to follow along and will be provided with set up instructions in advance, which must be completed before the workshop.
Murray Cadzow Scientific Programmer, University of Otago
Murray is on the Scientific Programming team for Research Teaching and IT Support at the University of Otago. With a PhD in Biochemistry, he works alongside researchers with their computational workflows and organises and instructs Software and Data Carpentry workshops.
This session offers practical guidance for researchers on how to publish strategically and purposefully. Learn how to assess journals for quality and fit, avoid predatory publishers and understand key indicators like peer review, indexing and journal metrics. We’ll share tips for publishing in top-tier journals such as Nature and Science, and explore purpose-driven strategies including Open Access, Indigenous publishing and broader outputs like policy briefs and preprints. Whether you're aiming to advance your career, share knowledge with communities or contribute to wider conversations, this session will help you choose the right publishing pathway.
Dawn Carlisle Research Services Adviser, Student and Scholarly Services, University of Auckland
Dawn Carlisle is a Research Services Adviser in Student and Scholarly Services with expertise in supporting systematic-style reviews. She provides guidance on developing robust search strategies, navigating the publishing process, and understanding open access. Dawn also undertakes contracted literature searches for Health New Zealand and has a particular interest in supporting high-quality, evidence-based research.
Visual abstracts are a 'movie poster' of a journal article displayed on social media that hooks a viewer's attention to read your article. Like a 3-minute thesis is a verbal elevator pitch, a visual abstract is a pictorial summary understood in a 30-second glance. Designed with icons and keywords, they are simpler than a graphical abstract and quicker to make. Visual abstracts are a powerful thinking tool for yourself and a valuable communication tool to engage others. The first half of the session is an interactive exploration of visual abstracts to inspire your imagination. The second half of the session is an introductory level guided workshop to create a basic VA.
Amanda Charlton Hon. Clinical Senior Lecturer, University of Auckland
Amanda is an enthusiastic biomedical educator at the University of Auckland and an Anatomical Pathologist at Auckland Hospital. Amanda is known for her simple, visual approaches to science communication across disciplines.
Peer review is a cornerstone of modern academic publishing practices, but researchers seldom receive any formal training on how to actually do it. This workshop provides an introduction to essential peer review skills, and a template to guide you on your way to producing useful peer reviews. It is aimed at published researchers who have started to receive review requests from journals or colleagues. Attendees will learn about the general peer review process, and how to write fair, constructive, and actionable reviews of others' work. Improving your peer review skills will also improve your own writing skills, and help you to think about your own work from the perspective of a peer reviewer.
This session offers practical guidance for researchers on how to publish strategically and purposefully. Learn how to assess journals for quality and fit, avoid predatory publishers and understand key indicators like peer review, indexing and journal metrics. We’ll share tips for publishing in top-tier journals such as Nature and Science, and explore purpose-driven strategies including Open Access, Indigenous publishing and broader outputs like policy briefs and preprints. Whether you're aiming to advance your career, share knowledge with communities or contribute to wider conversations, this session will help you choose the right publishing pathway.
Maria Dams Research Services Adviser, Student and Scholarly Services, University of Auckland
Maria is a Research Services Adviser in Student and Scholarly Services. She provides research support in scholarly publishing, open access and responsible AI use in literature reviews and publishing.
Wikipedia has become one of the most important free and open sources of knowledge, and it’s impossible to ignore the impact it has had on the internet and society as a whole. Researchers, and in particular doctoral candidates, can gain much from engaging with Wikipedia and its sister projects. This session will introduce Wikipedia and how it relates to the world of research. We will explore how researchers can engage with Wikipedia to increase their impact and boost their research metrics, while improving coverage and representation of topics that interest them. Attendees will learn how to edit existing pages, while following best practices. If you’d like to have a go during the workshop please create an account beforehand (click the ‘Create account’ link at the top right on any Wikipedia page. We recommend choosing an anonymous name, and adding your email so you can recover your account if you lose your password).
Mike Dickison Freelance Wikipedia Consultant,
Mike is a freelance Wikipedia consultant in Christchurch. A former museum curator and moa-bone specialist, he is currently Aotearoa Wikipedian at Large, improving the coverage of Banks Peninsula in Wikipedia, Commons, and Wikidata.
A hands-on introduction to high performance computing (HPC) on a REANNZ supercomputer. Members of the REANNZ training team will guide attendees through HPC fundamentals including software environment modules, scheduler use, profiling, and scaling. Requirements: REANNZ HPC account, details provided after registration and closer to the event. We recommend you attend 'Introduction to the Command Line' or are already familiar with navigating a command line Linux environment
This is a 1 hour workshop designed to help researchers move data securely and efficiently. Participants will be introduced to commonly used data transfer tools—including FileSender and Globus—and learn when and how to use each for different research scenarios. The session covers best practice for transferring or sharing large or sensitive datasets, managing access, and avoiding common pitfalls. Ideal for researchers, postgraduate students, and support staff who work with research data of any size
Vicky Fan Researcher Support Specialist, REANNZ
Prior to joining NeSI, Vicky worked as a bioinformatician at the Bioinformatics Institute at the University of Auckland, and the NETwork! Project, which studied neuroendocrine cancer. When not at work, she can be found at the fencing salle attempting to hit people with a pointy metal stick.
This is a 1 hour workshop designed to help researchers move data securely and efficiently. Participants will be introduced to commonly used data transfer tools—including FileSender and Globus—and learn when and how to use each for different research scenarios. The session covers best practice for transferring or sharing large or sensitive datasets, managing access, and avoiding common pitfalls. Ideal for researchers, postgraduate students, and support staff who work with research data of any size
Chelsea Finnie Senior Network DevOps Engineer, REANNZ
Chelsea is a Senior Network DevOps Engineer at REANNZ who specialises in infrastructure automation, spanning networks, systems, and the platforms that support them. An expert generalist, they enjoy working across disciplines and technologies, focusing on maintainability, clarity, and improving how teams operate complex systems. Chelsea is also an active contributor to the Python community in Aotearoa and Australia.
Finding it challenging to collaborate with other researchers? Do you want to make your research as accessible and reproducible as possible? Google Colab is a hosted Jupyter notebook service that allows anybody to write and execute python code through the browser, while providing access free of charge to computing resources including GPUs. With a robust free tier, no installation or prerequisites, and a tonne of features, Google Colab can undoubtedly help you. This one-hour introductory workshop will demonstrate the most important features of Google Colab. Some UoA-specific topics will also be covered, such as how to mount your Google Drive or Dropbox so you can utilise your datasets and have your results saved automatically. This workshop's final section will showcase examples of how Google Colab is being used for research and education.
Does your data analysis require several steps across various software? Do you need to run the same analysis repeatedly and reproducibly? These common scenarios in digital research can lead to complex manual processes with tedious file handling and a high chance of human error. Workflow languages solve these issues by automating your data analysis with code. They provide reproducibility by ensuring each workflow runs consistently every time. They allow you to organise your software, inputs, outputs and logging for clear versioning, reporting, and results. They are even self documenting, providing a clear illustration of how your whole workflow fits together. Finally they allow you to scale your workflows up for running on HPC such as REANNZ HPC. A well-defined workflow means you can set your full data analysis running and go make a cup of tea knowing you’ll come back to accurate outputs and clear logs. In this workshop, we will work through an introduction to Snakemake, a workflow language with its basis in the popular programming language, Python. This Workshop is intended for anyone who has several steps in their data analysis workflow, particularly when many different software tools are involved. Basic command line experience as provided in "Introduction To the Command Line" is highly recommended, but no other programming experience is required.
Victor Gambarini eResearch Platforms & Services Engineer, University of Auckland
Victor works in the Centre for eResearch as an eResearch Platforms & Services Engineer. He has recently completed his PhD in Biological Sciences at the University of Auckland. Victor has experience with Microbiology, Molecular Biology, and Bioinformatics, focusing on Metagenomics and Metatranscriptomics. At the Centre of eResearch, Victor is developing solutions to automate research projects' management and consult with researchers on the management of research data and computational resources.
Generative AI tools are now ubiquitous, but getting them to produce high-quality, reliable research outputs remains a challenge. If you’ve ever been frustrated by "hallucinations" or generic responses, this session is for you. We move beyond simple "chatting" to explore Prompt Engineering—the science of "programming with words." We will dive into advanced techniques like Chain-of-Thought reasoning and Few-Shot prompting to help you automate literature summaries, debug complex code, and refine manuscript abstracts with scientific precision.
Nidhi Gowdra eResearch Solutions Specialist, University of Auckland
Dr. Nidhi Gowdra is an eResearch Solutions Specialist at the University of Auckland’s Centre for eResearch (CeR). He holds a PhD in Deep Learning with a focus on neural network optimization and has published extensively in premier journals, including Pattern Recognition. A recognized leader in the field, Nidhi served as the Chair of the Machine, Signal, and Image Processing session at the IEEE Industrial Electronics Society Conference (IECON-2020). Beyond his research, he has supervised numerous undergraduate and postgraduate students and currently specializes in helping researchers navigate the complexities of AI. As New Zealand's only NVIDIA-certified instructor, Nidhi is dedicated to making advanced Deep Learning accessible to the broader research community.
Literature reviews are an important part of setting the scene for your research, but it can be time-consuming to find and evaluate large numbers of sources. With the explosion of interest surrounding all things AI, many researchers are wondering how generative AI tools might be applied to reviewing the literature. In this session, we will examine how generative AI tools can be used at different stages in the literature review process. We will explore the capabilities and limitations of some readily available AI tools and discuss how they can support your searches. Finally, we’ll review some important considerations when choosing to use them in the research process.
This 1 hour online workshop explores how researchers can use AI tools responsibly to improve the research process. Attendees will be introduced to how AI tools work, their capabilities and limitations, and the risks of producing incorrect or biased outputs. We’ll explore some examples of how AI can be applied to the research process, and the types of considerations that are important. We'll finish by signposting relevant University policies and where researchers can go for more information.
Dahlia Han Research Services Adviser, Student and Scholarly Services, University of Auckland
Dahlia is a Research Services Adviser in Student and Scholarly Services, with a strong background in supporting the research activities of postgraduate students and staff. Her work focuses on the responsible use of AI in research and literature reviews, as well as helping researchers maintain and optimise their online research profiles. She delivers practical training and guidance to build research skills using a range of research tools and platforms.
This is a 1 hour workshop designed to help researchers move data securely and efficiently. Participants will be introduced to commonly used data transfer tools—including FileSender and Globus—and learn when and how to use each for different research scenarios. The session covers best practice for transferring or sharing large or sensitive datasets, managing access, and avoiding common pitfalls. Ideal for researchers, postgraduate students, and support staff who work with research data of any size
Wes Harrell Research Support Specialist, REANNZ
Wes has been working in HPC and research computing for longer than he cares to admit. Wes worked for a few Unis in the US before moving to Aotearoa and taking up roles at VUW, NeSI and Manaaki Whenua before returning to NeSI (now REANNZ).
Spinning raw data into analysis-ready gold often takes far more time than anticipated. These steps don’t often show up in the methods but are critical for robust research results. Whether you're working with messy survey responses, archival documents, or image collections, transforming unstructured material into clean, structured variables is painstaking work that manual methods handle poorly and traditional programming approaches struggle to scale. Large language models change this. Used programmatically, they can extract structured features from text, interpret images, and produce consistent, usable datasets with more flexibility than rule-based approaches. In this hands-on two-hour workshop, you'll work with real New Zealand text and image data to extract meaningful features using free, cloud-based tools. You'll leave with reusable code you can adapt to your own research data, whatever your discipline. The goal is to demystify programmatic LLM use and give you a practical foundation you can build on immediately. Prerequisites: Basic Python programming experience will greatly assist in participation of this workshop. Set up: As we'll will be using free Google tools, you will be required to use a Google account to participate.
Kyle Hemming Senior Engagement Specialist, University of Auckland
Dr Kyle Hemming is a Senior eResearch Engagement Specialist at the Centre for eResearch (CeR) at Waipapa Taumata Rau | University of Auckland. Kyle proactively engages with researchers across the university community to meet emerging needs in areas such as AI, Python, R, and high-performance computing. With a strong technical background and a decade of experience in quantitative research, coupled with eight years of supporting researchers, Kyle is enthusiastic about enhancing research outcomes. His other areas of interest include supporting reproducible research, strategic planning, and stakeholder engagement.
An overview of research data management requirements, practices, tools and support across the research data lifecycle. Research data or artefatcs are defined as items created, collected or observed in the course of producing original research, regardless of format. This introductory workshop is aimed at researchers, particularly those embarking on their research career or starting a new research project. Attendees will hear about policy, legal and ethical requirements, the FAIR, CARE and Maori Data Sovereignty principles, and develop strategies for data management planning, capturing, organising, sharing, and reusing research data.
REDCap is used by researchers to create surveys or databases to collect and track information and research data, and schedule study events. It is ideal for sensitive research data, including personally identifiable data and consent. It supports different levels of access for collaborators, including from multiple sites and institutions, and tracking of data entry and revision history. REDCap enables online and offline data collection, data sovereignty obligations, and export of data into common software. It is used across the Aotearoa research community, including Universities, CRIs and Te Whatu Ora. Join us to hear about and see a demonstration of how this tool can help your research.
Data Management Plans are a useful way of mapping out the collection, storage, analysis, and publication of research data. They surface important institutional or funder requirements, and ensure that project members are aware of their ethical and legal responsibilities when working with project data. This session will provide an overview of how Data Management Plans are a useful tool for researchers at all stages of their work, and in particular, when revisiting research data over time or onboarding new project members.
Balancing privacy, legal, and ethics requirements with the need to access and analyse sensitive data across a project team can be challenging. This 1‑hour session is for researchers working with sensitive data who want a clear approach to data privacy and security. We will introduce the Five Safes framework (Safe Projects, People, Settings, Data, and Outputs) and demonstrate how these principles are practically applied within a Secure Research Environment. By the end of the session, you’ll have a clearer picture of how you can use secure infrastructure and how recognised approaches like the Five Safes can help meet data providers, funder and overseas partner requirements.
Sarah Hopkins Senior Engagement Specialist, University of Auckland
Sarah Hopkins is a Senior Engagement Specialist at the Centre for eResearch for Waipapa Taumata Rau | University of Auckland. Sarah has a clinical research background in exercise physiology and youth mental health. She is enthusiastic about supporting researchers to navigate the evolving requirements for research data management and to increase digital skills and capabilities to enhance their research.
There's a lot more to NVivo than initially meets the eye! In this webinar we'll be showcasing our favourite features of NVivo including matrix coding queries, explore and comparison diagrams, and mind-maps. This session is perfect for researchers who are new to NVivo, as well as those who are familiar with the basics and curious to know what else is possible.This workshop is recorded.
Reviewing the literature is an important part of the research process. Organising relevant papers and findings are more than just data entry or bibliographic tasks, you also need to be able to analyse and integrate this material with the qualitative data you are gathering. This one-hour demonstration will provide an overview of NVivo’s functionality with regard to literature reviews. Importing and coding literature, running queries on published material, and working with bibliographic data in conjunction with your NVivo project will all be covered. This workshop is recorded.
Lyn Lavery Director, Academic Consulting
Lyn is the director and founder of Academic Consulting where she utilises her extensive experience in both quantitative and qualitative methodologies to assist a diverse range of researchers, including senior academics in leading tertiary institutions, PhD students, and research teams within central government.
Working with personally identifiable information is common across many research disciplines and methodologies, but it comes with important considerations for privacy and data security. This session will provide an overview of the legal, ethical and policy requirements and best practices for working with personally identifiable data. We'll define the elements that can make data personally identifiable and how this is evolving with new technologies. The presenters will explore moving data across the spectrum of identifiable to deidentified to confidentialised, in the NZ context, in order to comply with a broad range of requirements and make it easier to work with the data.
Does your data analysis require several steps across various software? Do you need to run the same analysis repeatedly and reproducibly? These common scenarios in digital research can lead to complex manual processes with tedious file handling and a high chance of human error. Workflow languages solve these issues by automating your data analysis with code. They provide reproducibility by ensuring each workflow runs consistently every time. They allow you to organise your software, inputs, outputs and logging for clear versioning, reporting, and results. They are even self documenting, providing a clear illustration of how your whole workflow fits together. Finally they allow you to scale your workflows up for running on HPC such as REANNZ HPC. A well-defined workflow means you can set your full data analysis running and go make a cup of tea knowing you’ll come back to accurate outputs and clear logs. In this workshop, we will work through an introduction to Snakemake, a workflow language with its basis in the popular programming language, Python. This Workshop is intended for anyone who has several steps in their data analysis workflow, particularly when many different software tools are involved. Basic command line experience as provided in "Introduction To the Command Line" is highly recommended, but no other programming experience is required.
Jean Love Bioinformatician, University of Auckland
Jean is a Bioinformatician at Waipapa Taumata Rau|University of Auckland’s Precision Medicine Initiative. With a background in bioinformatics, cybersecurity software development, and management of sensitive data, Jean provides analysis and QC for clinical and research genomics data and has developed tools and training for handling sensitive research data at the university.
Hear from people who had no prior knowledge or background working in High Performance Computing (HPC) yet today are in roles involving digital approaches to research. Panellists will share stories of what it was like to learn things from scratch, what tips & tricks worked for them, and how they overcame challenges to get to where they are today. Facilitated by the Women in HPC Australasian Chapter (https://tinyurl.com/whpcaunz), this session highlights diverse voices and champions the message that “anyone can be successful in this space”.
Jana Makar Communications Manager, REANNZ
Based in Auckland, Jana Makar is a Communications Manager at REANNZ, where she works to highlight and support the critical role of national-scale eResearch infrastructure in enabling data-intensive research. Prior to joining REANNZ, she worked with multiple organisations in Canada’s cyberinfrastructure sector, from provincial research & education networks to national high performance computing platforms. She sits on the WHPC Australasia Chapter Organising Committee.
Learn about the different capabilities and skills needed for a successful career in academia, tips for planning your career in academia, and what transferable skills academics possess which are relevant outside of academia.
Peer review is a cornerstone of modern academic publishing practices, but researchers seldom receive any formal training on how to actually do it. This workshop provides an introduction to essential peer review skills, and a template to guide you on your way to producing useful peer reviews. It is aimed at published researchers who have started to receive review requests from journals or colleagues. Attendees will learn about the general peer review process, and how to write fair, constructive, and actionable reviews of others' work. Improving your peer review skills will also improve your own writing skills, and help you to think about your own work from the perspective of a peer reviewer.
Julia Mouatt Research Development Manager, University of Auckland
Julia has a background in academia with a PhD in molecular ecology from the University of Copenhagen and a postdoc focusing on population genetics conducted with the U.S. Geological Survey at Oregon State University. After academia she worked as a product manager at the kiwi start-up Publons, which was acquired by Clarivate in 2017, where she was the head of the Web of Science Academy. While at Publons and Clarivate she helped develop online research integrity training courses and practical courses on how to peer review for journals, and set up a global peer review mentoring community built into the Web of Science Academy. In March 2023 she took on the role of researcher development manager at the University of Auckland to support academics in their professional development at all stages of their career.
Emily O'Riordan Lecturer, Victoria University of Wellignton
Emily is a lecturer on the Artificial Intelligence programme at Te Herenga Waka Victoria University of Wellington. Her research focuses on machine learning methods for weather applications, particularly in capturing localised weather phenomena behind extreme weather events. Both AI and weather forecasting are computationally intensive fields, and as such HPC is vital to her research. Emily first encountered HPC during her postdoc, after having done her best to avoid it during her PhD due to fear of it being too complicated! Since then, she’s journeyed from HPC novice to a daily HPC user.
This talk will cover the basics how of longitudinal or repeated data may be captured using a variety of tools within REDCap. We’ll start with an introduction of the underlying data structures, then cover the use of events and repeating forms, and how to export the data in a way that simplifies the analysis to be undertaken.
Olivia Pearson Data Scientist / Data Manager , University of Otago
Olivia has an MSc in Applied Bioinformatics with Genetic Epidemiology from Cardiff University. She works at the University of Otago, Christchurch, where she develops REDCap resources and provides practical support to research teams with database design, build, and testing. She is also the Data Manager for the Christchurch Health and Development Study and a certified Carpentries instructor. Day-to-day she's focused on supporting researchers to strengthen data management practices and build computational skills to support robust and reproducible research.
Interested in learning how to use a suite of open-source tools to create interactive narratives and visualisations for your research? This session provides an overview of a range of free, easy-to-use tools from KnightLab useful for time or location-based narratives. Learn the basics and see how easy and fun it is to create a compelling StoryMap.
Matt Plummer Senior Research Partner, Victoria University of Wellington
Matt's background spans the arts and technology. He works with researchers from different disciplines to facilitate collaborative projects, especially those which utilise technology in innovative and transformative ways. He's assisted with the development of a range of open source projects, augmented reality applications and research tools.
Please note this session is intended primarily for University of Auckland researchers. Administrative data are increasingly used to undertake research because of their considerable volume and variety and ability to be captured automatically, over time, and to be linked. Their use is not without challenges though. In this session, Katrina Poppe, Vanessa Selak, and Mazyar Zarepour draw on their use of New Zealand health care data for research to outline potential data sources, processes for access and data management and curation issues. They will briefly describe the recently established UoA Health Data Platform.
Katrina Poppe Associate Professor, Faculty of Medical and Health Sciences, University of Auckland
Katrina Poppe is a biostatistician and clinical cardiac physiologist with extensive experience in cardiovascular disease from the perspectives of data science, clinical practice, and clinical, epidemiological and methodological research. Health data represents people and must be respected - from how it is collected, to how it is managed and stored, and importantly, how it is understood, analysed and interpreted.
Many early-career researchers find themselves questioning their readiness for professional roles, especially when exploring opportunities beyond a single, clearly defined pathway. Feelings of being behind, underqualified, or unsure where to start are common. This workshop introduces a practical, step-by-step approach to job searching that shifts the focus from vacancy scrolling to employer research and strategic exploration. Career Consultants based in the Unviersity of Auckland will show you how to use LinkedIn to assess role requirements, clarify what “qualified” really means, and prepare for the realities of a professional job search with greater confidence and direction.
Shannon Ring Career Development & Employability Consultant, University of Auckland
Shannon Ring's impressive professional journey includes her notable tenure of 7 years and counting at the University of Auckland, where she has honed her skills and laid the foundation for her successful career. As an alumna of the university, Shannon holds a Conjoint BSc (Biology, Geography) and a BA (Languages), as well as a Postgraduate Diploma in Translation/Interpreting, reflecting her dedication to acquiring a well-rounded education. Drawing on her extensive experience in the industry, Shannon has skilfully engaged in Career Conversations with individuals and groups, helping them navigate the complexities of career development. Her expertise developed from 8+ years working in recruitment agencies, working in-house in aspects of human resources, and recruitment for companies, as well as her background in career counselling and coaching, uniquely positions her to address a wide range of career challenges faced by students and graduates. Across this time Shannon has trained in using LinkedIn, both as a Recruiter – recruiting in Industry, as well as developing her own use to network and create exposure for her own mindset and career purpose coaching company, Clara & Calma. She has secured two roles and three contracts from her work on Linkedin – so is a strong advocate for the use of online networking for professionals and more importantly tertiary students wanting to develop their career paths. She is extremely excited to be able to share her expertise so that those interested, can benefit from her depth of knowledge in the area.
Programming skills are becoming more and more important for researchers to effectively collect, analyse, and translate data into publication-ready insights and figures. But it can be difficult to 'take the plunge' and learn those first steps. This practical, follow-along workshop is aimed at those who are completely new to programming, and introduces the R programming language for data analysis. Participants will learn about the most important concepts for starting with R, including setting up a project in R, basic programming principles, reading in data, summarising and subsetting data, and creating basic plots. We aim to give participants a brief overview of what is possible with R and to inspire them to continue learning. Participants will be expected to follow along and will be provided with set up instructions in advance, which must be completed before the workshop.
Data Management Plans are a useful way of mapping out the collection, storage, analysis, and publication of research data. They surface important institutional or funder requirements, and ensure that project members are aware of their ethical and legal responsibilities when working with project data. This session will provide an overview of how Data Management Plans are a useful tool for researchers at all stages of their work, and in particular, when revisiting research data over time or onboarding new project members.
Maturing from a beginner R programmer to an intermediate-level R developer can be a difficult transition to make. What sorts of concepts should you spend time learning about, and what sorts of practices will help you to level-up your programming game? This 1-hour talk is aimed at researchers who are comfortable with basic R syntax but find themselves overwhelmed by what to do next to improve their scripts. We'll introduce RStudio Projects, managing code history with version control, breaking down scripts into functions, using dependency management tools, and publishing your code repositories to promote your work and give back. Adding these skills and practices to your toolbox will save you time, help you to collaborate more effectively on analyses, and ensure your findings remain reproducible years after publication.
Tom Saunders Engagement Specialist, University of Auckland
Tom is a co-organiser of ResBaz Aotearoa. He works in the Centre for eResearch at the University of Auckland where he coordinates researcher development events by planning, organising, and in some cases teaching digital research skills workshops, as a certified Carpentries instructor. He also consults with researchers on managing research data, administers the University of Auckland's institutional Figshare repository, and publishes the Centre for eResearch's pages on the ResearchHub.
Python is a high-level general purpose programming language that is popular for working with research data owing to an active developer base and wide range of packages that can be leveraged for research. This comprehensive hands-on session will cover the fundamental building blocks of working with Python to analyse and visualize data. Together we'll interactively learn how to use Python to generate a plot from a csv file, getting to grips with the core functionality of the language along the way.
Moving from writing simple Python scripts to managing projects can feel like a leap into the unknown, but adopting a few professional workflows can make your code significantly more robust and maintainable. This 1-hour talk is designed for those who are comfortable with Python basics and are ready to transition from "scripting" to "development." Participants will explore the modern Python ecosystem, focusing on how to use the uv tool for package management and ruff for code formatting and linting. We’ll also cover the essentials of project architecture, the "why" behind type hinting, and how to ensure your code actually works using pytest. The aim is to introduce modern Python tooling and describe a more professional workflow. By the end of the session, you’ll have a clearer roadmap for learning how to better structure your next Python project.
Chris Seal Senior eResearch Solutions Specialist, University of Auckland
Chris is a Senior Solutions Specialist at the University of Auckland's Centre for eResearch, where he leads the development of the University's Instrument Data Service (IDS), which is built using Python. He has an interest in furthering the use of persistent identifiers (PIDs) as a means of connecting different systems together. Because of this interest, he is a member of the I4IOz, an Australasian community of practice developing best-practice guidance for using PIDs for instruments and is on the international advisory board for the newly developed research activity identifier (RAiD).
Please note this session is intended primarily for University of Auckland researchers. Administrative data are increasingly used to undertake research because of their considerable volume and variety and ability to be captured automatically, over time, and to be linked. Their use is not without challenges though. In this session, Katrina Poppe, Vanessa Selak, and Mazyar Zarepour draw on their use of New Zealand health care data for research to outline potential data sources, processes for access and data management and curation issues. They will briefly describe the recently established UoA Health Data Platform.
Vanessa Selak Associate Professor, Faculty of Medical and Health Sciences, University of Auckland
Vanessa Selak is an epidemiologist and Public Health Medicine Specialist with 20 years' health sector experience in clinical, planning, funding, and quality roles. The use of routinely collected health data to improve health outcomes and equity has underpinned Vanessa's academic and health sector roles.
The computational demands of high impact research continue to outpace what individual groups or institutions can realistically support. REANNZ’s Mahuika high performance computing (HPC) platform is designed to help bridge this gap for researchers across Aotearoa. In this talk, we’ll explore the core HPC services REANNZ provides, discuss why HPC might be the right fit for your research, and outline the steps your team can take to gain access to these powerful resources.
A hands-on introduction to high performance computing (HPC) on a REANNZ supercomputer. Members of the REANNZ training team will guide attendees through HPC fundamentals including software environment modules, scheduler use, profiling, and scaling. Requirements: REANNZ HPC account, details provided after registration and closer to the event. We recommend you attend 'Introduction to the Command Line' or are already familiar with navigating a command line Linux environment
Anthony Shaw Research Support Specialist, REANNZ
Research Support Specialist at REANNZ.
International collaboration is the lifeblood of modern research, yet the global landscape is changing. As universities become central to geopolitical strategy, the "open doors" of the past are being replaced by a model of managed openness. For researchers, this shift can feel like a maze of new risks and policies. Using practical examples from the New Zealand and Australasian context, we’ll explore how research security enables safe, responsible collaboration while addressing risks such as foreign interference, talent programmes, and IP leakage. We’ll discuss what researchers can do to protect their work, reputations, and institutions, while still participating in international collaborations that drive high-impact work.
Ben Turley Research Risk and Compliance Manager, University of Auckland
Ben Turley is the Research Risk & Compliance Manager at the University of Auckland. His role involves implementing the New Zealand Government's Trusted Research – Protective Security Requirements (TR-PSR) and managing the university's export control regime. Before joining the University of Auckland, Ben worked as a civilian advisor with the New Zealand Defence Force for 10 years. He has a background in International Relations policy and studied Politics and History at the University of Auckland.
A hands-on introduction to high performance computing (HPC) on a REANNZ supercomputer. Members of the REANNZ training team will guide attendees through HPC fundamentals including software environment modules, scheduler use, profiling, and scaling. Requirements: REANNZ HPC account, details provided after registration and closer to the event. We recommend you attend 'Introduction to the Command Line' or are already familiar with navigating a command line Linux environment
Callum Walley Research Support Specialist, REANNZ
Research Support Analyst at REANNZ, Software Carpentry Instructor.
Are you interested in learning how to investigate reaction mechanisms and transition states of organic and inorganic reactions using computational chemistry? Come and join us for a hands-on, online tutorial where we will learn how to: Run density functional theory (DFT) calculations using ORCA on a high-performance computer (HPC) cluster. Obtain the transition state and activation energy of a chemical reaction using ORCA Use Mahuika OnDemand to view your results directly using Avogadro. Follow [this link](https://geoffreyweal.github.io/ORCA_Mechanism_Procedure/) to know more about what the workshop will cover.
Geoffrey Weal Research Support Specialist, REANNZ
Geoffrey Weal is a Research Support Specialist at REANNZ. Geoffrey completed his PhD in 2021 at Otago University where he specialised in computational chemistry. Geoffrey is an expert in global optimisation algorithms, molecular dynamics, catalytic and CO2 reduction chemistry, solar cell research, and machine learning in chemistry, having conducted postdoc research at Victoria University of Wellington and Kyoto University. Geoffrey is a keen programmer, having learnt to code in Python and C/C++, and is always interested in learning new coding languages for research applications. Geoffrey has experience using various chemistry programs, including Gaussian, ORCA, VASP, CP2K, GROMACS, and LAMMPS. Geoffrey is also passionate about teaching, having taught chemistry in schools around Southland, Otago, Auckland, Malaysia, Taiwan, and Japan.
An overview of research data management requirements, practices, tools and support across the research data lifecycle. Research data or artefatcs are defined as items created, collected or observed in the course of producing original research, regardless of format. This introductory workshop is aimed at researchers, particularly those embarking on their research career or starting a new research project. Attendees will hear about policy, legal and ethical requirements, the FAIR, CARE and Maori Data Sovereignty principles, and develop strategies for data management planning, capturing, organising, sharing, and reusing research data.
Balancing privacy, legal, and ethics requirements with the need to access and analyse sensitive data across a project team can be challenging. This 1‑hour session is for researchers working with sensitive data who want a clear approach to data privacy and security. We will introduce the Five Safes framework (Safe Projects, People, Settings, Data, and Outputs) and demonstrate how these principles are practically applied within a Secure Research Environment. By the end of the session, you’ll have a clearer picture of how you can use secure infrastructure and how recognised approaches like the Five Safes can help meet data providers, funder and overseas partner requirements.
Yvette Wharton eResearch Solutions Lead, University of Auckland
Yvette is the team lead of the Centre for eResearch's Solutions team.
Literature reviews are an important part of setting the scene for your research, but it can be time-consuming to find and evaluate large numbers of sources. With the explosion of interest surrounding all things AI, many researchers are wondering how generative AI tools might be applied to reviewing the literature. In this session, we will examine how generative AI tools can be used at different stages in the literature review process. We will explore the capabilities and limitations of some readily available AI tools and discuss how they can support your searches. Finally, we’ll review some important considerations when choosing to use them in the research process.
This 1 hour online workshop explores how researchers can use AI tools responsibly to improve the research process. Attendees will be introduced to how AI tools work, their capabilities and limitations, and the risks of producing incorrect or biased outputs. We’ll explore some examples of how AI can be applied to the research process, and the types of considerations that are important. We'll finish by signposting relevant University policies and where researchers can go for more information.
Erin Wood Research Services Adviser, Student and Scholarly Services, University of Auckland
Erin is a Research Services Adviser in Student and Scholarly Services. They support researchers with expertise in scholarly communications and AI tools for research, contributing to researcher capability building in ethical and responsible AI use in research and literature reviews.
Many researchers approach statistical analyses with trepidation because they’re unsure about which analyses are appropriate for their data. This hands-on workshop introduces some important background statistical concepts, provides a simple workflow for deciding on which analyses are appropriate based on the kinds of variables you’re working with, and then demonstrates how to conduct these analyses in R. We will apply commonly used statistical analyses such as linear regression, independent-sample t-tests, and chi-squared tests, to R’s built-in datasets. We will discuss the output and how we might present the results for publication. This workshop is aimed at attendees who already understand the basics of working with the R programming language, and who want to learn how to perform statistical tests in R. For an introduction to R for absolute beginners please see ‘Introduction to R & RStudio’ instead.
Lisa Woods Statistical Consultant, Victoria University of Wellington
Dr. Lisa Woods works as a Statistical Consultant at Victoria University of Wellington, providing statistical advice to postgraduate students and academic staff.
Please note this session is intended primarily for University of Auckland researchers. Administrative data are increasingly used to undertake research because of their considerable volume and variety and ability to be captured automatically, over time, and to be linked. Their use is not without challenges though. In this session, Katrina Poppe, Vanessa Selak, and Mazyar Zarepour draw on their use of New Zealand health care data for research to outline potential data sources, processes for access and data management and curation issues. They will briefly describe the recently established UoA Health Data Platform.
Mazyar Zarepour Data Scientist, University of Auckland
Mazyar Zarepour is a Doctoral Candidate in Engineering Science, his research focuses on building data-driven optimisation models to improve healthcare systems. Mazyar is working as a Data Scientist at the Health Data Platform, a service offered by University of Auckland for staff and students. He oversees the data management of the Platform and provides data linkage and cohorting services. His vision is to combine data science and operations research to empower efficient health service delivery.
Open drop-in session to help with troubleshooting, getting help with installing session requirements, and any ResBaz questions. No registration required, just join via Zoom when the session starts.
Are you working with code? Do you wish there was a neater way to keep an old copy of your code around, in case you still needed them? Do you need to collaborate with your colleagues? This workshop is for you! We will introduce Git, a version control system, for tracking changes on your local machine. We will also briefly touch on how to use GitHub as a remote repository. Git keeps track of changes to code and free us from the burden of keeping multiple files with increasingly long and complex filenames. Even though version control systems originated in the world of software development, they're just as useful when working with research projects. You can also connect to a remote repository like GitHub, which allows you to keep a backup of your code and its history, sync across your devices, and have powerful features for collaborating with your colleagues. If you're planning to write any kind of code during your research, it's highly recommended you understand and use version control systems like Git and remote repositories like GitHub to improve the way you work and collaborate (and to make it more enjoyable). This is a beginner-friendly workshop - participants will benefit from having some basic experience with a command-line, but this isn't required.
Noel Zeng eResearch Solutions Specialist, University of Auckland
Noel Zeng is an eResearch Solutions Specialist at the Centre for eResearch, Waipapa Taumata Rau University of Auckland. He received a BSc in Computer Science in 2012. While his main role is in software development, he is passionate about sharing skills and tips for using tools like Python, JavaScript and Git to accelerate your research. He is a certified [Carpentries](https://carpentries.org/) instructor, and hosts [HackyHour](https://uoa-eresearch.github.io/HackyHour/) at University of Auckland, a shared space where students and researchers can get help for and help others with questions around coding and data.
Why are you here? What are you presenting? Who are you presenting to? No, this is not the abstract for “Existentialism with Nietzsche”, it’s “Design 101: Presentations, Posters, and PowerPoints for Researchers”! Have you ever seen a research poster or a PowerPoint presentation that was truly terrible and thought, “Wow, I wonder how I could salvage that? I wonder how I can make research approachable through attractive design?” In this session, we will give you tips on what makes good visual design for research. We will walk you through the do’s (and some don’ts) and what to consider when putting together a visual research presentation, whether a poster, a PowerPoint slideshow, or another type of medium.
Rayna Dewar Research Services Adviser, Student and Scholarly Services, University of Auckland
Rayna Dewar is a Research Services Adviser in Student and Scholarly Services. Her work focuses on providing guidance for those conducting systematic-style reviews and supporting research communication and dissemination needs for early career researchers and doctoral students.
Do you use Jupyter but wish there was an easier way to share notebooks with interactive outputs—for research or teaching—without setting up a server or asking users to install anything? JupyterLite is a WebAssembly-based version of Jupyter that runs entirely in the browser. This 1-hour workshop will show you how to get it up and running on GitHub Pages, walk through a few examples, and finish with Q&A.
Andre Geldenhuis Research DevOps Engineer, REANNZ
Before joining REANNZ, I spent a year at the Center for eResearch at the University of Auckland, where I focused on Trusted Research Environments. Prior to that, I looked after the High-Performance Computing cluster at Victoria University. I hold a Bachelor’s degree in Philosophy and a Master’s degree in Physics from the University of Canterbury, which included a few memorable weeks in Antarctica. Outside of work, I enjoy rock climbing and making LED art, and I occasionally delve into model rocketry, a hobby that combines my interest in physics and electronics.
Python is a high-level general purpose programming language that is popular for working with research data owing to an active developer base and wide range of packages that can be leveraged for research. This comprehensive hands-on session will cover the fundamental building blocks of working with Python to analyse and visualize data. Together we'll interactively learn how to use Python to generate a plot from a csv file, getting to grips with the core functionality of the language along the way.
Are you working with code? Do you wish there was a neater way to keep an old copy of your code around, in case you still needed them? Do you need to collaborate with your colleagues? This workshop is for you! We will introduce Git, a version control system, for tracking changes on your local machine. We will also briefly touch on how to use GitHub as a remote repository. Git keeps track of changes to code and free us from the burden of keeping multiple files with increasingly long and complex filenames. Even though version control systems originated in the world of software development, they're just as useful when working with research projects. You can also connect to a remote repository like GitHub, which allows you to keep a backup of your code and its history, sync across your devices, and have powerful features for collaborating with your colleagues. If you're planning to write any kind of code during your research, it's highly recommended you understand and use version control systems like Git and remote repositories like GitHub to improve the way you work and collaborate (and to make it more enjoyable). This is a beginner-friendly workshop - participants will benefit from having some basic experience with a command-line, but this isn't required.
Maturing from a beginner R programmer to an intermediate-level R developer can be a difficult transition to make. What sorts of concepts should you spend time learning about, and what sorts of practices will help you to level-up your programming game? This 1-hour talk is aimed at researchers who are comfortable with basic R syntax but find themselves overwhelmed by what to do next to improve their scripts. We'll introduce RStudio Projects, managing code history with version control, breaking down scripts into functions, using dependency management tools, and publishing your code repositories to promote your work and give back. Adding these skills and practices to your toolbox will save you time, help you to collaborate more effectively on analyses, and ensure your findings remain reproducible years after publication.
Balancing privacy, legal, and ethics requirements with the need to access and analyse sensitive data across a project team can be challenging. This 1‑hour session is for researchers working with sensitive data who want a clear approach to data privacy and security. We will introduce the Five Safes framework (Safe Projects, People, Settings, Data, and Outputs) and demonstrate how these principles are practically applied within a Secure Research Environment. By the end of the session, you’ll have a clearer picture of how you can use secure infrastructure and how recognised approaches like the Five Safes can help meet data providers, funder and overseas partner requirements.
Toby Johnson Engagement Specialist, University of Auckland
Toby works as an eResearch Engagement Specialist at the Centre for eResearch, Waipapa Taumata Rau University of Auckland. He received his PhD in Psychology from the University of Exeter where he investigated computational models of learning. At the Centre for eResearch he provides digital research and AI skills training and assists researchers in accessing compute resources, including the Secure Research Environments.
Have you got a big paper coming out that you think is newsworthy? The Science Media Centre can help you get journalists’ attention. This session will introduce you to Scimex - our online portal for promoting embargoed research to registered journalists - alongside our other tools and resources for media engagement. You will learn some tips and tricks on what to do when a journalist calls, and how to ensure your expertise has impact.
Daniel Walker Media Advisor, Science Media Centre
Daniel Walker is a media advisor at the Science Media Centre, where he helps journalists and researchers to speak each others' language. He brings years of experience in broadcast journalism, on-air newsreading, and covering breaking news from his previous work at RNZ, Newstalk ZB, and 95bFM. Daniel enjoys translating complex science into something that anyone can understand and feel inspired by.
Developing an R package might seem like a task reserved for software engineers, but a basic data package can be created surprisingly quickly. Packaging up your data is one of the most effective ways for researchers to organise, document, and share their work, and it makes using one dataset across multiple projects much easier. This 1 hour talk is aimed at emerging researchers who want to make their data more accessible and reproducible, and who are comfortable with basic R and committing/pushing to GitHub. Participants will learn why creating packages is so useful, and an overview of how to create a simple data package. The aim is to demystify the process of package development and inspire participants to go on to create their own packages. A collection of step-by-step resources will be provided to help get you started on your package development journey.
Neil Birrell Research Fellow, University of Auckland
Neil Birrell is a Research Fellow at the University of Auckland with a fascination with insects and how people think about them. He is currently working on the ecology and systematics of some of our endemic giant weevils, and the emerging role of insects as food and feed. Neil is particularly interested in why eating insects feels normal in some cultures and confronting in others, and what that says about food, history, and perception.
Many research literatures, across disciplines, are full of findings that cannot be replicated. A major contributor to this “replication crisis” is the use of questionable research practices that inflate statistical significance, meaning that many published findings are not “real”. Preregistration is one solution to this problem. A preregistration is a time-stamped document outlining a study’s hypotheses, sample size, methodology, and analytical plan before data collection begins. It therefore reduces researcher flexibility and increases the credibility of research findings. It is increasingly required or recommended by journals and funders, and is a valuable practice for all researchers. In this practical session I’ll introduce the options for where to post your preregistration and walk through some of the trickier decisions that must be made, including sample size determination, stopping rules, data exclusions, violations of assumptions, and exploratory analyses.
Gina Grimshaw Professor of Psychological Sciences , Victoria University of Wellington
Gina Grimshaw is a Professor of Psychological Sciences at te Herenga Waka – Victoria University of Wellington, where she teaches cognitive science and research methods. She is a strong advocate of open science practices, and is an Associate Editor for Royal Society Open Science. She sits on the Board of the Association for Interdisciplinary Meta-Research and Open Science (AIMOS) and this year will co-host the AIMOS conference at te Herenga Waka in Wellington.