Getting here

John Mahoney , ACU

John is a psychologist by training, with an interest in leadership, coaching, and performance. In his academic role, John teaches into undergraduate and postgraduate courses in the School of Behavioural and Health Sciences. He also has a strong track record of leading learning and teaching projects with a focus on student engagement and learning. His passion, however, is to support academics in using highest-level evidence to inform their learning and teaching practices. Along with three colleagues, he established INSPIRE, which aligns closely with his passion. He continues to grow INSPIRE and scale it, as well as work on other learning and teaching projects aimed at providing high-quality student experiences.

Key Story - Inspiring students and giving them the tools they need to thrive at Uni

Jelena Nikolic Chief Digital Officer, QLD Department of Tourism and Sport

Jelena leads the Digital Services team at the Department of Tourism and Sport, which provides oversight of all ICT delivery across the department, including the strategic digital agenda, provision of advice, guidance and support of key technology and digital initiatives, digital governance frameworks, and information management and security to advance the department's digital priorities.

Key Story

Dr Aaron Snoswell Senior Research Fellow, Generative AI Lab (QUT)

Dr Aaron Snoswell is a computer scientist and senior research fellow in AI accountability at the QUT Generative AI Lab. Aaron’s research uses computational and socio-technical approaches to investigate the cultural and social impacts of Generative AI. Past and ongoing projects include the development of measurement and mitigation frameworks for toxicity in Large Language Models (LLMs); co-designing appropriate industry and policy responses to Generative AI’s rapid integration across society; using Explainable AI methodologies and moral philosophy frameworks to understand how logical and moral reasoning processes work (or don’t) in Generative AI language agents; and studying the socio and cultural well-being implications of companion chat-bots and “virtual influencers”.

Key Story - The Pro-social Ranking Challenge: reflections from a large-scale project translating AI research into practice

In 2024, the QUT Generative AI Lab, along with colleagues from the QUT Digital Media Research Centre (DMRC) and ARC Centre for Excellence in Automated Decision Making and Society (ADM+S) participated in the Pro-Social Ranking Challenge. Hosted by the Centre for Human-Compatible AI (CHAI) at UC Berkeley, this competition charged teams with re-designing social media feed algorithms, based on cutting edge science about wellbeing, and the latest AI technology advances. Our submission, which was selected as a finalist entry but not one of the winners, focused on reducing political polarization through a combination of interventions, utilising multiple 'off the shelf' and custom AI models. This short talk will share reflections from this international research collaboration, as well as lessons learned from translating an AI-centric research idea into a production quality software system over the course of a nine-month international collaboration.

A gentle introduction to stable diffusion and generative text-to-image models

In this hands-on workshop, participants will learn more than they ever wanted to know about how generative text-to-image models work. Come and look 'under-the-hood' of DALL-E, MidJourney, Stable Diffusion, and other similar systems as you work through a series of interactive python Jupyter notebooks to deconstruct then re-construct a diffusion model from scratch. By the end of the workshop, you will understand the components that go into making a contemporary GenAI image generator, be equipped to critique and study these socio-technical systems, and will hopefully have had some fun interrogating and interacting with all of the technological 'ingredients' along the way.

Some familiarity with python and/or Jupyter notebook is recommended for participants. Participants are strongly encouraged to bring their own laptop to work through the activities on the day. Optionally, participants can get started with the notebooks early by browsing to this page, under the heading 'A Gentle Introduction to Stable Diffusion'.

Allison Bambrick Executive Director, Science Development and Office of the Queensland Chief Scientist

Key Story - Queensland initiatives for science

Prof. Kerrie Mengersen Professor of Statistics, QUT

Kerrie Mengersen holds a BA (Hons) in Mathematical Statistics and Computing and a PhD in Mathematical Statistics, both from the University of New England, NSW Australia. She has held positions as a commercial statistical consultant and an academic staff member at four Australian Universities. She is currently a Distinguished Research Professor in Statistical Science and the Director of the QUT Centre for Data Science at QUT, and holds a concurrent role as Associate Member in the Department of Statistics at the University of Oxford, UK. She was a Deputy Director in the ARC Centre of Excellence in Mathematical and Statistical Frontiers (2015-2021) and an ARC Laureate Fellow (2015-2021). In 2018 she was elected as a Fellow of the Australian Academy of Science (AAS), the Academy of Social Sciences in Australia (ASSA) and the Queensland Academy of Arts and Sciences (QAAS). She is an active member of the Institute for Mathematical Sciences, International Biometrics Society, International Statistical Institute and the Statistical Society of Australia.
Research Distinguished Professor Mengersen focuses on using and developing new statistical and computational methods that can help to solve complex problems in the real world. These problems are in the fields of environment, genetics, health and medicine, and industry. She enjoys working with a diverse range of people doing outstanding things in many different areas, and contributing expertise in an important component of their work.

Key Story

Dr Tapani Rinta-Kahila ARC DECRA Fellow, UQ School of Business

Dr Tapani Rinta-Kahila is a Lecturer of Business Information Systems and an ARC DECRA Fellow at The University of Queensland Business School. He holds a doctoral degree from Aalto University School of Business, where he wrote an award-winning dissertation on the decommissioning of organisational information systems. His research focuses on issues around the implementation and management of artificial intelligence (AI) systems in organisations, unintended consequences of technology use, and replacement of organisational information systems (IS). In particular, Tapani strives to understand how contemporary technologies such as AI affect the way in which people learn, work and organise, and how the negative consequences of such technologies can be managed.

Key Story - Artificial Intelligence and the Future of Our Skills

Sharron Stapleton Research Library Specialist, Griffith University

Sharron is a Research Library Specialist at Griffith Library providing training and advice to researchers on finding external data and primary sources for research and preparing data for analysis, visualisation and publishing. Sharron is a certified Data Carpentry instructor, a strong supporter of open research for societal benefit and is regularly involved in ResBaz as a trainer.

Introduction to data cleaning with OpenRefine

Learn basic data cleaning techniques in this hands-on workshop, working with structured text data and using open source software OpenRefine.
You will need a laptop with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.) that you have administrative privileges on.

Dr Sam Hames Research Fellow, UQ

Dr. Sam Hames is a research fellow in computational humanities with UQ's School of Languages and Cultures and also works on the Language Data Commons of Australia and the Australian Text Analytics Platform. Sam's PhD was on machine learning for medical imaging analysis, and he has an extensive background as a data-focused software developer supporting social media and web researchers. His primary research focus is to understand how computation can enable qualitative and interpretive inquiry across the humanities and social sciences.

Text Analytics part 1: Introduction to R for Text Analysis

Are you looking to improve your text analysis skills using R? This introductory session will focus on setting up efficient workflows for analysing language data in R and RStudio. The workshop is ideal for participants with basic R skills who want to explore how R can be applied to text analysis. In this hands-on session, you will learn:

How to properly configure R and RStudio for text analysis projects
Techniques for loading, cleaning, and processing language data in R
How to generate concordances (keyword-in-context displays) to better understand word usage in context
Methods for extracting collocations and identifying keywords in your dataset

This session will focus on best practices and optimal workflows, helping you work more efficiently and accurately when processing language data. Whether you're a linguist, social scientist, or researcher in the humanities, this workshop will give you the skills to get the most out of your data analysis in R.

Text Analytics part 2: Interactive Text Analysis with LADAL Tools

Not familiar with R but still want to dive into text analysis? In this second part of the workshop, we’ll introduce LADAL Tools, a suite of interactive notebooks designed to make text analysis accessible to researchers of all levels, allowing you to perform complex analyses without needing to code. During this session, we will:

Demonstrate how to upload and clean your own language data using LADAL Tools
Guide you through concordancing and keyword extraction to better understand patterns in your text
Showcase advanced text analysis techniques such as topic modelling and network analysis
Provide hands-on examples and real-time demonstrations to ensure you can follow along, even without coding experience

Whether you’re a linguist, researcher, or academic from the humanities, social sciences, or related fields, this session will equip you with practical tools to enhance your text analysis without the steep learning curve of programming. You'll leave the workshop ready to apply LADAL’s easy-to-use tools to your own research data. For more information on LADAL Tools, visit the LADAL website.

Karen Cavu Research Fellow, QUT

Karen Cavu is a certified career coach with 15 years experience in higher education, specializing in career development support for emerging and early career researchers. With a background in HR consulting, recruitment, training and business development for over a decade, Karen understands how to navigate the recruitment landscape and translate research skills into job-ready jargon. Karen is currently the HDR Career Educator at QUT and sessional academic for QUT's postgraduate career counselling units.

Personal Branding for Researchers (and the branding-averse)

Craft a compelling personal brand as a research, content and technical expert in your field that doesn't leave you feeling like a snake-oil salesman. Investigate the why, how, where and when of branding opportunities, and get comfortable with the uncomfortable reality that you are the brand manager of your own career. The perfect workshop for any introverted, socially-awkward, branding-averse researcher who needs tips on how to successfully promote their career without selling their soul.

ChattieG Cheats to Optimise your Research Resume

Leverage your favourite AI platform to: review job advertisements efficiently; assess your skills against a vacancy; unpack unknown assumptions about your skills; and translate your skills into job-ready jargon. This workshop is ideal if you struggle to define, evidence, or translate your academic research into industry terminology, or if you're exhausted by the prospect of relentlessly re-writing job applications. Learn the best cheats with ChattieG!

Dr Jenna Wraith Senior Data Scientist, QCIF

Jenna is a Conservation Scientist with expertise in ecological modelling, species distribution, and biodiversity data analysis to support policy and conservation efforts. As the Senior Data Scientist at QCIF for EcoCommons, she oversees the development of the collaborative platform that enables researchers to build, share, and apply advanced ecological models.

Using the EcoCommons platform to run species distribution models

EcoCommons Australia offers a comprehensive suite of resources for ecological modelling. This includes a user-friendly platform with thousands of trusted datasets and a range of expert-developed species distribution and community modelling workflows. This workshop will begin with a brief introduction to species distribution models (SDMs), followed by a guided tour of the EcoCommons platform. Attendees will learn how to run effective SDMs, select fit-for-purpose data, and produce accurate and meaningful results in a point-and-click environment.

Yolante Jones Senior Data Access Management Officer, ANU - Australia Data Archive

Yolante is the Senior Data Access Management Officer at the Australian Data Archive. She reviews applications for access to some Australia's most sensitive (& valuable) social science datasets. Before this role she was the Community Coordinator for the CADRE project and developed learning materials for the Five Safes conceptual framework. She is passionate about data management and ensuring best practices are upheld by all.

A New Tool for Managing Access to Sensitive Research Data

By attending this workshop, you will learn
- About facilitating access to sensitive data at the Australian Data Archive
- How to use the CADRE (Coordinated Access for Data, Research & Environments) platform
- Key considerations for developing your own data sharing arrangements

Robert Fleet Senior Data Scientist, QUT Digital Observatory

Robert Fleet is a senior data scientist at the QUT Digital Observatory, where he spearheads the development of innovative research software and cutting-edge methodologies for digital and computational research. With a keen focus on advancing the field, Robert is currently immersed in creating Large Language Model (LLM) pipelines for data analysis and exploring topic models that evolve over time.

Qualitative Data Analysis using AI (Booked out)

The workshop will cover the use of LLM to process data qualitatively as well as perform extractive reasoning on the data. LLM Summarisation of data and outputs is also discussed. The objective of the workshop is to demonstrate the usefulness of LLM to accelerate research outputs and discovery when working with research data. We will discuss the benefits and limitations as well as the considerations that need to be made with data and data processing. There will be a practical demonstration of the processing of some data drawn from various sources such as Reddit, YouTube and NewsTalk.

Demystifying AI for Research (Booked out)

This workshop aims to raise awareness of the potential for AI to accelerate and enhance research outputs for the current research milieu. AI is now a fact of life for research and is being increasingly used by students at both undergraduate and post graduate level. This workshop will cover the newest developments in AI and introduce what AI means for research and how researchers can be prepared for it. The workshop will also cover what researchers need to ask for from research infrastructure at their institution. We will try to present a balanced view of both sides of the arguments for and against the use of AI in research. The format will be informal and will encourage discussion.

Running an AI locally: Can it be done?

This workshop aims to demonstrate how a small open LLM can be run locally to automate small, simple tasks locally without the need to use of commercial models. This is a very recent development in the AI space and therefore might be considered an advanced topic for many users. The workshop will assume some intermediate level of coding and will be based in notebooks for ease of hardware specs. The workshop will cover the basic set up and a discussion of the types of models that will work and where to acquire them. Then a simple workflow will be described. Attendees may bring their own data and the notebooks can be provided as long as the attendee can confidently use them on their hardware and coding environment.

Addison Suhr Research Data Analyst, QUT Digital Observatory

Research Data Analyst for the Digital Observatory

Ethics Advisor: AI & RAG for discussion & advice based on ethics guides

Discussion, demonstration, and implementation of RAG (Retrieval Augmented Generation) as an approach for exploring large and complex data sources

Cameron West Technology Trainer, UQ Library

Cameron is a technology trainer at UQ Library. He helps run the Python User Group, enjoys assisting others with programming and is also studying his honours year. The technology training team also facilitate the R User Group (RUG), deliver hands-on programming and software training and offer one-on-one consultations.

Collaborative User Groups: Could you start one? Come join ours!

Programmers are advised to debug their code by explaining it, line by line, to a rubber duck*. In fact, one of the best ways to troubleshoot your data/research/programming woes is to talk about them. User groups - i.e., communities of practice - offer a collaborative space for researchers to share, discuss and learn about the tools they use. Join us for a live user group - all programming languages welcome! Most of the session will be a drop-in space for any data/programming questions you have (we're teaming up with UQ's usual Python User Group) but we'll also include a discussion on how user groups work, what they take and approaches for starting them.
*Hunt, Andrew; Thomas, David (1999). The Pragmatic Programmer - From Journeyman to Master

Lucena Miranda , Griffith University

Lucena Miranda is a secondary school teacher from the Philippines who completed her master’s degree at the University of Queensland. She is now a post-confirmation PhD student at Griffith University, researching inclusion approaches to overcome multiple disadvantages in high school. As a non-native English speaker and a mother, her skills in using various technological tools and collaborating in diverse environments have enabled her to co-publish articles and manage book publication projects, at the early stage of her PhD journey, both inside and outside academia.

Using Leximancer and Obsidian

This presentation will explore the PhD student’s use of tools to prepare for her confirmation (Obsidian) and to analyse textual data (Leximancer), which led to the publication of an article. Participants will gain valuable insights into the use of these tools and how they facilitated a successful research collaboration with her research supervisor and other academics outside the university.

Udita Gupta , QUT

Udita Gupta is a research student at the THRIVEIAQ program hosted at the Queensland University of Technology. Her research focuses on improving indoor air quality in highly occupied buildings. She is passionate about research methodologies, contributing to advance existing knowledge and learning about different research.

Academic Writing Tips and Skills (without AI)

The researchers face lot of trouble in writing their ideas. I would like to share my learnings and tips on how to properly and systematically write, how to structure the ideas, common mistakes and how to avoid them. This workshop will focus on writing skills without using any AI tools because at the end, academic writing has to be original and human created.

Dr Emily Kahl Supercomputing Applications Specialist, Pawsey Supercomputing Center

Dr Emily Kahl is a Supercomputing Applications Specialist at the Pawsey Supercomputing Centre, and is based remotely in Brisbane. Emily develops and maintains software for molecular simulation, with a specific focus on GPU-accelerated computing and machine learning methods in quantum chemistry. She has extensive experience developing and supporting software for computational chemistry and molecular modeling and has contributed to multiple open-source molecular dynamics projects. She is also an advocate for open-source software in computational science, and the code she has developed for atomic and molecular simulation has seen widespread use by Australian and international researchers. Prior to joining Pawsey, Emily completed her PhD in physics at the University of New South Wales and worked as a research software engineer at the University of Queensland.

Make your code go fast, fast

Make your code go fast, fast - practical performance engineering for research software.

Whether you're running massively-parallel computer simulations or processing huge amounts of research data, research software across all domains increasingly requires the use of large-scale data and computational resources. As a result, it's becoming increasingly important to be able to write fast, well-optimised code to ensure efficient use of computational resources such as high-performance computing clusters, as well as improved turnaround time on research outcomes. Simply put, time spent waiting for code to run is time not spent doing research.

Squeezing every available bit of performance out of your code can be extremely time-consuming, but fortunately you can go a long way with just a little bit of programming know-how applied in the right places. This talk will provide an introduction to performance engineering, with a focus on practical, well-tested techniques for both compute- and data-heavy workflows. I will discuss methodologies and open-source tools which will help you get the most 'bang for your buck' when optimising slow code in your research pipelines.

Joanna Salerno Data Scientist, QCIF

As a Data Scientist at QCIF, I provide comprehensive support across QCIF’s research projects. I work closely with researchers to understand their project needs so that I can provide tailored support to advance their work. I also deliver workshops designed to help researchers upskill in areas such as programming, statistical analysis, data management, and research communication.

Data capture and form design using REDCap

This workshop will guide participants through the stages of the data capture process, from establishing the requirement, through field selection, form logic, and deployment. Participants will have an opportunity to follow along practical exercises to cement their understanding of the theory presented, using REDCap as an exemplary tool. Participant log-in details for the REDCap training environment will be provided on the day.

Data analysis and form design using REDCap

This workshop continues from the earlier data capture session, to evaluate the consequences of form design and field selection on data formats, consistency and ease of analysis. Participants will have an opportunity to follow along practical exercises to cement their understanding of the theory presented, using REDCap as an exemplary tool. Participant log-in details for the REDCap training environment will be provided on the day.

Dr Awais Hameed Khan , UQ

I am a designer / technology researcher / illustrator / (reluctant) academic / (recovering) marketer — with over a decade of experience working across emerging technologies, telecommunications, consumer goods, and design consulting sectors. I am interested in the human and social aspects of designing technology, in collaboration with users. I enjoy working on human-computer interaction projects, developing participatory design tools and methods, design fictions, and using speculative approaches in my work.

How to design 'design methods' to support participation in research

In this design methods workshop, learn about the basics of how to create participatory design methods, tools, and techniques. We will explore what considerations are important to creatively scaffold participation in collaborative research settings. The workshop will cover practical strategies to design ‘design methods’, importance of materiality and staging, as well as how reformatting outcomes can create meaningful value.

William Pinzon Perez , QCIF

After working with QCIF as a casual biostatistics training instructor for three years, William joined QCIF full-time in late March 2022 as a Gold Coast-based Junior Statistician. As a fully certified The Carpentries instructor, William will continue to assist QCIF with its training program for researchers, including providing and developing training materials. He will also work across all of QCIF’s biostatistics clinics for its Members, and on any QCIF projects requiring his expertise.

Statistical Comparisons in R

This practical workshop will help participants to choose and use the appropriate standard statistical test for their data by introducing key concepts of inferential statistics in R. Participants will learn how to compute and interpret hypothesis tests for popular statistical models such as correlation, contingency tables, chi-square test, t-test and ANOVA.

Dr Ade Adeyinka , QCIF

Ade is a casual trainer with QCIF. Previously, he was the digital research analyst at Southern Cross University (SCU) and the University of Southern Queensland (UniSQ). He specializes in the application of quantitative and qualitative techniques in proffering solutions to financial, social and management problems. His PhD thesis was on the application of weather index-insurance in managing drought risks among Australian farmers.

Statistical Comparisons in R

Analysing Categorical Outcomes and Logistic Regression

This practical half-day workshop will help participants to develop an understanding of the principles, methods, and interpretation of logistic regression, a statistical technique to generate binary (yes/no) outcomes from complex input data. The course will cover the principles of logistic regression and includes practical sessions getting hands-on experience of logistic regression in R.

R Shiny essentials: from data to interactive dashboards

R Shiny is a popular R package that allows you to transform complex analytics into powerful, user-friendly interactive visualisation tools.
In this workshop we will provide an introduction to R Shiny, and how you can use it to create web apps, and more interactive data visualisations.
We will go over how to build a basic Shiny application, and cover the best practices and resources when approaching Shiny.

Kaitlin Moat , UQ

Introduction to programming: Plotting and Programming with Python

Participants will learn about basic programming concepts including simple and complex data types, conditionals and looping that are applicable to Python and other languages. This workshop will prepare participants to carry out batch analysis and equip them with the knowledge to start creating automated pipelines to increase data processing power and productivity.

Dr Tony Howes Honorary Associate Professor, UQ

Introduction to programming: Plotting and Programming with Python

Dr Martin Schweinberger Lecturer in Applied Linguistics, UQ

Dr Martin Schweinberger is Lecturer in Applied Linguistics in the School of Language and Cultures at the University of Queensland (UQ). Martin has specialized in computational approaches to analysing language data with a focus on corpus linguistics and quantitative analyses. His research interests lie in language variation and change, language use and acquisition, and reproducibility in the language sciences. Martin is co-director of the Language Technology and Data Analysis Laboratory (LADAL), board member of the International Computer Archive of Modern and Medieval English (ICAME), Vice-President Profession of the International Society for the Linguistics of English (ISLE), as well as CI at the Language Data Commons of Australia (LDaCA) and the Australian Text Analytics Platform (ATAP).

Text Analytics part 1: Introduction to R for Text Analysis

How to properly configure R and RStudio for text analysis projects
Techniques for loading, cleaning, and processing language data in R
How to generate concordances (keyword-in-context displays) to better understand word usage in context
Methods for extracting collocations and identifying keywords in your dataset

Text Analytics part 2: Interactive Text Analysis with LADAL Tools

Demonstrate how to upload and clean your own language data using LADAL Tools
Guide you through concordancing and keyword extraction to better understand patterns in your text
Showcase advanced text analysis techniques such as topic modelling and network analysis
Provide hands-on examples and real-time demonstrations to ensure you can follow along, even without coding experience

Dr Sara King Training and Engagement Lead, AARNET

Dr Sara King is the Training and Engagement Lead for AARNet and a member of the engagement team for the Language Data Commons of Australia. She is focused on outreach within the research sector, developing communities of interest around training, outreach and skills development in eResearch. She is passionate about helping others develop the infrastructure and digital literacies required for working in a data-driven world, translating technology so it is accessible to everyone.

Network Know-how: A Practical Workshop on Digital Research Infrastructure

Do networks and data feel like a foreign language? We’re here to help. In this hands-on workshop, we’ll break down the jargon and explore key topics like network basics, data movement, and tools to streamline your research.

Join us for a fun exploration of the digital world where you’ll learn how to master the art of network tech, manage active research data, and transfer even the largest files with ease. By the end of this workshop, you’ll walk away with practical skills and the confidence to tackle complex internet and data challenges like a pro:

Understand different internet connections in Australia and how to make the most of them.
Learn key network terms and concepts.
Run tests to check and improve your connection.
Calculate data transfer times and move large files efficiently.
Troubleshoot network challenges and find the best tools for data movement.

Boost your research toolkit and navigate networks with confidence!

Stéphane Guillou Technology Trainer, UQ Library

Stéphane is a technology trainer at the UQ Library, promoting Open Research practices and teaching about Open Source tools for scripting, data analysis, data visualisation and authoring. Before then, he worked in plant science research and studied botany and ecology.

Introduction to geospatial data with R

In this Data Carpentry workshop, learn how to import, work with, and plot vector and raster-format spatial data in R. The workshop also touches on spatial metadata (extent and coordinate reference systems), reprojecting spatial data, and working with raster time series data.

This workshop expects attendees to have used R, dplyr and ggplot2 before.

Justin Scott Biostatistician, QCIF

Introduction to programming: Plotting and Programming with Python

Nicholas Maitigian Biostatistician and Bioinformatician, QCIF

Nicholas (Nicko) is a data analyst (Biostatistician and Bioinformatician). He has 20 years’ experience in analysing high-throughput genomic data, including gene expression, methylation, metagenomics, high-throughput mass spectrometry protein profiling, next-generation sequencing data, single-cell and spatial transcriptomics.

Statistical Comparisons in R

Rhetta Chappell Data Scientist & Partnerships Lead, RIDL/GDT (Griffith University)

Rhetta Chappell is the Data Science and Partnerships Lead at Griffith University’s Relational Insights Data Lab (RIDL). In this role she leads a growing team of high-performing data analysts and provides strategic direction on complex, mission and data-driven projects for industry, government, and academic partners. Her role as a speaker at the Royal Statistical Society Conference in Scotland highlights her standing in the field. Rhetta’s work is not just about data analysis; it’s about creating sustainable, impactful solutions aligned with global initiatives like the UN’s Sustainable Development Goals.

Moving from insight to influence and impact: the power of data communication

This workhsop will cover:

Introduction to the Relational Insights Data Lab (RIDL) and the Griffith Data Trust (GDT)
What is impact reporting?
2 case studies
How to communicate and visualise impact - mistakes and lessons learned
Q & A panel with RIDL data analysts and data scientists
How to make your data matter

Heather Monro-Allison Librarian, Griffith University

Introduction to data cleaning with OpenRefine

Mark Hoffman Senior Health Informatician, QCIF

As a Senior Health Informatician at QCIF, I support researchers with sensitive data management and planning, as well as REDCap project design and deployment. I am also one of the Platform Managers for KeyPoint, QCIF’s purpose build Trusted Research Environment, which facilitates the secure sharing and analysis of sensitive data by Data Stewards to approved Researchers. Prior to joining QCIF I was a data manager at a non-profit health research organisation, working with analysist, managers and researchers to transform routinely collected health record data into positive research and public policy outcomes.

Data capture and form design using REDCap

Data analysis and form design using REDCap

Peter Marendy Head of Data Services, Queensland Cyber Infrastructure Foundation (QCIF), RSE-AUNZ

Peter is currently employed as Head of Data and Software Solutions at the Queensland Cyber Infrastructure Foundation (QCIF), which provides eResearch infrastructure and services for Queensland research institutions and contributes to the National Research Infrastructure.

In this role, Peter is responsible for leading a team that delivers innovative, high quality, and time driven results for a wide variety of research programs from within universities, research institutes, and commercial companies. The team has expertise in workflows, specialised computing, data capture and management, and working with sensitive data.

Prior to his role with QCIF, Peter led the Microsystems research within CSIRO’s Cybernetics research Group. During his time at CSIRO, Peter also led projects such as Bees with Backpacks, Optimising Pollination, Smart Hives, Probing Biosystems – Implantables, Brain Implants, and Smart Helmets for optimising the timing of Cranioplasty.

Peter is also a member of the RSE-AUNZ steering committee which aims to build awareness of the diverse Research Software Engineer (RSE) roles, to connect volunteers in the RSE domain, and to help build practical solutions for the RSE Community.

Peter brings his experience in team/capability management, project management, and customer focused collaboration and relationships. A people focused leader with broad knowledge across multiple domains with a focus on cutting edge development and applications. An excellent technology communicator to the public, academia, government, grant bodies, and industrial stakeholders.

He also has more than 20 years of software engineering experience across multiple domains, including Digital Agriculture, Energy, Food and Nutritional Sciences, Health, Marine Sensing, Robotics, and Visual Analytics, in research and innovation environments.

Using KeyPoint for Sensitive Data

Sensitive data is increasingly common in research, including in fields as disparate as population health, biosecurity, food-security and agriculture, environmental science and biodiversity, defence, humanities, Indigenous studies, and social science. All involve the production, use, analysis, and management of sensitive data. To unlock the full potential of data sets in such sectors, researchers need secure and trusted digital environments allowing them to hold sensitive data they produce or receive from third parties (e.g., government and industry) and/or collaborate at scale on sensitive data whilst always ensuring the security of that data.

QCIF, in conjunction with ARDC and The University of Queensland, has developed a purpose-built trusted research environment named KeyPoint.

This session will explore the governance model of KeyPoint, how we ensure strict project separation at the desktop, and finishes with a live demonstration of the platform.

BoF: Charting a path towards a sustainable community of people who work on Research Software

Please join us to raise awareness across Queensland of the community of people who work on Research Software, the Research Software Engineer Australia New Zealand (RSE-AUNZ) community, and to understand the needs of the community.

This BoF would be of interest to people who:

Develop research software and are worried about career progression,
Want to make the research software more visible,
Streamline and scale research workflows but feel undervalued,
Balance researcher needs with good software practices, and
Make research software easier to use.

It would also be useful to those who manage RSEs or who struggle to recruit or maintain RSEs within their project lifecycles, and those who would like to help sustain this community.

Objectives would be to solicit feedback and discussion about the following topics :

What are the needs of the community and is the RSE-AUNZ meeting those needs?
What can we do to get more active community participation? Eg. proactively sharing knowledge, joining the steering committee, or asking for help?
How can we ensure greater equity and inclusion within the RSE-AUNZ community to better support and represent all members?

Abhimanyu (Raj) Singh Data Ecologist, QCIF

Using the EcoCommons platform to run species distribution models

Xiang Zhao Software Developer and R Specialist, QCIF

Using the EcoCommons platform to run species distribution models

Dr Andrew Jones Senior Biostatistician, QCIF

How to get to Resbaz?

Getting to campus

Public transport

Cycling

Driving and parking

At campus?