Learn about the fundamental concepts in programming using Python and apply them to analyse a sample research dataset.
Programming is becoming more and more popular, with many researchers using programming to perform data cleaning, data manipulation, data analytics, as well as creating publication quality plots. Programming can be really beneficial for automating processes and workflows. In this presentation, we are exploring four of the most popular programming languages that are widely used in academia, namely Python, R, MATLAB, and Julia.
Explore DataFrames in-depth and learn about Data Manipulation in Python using the Pandas library.
Learn about Data Visualisation in Python using the Matplotlib and seaborn libraries.
Jianzhou Zhao Intersect
Dr Jianzhou Zhao is an eResearch Training Specialist, planning and delivering Intersect's training program for its members and partners. Jianzhou works collaboratively with universities help guide the development and deployment of relevant eResearch services; and, increase the visibility and acceptance of good eResearch practice across all areas. Jianzhou holds a PhD in Photovoltaics and Renewable Energy Engineering.
Learn about the fundamental concepts in programming using Python and apply them to analyse a sample research dataset.
Explore DataFrames in-depth and learn about Data Manipulation in Python using the Pandas library.
Learn about Data Visualisation in Python using the Matplotlib and seaborn libraries.
Andrew Goh Intersect
Learn about the fundamental concepts in programming using R and apply them to analyse a sample research dataset.
Learn about Data Manipulation and Data Transformation in R using the dplyr and tidyr packages.
Learn about Data Visualisation in R using ggplot2, one of the most popular plotting packages.
Belinda Fabian Macquarie University
Belinda is a Project Officer for the ARC Centre of Excellence in Synthetic Biology and a PhD candidate at Macquarie University. Her research uses high-throughput genomics techniques to study beneficial bacteria that colonise plant roots. Belinda is certified Carpentries Instructor, an Advance HE Fellow, and is passionate about equipping students with useful skills for the workforce.
Learn about the fundamental concepts in programming using R and apply them to analyse a sample research dataset.
Learn about Data Manipulation and Data Transformation in R using the dplyr and tidyr packages.
Learn about Data Visualisation in R using ggplot2, one of the most popular plotting packages.
Marium Afzal Khan Intersect
Marium Afzal Khan is the eResearch Analyst from Intersect at the University of Adelaide. She has over 7 years of experience incorporating technology and data analytics across multiple industries including education, health, governance and research. Marium has a background in computer science with a Masters in Educational Technology.
Learn about the fundamental concepts in programming using R and apply them to analyse a sample research dataset.
Learn about Data Manipulation and Data Transformation in R using the dplyr and tidyr packages.
Learn about Data Visualisation in R using ggplot2, one of the most popular plotting packages.
Jerry Lai Intersect
Learn about the CloudStor interface and its associated tools and services for managing research data, including SWAN, a cloud service for interactive data analysis using Jupyter Notebooks.
Sara King AARNet
Dr Sara King is the Training and Engagement Lead for AARNet. She is focused on outreach within the research sector, developing communities of interest around training, outreach and skills development in eResearch. She is currently working on creating reusable guidance information for Jupyter Notebooks and other AARNet services. 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.
Learn about building an electronic data capture form, enabling survey settings, simple longitudinal project setup and access provisions
Needing to collect data from people in a structured and intuitive way? Have you thought about using Qualtrics? Qualtrics in a powerful cloud-based survey tool, ideal for social scientists from all disciplines. This course will introduce the technical components of the whole research workflow from building a survey to analysing the results using Qualtrics. We will discover the numerous design elements available in order to get the most useful results and make life as easy as can be for your respondents. If your institution has a licence to Qualtrics, then this course is right for you.
This presentation will demonstrate a number of in-flight research projects using an extensive REDCap feature set, such as randomisation, advanced reporting (e.g., enrolment tracking) and automated notifications via email and SMS. It will be a great opportunity to be inspired by a range of advanced REDCap features that enable real-life research projects.
David Jung UNSW
David Jung is Research Data Support Officer at the UNSW Sydney. He supports researchers navigate the policies, guidelines, and technologies in managing their research data. One of his roles is being a REDCap administrator: training, consulting and supporting the use of REDCap. He has recently taken interest in Public Health and enrolled into an MPH program.
Learn about building an electronic data capture form, enabling survey settings, simple longitudinal project setup and access provisions
Needing to collect data from people in a structured and intuitive way? Have you thought about using Qualtrics? Qualtrics in a powerful cloud-based survey tool, ideal for social scientists from all disciplines. This course will introduce the technical components of the whole research workflow from building a survey to analysing the results using Qualtrics. We will discover the numerous design elements available in order to get the most useful results and make life as easy as can be for your respondents. If your institution has a licence to Qualtrics, then this course is right for you.
This presentation will demonstrate a number of in-flight research projects using an extensive REDCap feature set, such as randomisation, advanced reporting (e.g., enrolment tracking) and automated notifications via email and SMS. It will be a great opportunity to be inspired by a range of advanced REDCap features that enable real-life research projects.
Aidan Wilson Intersect
Aidan Wilson is Intersect's eResearch Analyst for Australian Catholic University, where his role includes administration and user support for REDCap, Qualtrics, and a host of other research software applications. When he was a researcher himself, he studied the Aboriginal languages of Australia's top-end, and wrote his Master's thesis on Traditional Tiwi.
Learn about building an electronic data capture form, enabling survey settings, simple longitudinal project setup and access provisions
This presentation will demonstrate a number of in-flight research projects using an extensive REDCap feature set, such as randomisation, advanced reporting (e.g., enrolment tracking) and automated notifications via email and SMS. It will be a great opportunity to be inspired by a range of advanced REDCap features that enable real-life research projects.
Weisi Chen Intersect
Weisi Chen is Intersect’s eResearch Analyst for University of Technology Sydney, his routine responsibilities include research support, as well as the UTS REDCap administrator. With more than nine years of eResearch experience, Weisi has expertise in a broad range of eResearch technologies.
Programming is becoming more and more popular, with many researchers using programming to perform data cleaning, data manipulation, data analytics, as well as creating publication quality plots. Programming can be really beneficial for automating processes and workflows. In this presentation, we are exploring four of the most popular programming languages that are widely used in academia, namely Python, R, MATLAB, and Julia.
In this talk we will walk through the DReSA web application, including: how to search and filter training events and material, how to subscribe to updates, and how to find trainers and training providers in your area (geographic and academic).
Anastasios Papaioannou Intersect
Programming is becoming more and more popular, with many researchers using programming to perform data cleaning, data manipulation, data analytics, as well as creating publication quality plots. Programming can be really beneficial for automating processes and workflows. In this presentation, we are exploring four of the most popular programming languages that are widely used in academia, namely Python, R, MATLAB, and Julia.
Dr Emmanual Blanchard Mathworks
Dr Emmanuel Blanchard is a senior application engineer at MathWorks who first joined the company as a training engineer in 2014. His main focus is on data analytics, which includes machine learning and deep learning. He taught several MATLAB and Simulink courses as well as specialized topics such as machine learning, statistics, optimization, image processing and parallel computing. Prior to joining MathWorks, he was a Lecturer in Mechatronic Engineering at the University of Wollongong. He holds a PhD in Mechanical Engineering from Virginia Tech. He also worked as a Systems / Controls Engineer at Cummins Engine Company and as a research assistant in several research institutions in California and Virginia.
Programming is becoming more and more popular, with many researchers using programming to perform data cleaning, data manipulation, data analytics, as well as creating publication quality plots. Programming can be really beneficial for automating processes and workflows. In this presentation, we are exploring four of the most popular programming languages that are widely used in academia, namely Python, R, MATLAB, and Julia.
This presentation will talk about my journey of switching over to Julia, summarise the pros and cons, and provide some tips on learning to code in Julia.
Jason Potas UNSW
Jason Potas is an inventor and neuroscientist working on sensory processing and pain. He is currently an Adjunct Senior Lecturer at UNSW and Director of Bionic Innovations.
Learn about the fundamental concepts in programming using Python and apply them to analyse a sample research dataset.
Explore DataFrames in-depth and learn about Data Manipulation in Python using the Pandas library.
Learn about Data Visualisation in Python using the Matplotlib and seaborn libraries.
Abdullah Shaikh Intersect
Abdullah Shaikh is an eResearch Analyst at Intersect Australia (based at the University of New South Wales). He has a wealth of experience in delivering training courses on multiple programming languages and software like R, Python, MATLAB, Excel, and SPSS. His areas of interest are machine learning, data analysis, visualisations, and statistics. Abdullah has experience working with researchers with diverse backgrounds for over four years.
Tomasz Bednarz UNSW & CSIRO
This presentation will examine crowdsourcing or citizen science - that is involving public volunteers in the completion of research tasks - as a method in the digital humanities. It will draw on my experiences in two such crowdsourcing projects, The Prosecution Project (https://prosecutionproject.griffith.edu.au/) and Criminal Characters (https://prosecutionproject.griffith.edu.au/). Topics covered will include rationale and ethics of crowdsourcing, platforms available for building projects, how to motivate volunteers and sharing the resulting research and data with the public.
Dr Alana Piper University of Technology Sydney
Dr Alana Piper is a Chancellors Postdoctoral Research Fellow at the Australian Centre for Public history at UTS. Her research interests draw together the social and cultural history of crime with criminological, legal and digital humanities approaches. She has authored over 40 academic publications, and is currently a CI on the ARC Discovery project 'Sex and the Australian Military, 1914-2020' (2021-2023) and the ARC LIEF project 'Time-Layered Cultural Map of Australia' (2019-2021).
From my overwhelming first use of REDCap to where I am now - a competent REDCap user and advocate of the software for clinical research. I am going to talk through my experience, learnings, frustrations, tips and tricks, and why I believe it is software every researcher should have in their arsenal.
Jessica Wilson University of Newcastle
Jess has a Bachelors degree in Psychology and is a project officer for Frances Kay-Lambkins research team where mental health and substance use dual diagnosis and the development of eHealth interventions are the primary focus. Jess's current research trials and project areas include suicide prevention, brain cancer caregiving, and depression and alcohol/other drug use. Jess will commence her PhD in trauma-informed care in late 2020.
The EPIWATCH (TM) ‘Global Eye’ monitors a wide variety of data generated around the world 24/7 through its AI-driven data collection including news casts, social platforms and medical reporting using over 25 global languages including the major languages of Asia. We can tap into chatter in communities and local news reports to find out about outbreaks long before health officials are notified.
Prof Raina MacIntyre UNSW
Raina MacIntyre (MBBS Hons 1, M App Epid, PhD, FRACP, FAFPHM) is Professor of Global Biosecurity, NHMRC Principal Research Fellow and Head of the Biosecurity Program at the Kirby Institute, UNSW, Australia. She leads a research program in control and prevention of infectious diseases, spanning vaccinology, pandemics, bioterrorism and emerging infections, and personal protective equipment.
This three-hour hands-on tutorial teaches the fundamentals of using Linux and High Performance Computing, using the NCI Gadi HPC system.
John Zaitseff UNSW
John Zaitseff has been using and programming computers since his primary school purchased its first in the early 1980s. Having studied Computer Engineering at UNSW, he has been involved with the Free / Open Source Software movement and with Linux in particular since 1993. He has been teaching others the joys of these technologies since 2014.
Needing to collect data from people in a structured and intuitive way? Have you thought about using Qualtrics? Qualtrics in a powerful cloud-based survey tool, ideal for social scientists from all disciplines. This course will introduce the technical components of the whole research workflow from building a survey to analysing the results using Qualtrics. We will discover the numerous design elements available in order to get the most useful results and make life as easy as can be for your respondents. If your institution has a licence to Qualtrics, then this course is right for you.
Jeff Wang Intersect
I am the Intersect eResearch Analyst for Western Sydney University. I deliver training workshops and provide support on digital research tools. Previously I worked as Vice-Chancellor’s Postdoctoral Research Fellow at the University of Wollongong, and my research background is Computational Chemistry.
More and more institutions in the GLAM sector (Galleries, Libraries, Archives, and Museums) are sharing their collection data online, but what is it, and how do you use it? In this talk, I'll survey the types of data available – including metadata, images, OCRd text, and transcriptions – and explore possible research topics. Using tools and examples from the GLAM Workbench, I’ll show how GLAM data can be harvested, aggregated, analysed, and visualised. What can GLAM data tell us about Australian history, society, and culture?
A/Prof Tim Sheratt University of Canberra
Tim Sherratt is a historian and hacker who researches the possibilities and politics of digital cultural collections. Tim has worked across the cultural heritage sector and has been developing online resources relating to libraries, archives, museums and history since 1993. He's currently Associate Professor of Digital Heritage in the Centre for Creative and Cultural Research at the University of Canberra. You can find him at timsherratt.org or as @wragge on Twitter.
Are you having trouble navigating your spatial data? Then you have come to the right space! I will be introducing the basic concepts of geospatial data, as well as show a few open source tools to visualise and analyse Geospatial data using R, Python, and QGIS. This will allow you to find your own geospatial path and put your research on the map!
Jonathan Garber Melbourne Data Analytics Platform
I am a Physical Geographer/Environmental Scientist and Research Data Specialist. My professional goals are to critically examine and utilise cutting edge digital technologies to find novel solutions across domains, making these technologies and data analytic techniques more accessible to diverse users
Heard about the Nectar Cloud but want to learn more? In this workshop you will get an overview of the Nectar Cloud's capabilities, and then try some new basic skills, including running an R studio application, and having a play in the Command Line. Note: This is not a full workshop, but like an information session with a small sample of basic Cloud skills.
Advances in Deep Learning have revolutionised the world of AI and changed the way we innovate. This talk provides a high level overview about what Deep Learning is and how it works. It explains how Deep Learning is different from traditional data science and machine learning, and introduces the main branches of this fast developing field of research. This talk is intended for researchers who are curious but unfamiliar with the world of AI and would like to start their journey. No coding or math skills required.
Titus Tang Monash University
Titus is a Deep Learning engineer and educator on the Monash Data Science and AI platform. He provides advice and hands-on assistance to researchers looking to apply deep learning and AI techniques to their research. Titus also leads various AI training events at Monash.
Advances in Deep Learning have revolutionised the world of AI and changed the way we innovate. This talk provides a high level overview about what Deep Learning is and how it works. It explains how Deep Learning is different from traditional data science and machine learning, and introduces the main branches of this fast developing field of research. This talk is intended for researchers who are curious but unfamiliar with the world of AI and would like to start their journey. No coding or math skills required.
Tarun Bonu Monash University
Tarun is a Machine learning engineer at the Data Science and AI platform, Monash University. He is the coordinator for the Machine Learning Community of Practice - ML4AU which explores issues, challenges and interests of user, training and practitioner communities. He involves himself in training events that enable researchers with data skills for effective research.
NCI is one of the tier 1 national supercomputer facility. Gadi is Australia’s most powerful supercomputer, a highly parallel cluster comprising more than 150,000 processor cores on ten different types of compute nodes. Gadi accommodates a wide range of tasks, from running climate models to genome sequencing, from designing molecules to astrophysical modelling.
The Pawsey Supercomputing Research Centre is a tier 1 publicly funded national supercomputing Centre, located in Perth. The Centre provides free access to supercomputing, data, visualisation and cloud infrastructure and expertise. We just welcomed Australia’s new supercomputer Setonix, scheduled to deliver 50 petaFLOPS of compute power for Australian researchers. We have proudly supported Australian researchers on a vast array of projects, from developing new tools to assess patient risk with machine learning, to guiding the experimental development of safe, long-life, high-capacity rechargeable batteries, to underpinning research that helps protect vulnerable species, including the Quokka, to playing a key role in creating a new atlas of the Universe. And we continue to empower students by building their capacity in data literacy. Ann will present the opportunities Pawsey has to offer to your research project and introduce you our new supercomputer, Setonix, an HPE Cray EX system built on the same architecture used in world-leading exascale supercomputer projects. Setonix will include more than 200,000 AMD compute cores across 1600 nodes, over 750 next-generation AMD GPUs, and more than 548 TB of CPU and GPU RAM, connected by HPE’s Slingshot interconnect.
Find out from researchers working at scale why and when to scale your research project to run efficiently and at speed. Supercomputers are available to help accelerate scientific breakthroughs, sometimes to even make them possible. In Australia, researchers have access to supercomputers within universities and research organisations, known as Tier 2 systems. They also have access to publicly funded Tier 1 national research facilities. Access to the national facilities, Pawsey Supercomputing Research Centre and NCI, is free and done via merit allocations. Join panellists, Junming Ho, a Senior Lecturer in the School of Chemistry in UNSW; Samaneh Sadat Setayandeh, a postdoctoral researcher at UNSW with interests focused on the hydrogen storage materials, renewable energy, superconductors, ceramic and radiation-matter interaction; and Duncan Smith, a member of Research Technology Services at the UNSW, to hear about their journey from the lab to supercomputers. The Session will be moderated by Pawsey’s Education and Training Manager Ann Backhaus.
Ann Backhaus Pawsey Supercomputing Centre
Ann Backhaus is the Education & Training Manager at the Pawsey Supercomputing Research Centre. Ann has significant experience in adult teaching and learning, and project and program management. She has led distributed, global teaching & learning teams strategically and operationally, using a variety of modalities and training / enablement materials. Her experience spans numerous industries and domains.
We are all told research must be reproducible. Reproducible research is key to the development of more transparent science, where research can be conducted quickly and rigorously. But how do you put this into action? In this talk we discuss the basic principles that underlie our approach to reproducible research and how we implement them. We will demonstrate some of the tools that we use to build a workflow, and show you how you could apply these to your research.We also discuss the challenges we have and where we want to go next (we look forward to your suggestions).
Dr Taren Sanders Australian Catholic University
Dr Sanders is the Deputy Program Leader of the Motivation and Behaviour at the Institute for Positive Psychology and Education at the Australian Catholic University. His research focuses on the health of children and young people, including perspectives from public health and education.
We are all told research must be reproducible. Reproducible research is key to the development of more transparent science, where research can be conducted quickly and rigorously. But how do you put this into action? In this talk we discuss the basic principles that underlie our approach to reproducible research and how we implement them. We will demonstrate some of the tools that we use to build a workflow, and show you how you could apply these to your research.We also discuss the challenges we have and where we want to go next (we look forward to your suggestions).
Prof Philip Parker Australian Catholic University
Professor Phil Parker is the Deputy Director of the Institute for Positive Psychology and Education at the Australian Catholic University. He received his doctorate in Educational Psychology from the University of Sydney. His major research interest includes educational inequality, developmental transitions, and educational attainment.
Dask is a parallel computing library that scales the existing Python ecosystem. Dask can scale down to your laptop and up to a cluster. This tutorial will introduce Dask and parallel data analysis with dataframes (tabular data). Prerequisites for this workshop are basic/intermediate knowledge of Python, Jupyter notebooks, and pandas dataframes. We will use a small subset of the tutorial materials available here: https://github.com/dask/dask-tutorial
Does your research see you working through unstructured and non-numerical data? With the ability to collect, store and analyse different data types all in one location makes, it’s easy to see why NVivo is becoming the tool of choice for many researchers.
Peta Scott Intersect
In this talk we will walk through the DReSA web application, including: how to search and filter training events and material, how to subscribe to updates, and how to find trainers and training providers in your area (geographic and academic).
Nick May CSIRO
Nick is an accredited software engineer with over thirty years of Information Technology experience, across a variety of roles, languages, systems and domains. The last thirteen years have been spent in the research domain, partly in a software architecture research group, but mostly helping researchers with software and data projects and technology. More recently I have been actively engaged in the Research Software Engineering (RSE) community, as a member of the organising committee for the 2019 UK RSE conference, and as secretary of the RSE Association of Australian and New Zealand (rse-aunz.org).
Jake Surman UNSW
Jake Surman has been supporting research at UNSW for over 20 years, from fixing dial-up modems to helping people manage terabytes of research data. Currently he works for Research Technology Services at UNSW in the Research Data Management (RDM@UNSW) team.
Carina Kemp AARNet
Australian BioCommons aims to build digital capability for life science research. In this talk, Melissa Burke, the Australian BioCommons Training and Communications Officer will outline how you can access and benefit from the bioinformatics tools, methods, compute and training that Australian BioCommons and its partners have to offer.
Melissa Burke Australian BioCommons
Melissa is the Training and Communications Officer for Australian BioCommons. She has many years of experience in developing and delivering face-to-face and online training in bioinformatics with Australian BioCommons and EMBL-EBI. Melissa has a PhD in Molecular Parasitology from the University of Queensland.
The Australian Research Data Common (ARDC) Institutional Underpinnings (IU) program aims to develop a jointly-agreed framework for Research Data Management (RDM) practices. As part of this program, Bond University, University of New South Wales and University of Sydney will be developing and pilot testing a Principledly-Aligned Institutionally-Contextualised (PAIC) RDM introductory educational/training experience for Higher Degree Research (HDR) candidates. At the end of the program, the experience will be made available to other institutions to implement and customise based on their policies, systems and processes, while still espousing common RDM principles (e.g. sharing data safely). It is envisaged that once the PAIC experience is implemented by institutions nationwide, it will result in a ‘standardised’ RDM training for HDR candidates, which will raise their awareness of RDM best practices to a common baseline. This baseline awareness will assist them in making informed decisions around managing their data, and facilitate cross-institutional management of data (e.g. having common RDM expectations when moving between institutions). To ensure that the PAIC experience is effective and engaging, the experience must be designed to be relevant and useful for the HDR candidates (i.e. contextualised content that allows them to start RDM planning and enact RDM best practices relevant to their early project phase in their institutions) (Oo, Chew, Wong, Gladding, & Stenstrom, 2021). This presentation will (1) outline the design and development of the PAIC experience, (2) present the first iteration of the PAIC RDM focus areas, and (3) share findings from the PAIC prototype.
Adrian Chew UNSW
Adrian W. Chew is an Adjunct Lecturer with the School of Education at UNSW Faculty of Arts, Design & Architecture. He is also the Academic Development Consultant leading the Institutional Underpinnings PAIC educational/training experience project across Bond University, University of New South Wales and University of Sydney.
Learn about the CloudStor interface and its associated tools and services for managing research data, including SWAN, a cloud service for interactive data analysis using Jupyter Notebooks.
Explore DataFrames in-depth and learn about Data Manipulation in Python using the Pandas library.
The Single Cell App is a cloud-based application that allows visualisation and comparison of scRNA-seq data and is scalable according to use. Users upload their own or publicly available scRNA-seq datasets after pre-processing to be visualised using a web browser. The data can be viewed in two colour modes, Cluster - representing cell identity, and Values – level of expression, and data queried using keyword or gene identification number(s). Using the app to compare four different studies we determined that some genes frequently used as cell-type markers are in fact study specific. These differences, identified using the Single Cell App, highlight the need for resources to enable researchers to find common and different patterns of cell specific gene expression. Thus, the Single Cell App enables researchers to form new hypothesis, perform comparative studies, allows for easy re-use of data for this emerging technology to provide novel avenues to crop improvement.
Prof Jim Whelan La Trobe University
Jim has made outstanding contributions to research and research training. He is a world leading expert in mitochondrial biology in plants, from biogenesis to function, mitochondrial signalling and the role of mitochondria in plant growth, development and stress resistance. He is an expert in phosphate nutrition in plants and leads efforts to develop crop plants that are less reliant on phosphate fertilizers, benefiting both producers and the environment.
The Single Cell App is a cloud-based application that allows visualisation and comparison of scRNA-seq data and is scalable according to use. Users upload their own or publicly available scRNA-seq datasets after pre-processing to be visualised using a web browser. The data can be viewed in two colour modes, Cluster - representing cell identity, and Values – level of expression, and data queried using keyword or gene identification number(s). Using the app to compare four different studies we determined that some genes frequently used as cell-type markers are in fact study specific. These differences, identified using the Single Cell App, highlight the need for resources to enable researchers to find common and different patterns of cell specific gene expression. Thus, the Single Cell App enables researchers to form new hypothesis, perform comparative studies, allows for easy re-use of data for this emerging technology to provide novel avenues to crop improvement.
Matthew Lewsey La Trobe University
Prof Peter Vuillermin Deakin University
When software is created by and for research use, it can be tricky gain credit for that work. Maybe you're seeking credit for your own software, maybe you want to support the creators of the code you regularly use. In this talk we'll cover the basics of software citation: what is it, why do it and how to do it.
Tom Honeyman ARDC
Tom is the program manager of the Software program at the ARDC. In this role he is overseeing the delivery of a program of activities to push for recognition of research software as a first-class output of research. As part of this work the ARDC has released a National Agenda for Research Software (bit.ly/rs-agenda) which lays out the actions that we as a sector need to take to achieve this recognition for research software.
Kat Redzikultsava University of Sydney
A/Prof Abhay Singh Macquarie University
Assoc. Prof. Abhay Kumar Singh is a leading researcher in Data Science with a strong focus on multidisciplinary research in financial risk modelling, econometrics, education, and data analytics. His expertise in the field of empirical research has been demonstrated through industry-funded research projects, high impact publications and research-informed teaching. His research has been published in numerous high impact research outlets, including high-quality ABDC ranked A/A* journals. Abhay is a big believer in open-source software and has been using R for statistical computing, data analytics, machine learning and quantitative research for over ten years. He is also the author of the book “R in Finance & Economics: A Beginner’s Guide” and has extensive experience in training early career and experienced researchers in empirical research and data analytics.
Research Imaging New South Wales (RINSW) is a strategic initiative developed by UNSW in collaboration with the South Eastern Sydney Local Health District. This facility for human imaging, located in the Prince of Wales Hospital, is providing researchers with state-of-the-art imaging capabilities for world-class basic, translational and clinical imaging research. This presentation will introduce the imaging facility and highlight data capturing processes from meta data to images, touch on data storage, processing pipelines, hospital vs. research electronic medical record (EMR) keeping and picture archiving systems (PACS). The entire data collection and analysis workflow will be demonstrated on two examples, quantitative hepatic iron assessment and combined EEG and MRI for identifying unspecified foci of epileptic seizures.
A/Prof Claudia Hillenbrand UNSW
Claudia is the Director of Research Imaging New South Wales. She is an experienced MR scientist developing novel MRI sequences and translating these into clinical application. She has worked on over 30 prospective clinical research studies or trials that investigated MRI for diagnosis, and assessment of therapy, as well as late effects of treatment for cancer and other catastrophic illnesses. She is a renowned expert on MR-based liver iron quantification. Her work has been published in >70 peer-reviewed journal papers, 2 books and 4 book chapters.
Data is an important research asset for the reproducibility of scientific results. However, researchers are often trapped in data sharing dilemmas caused due to several factors such as lack of awareness and support programs, variation in data sharing practices, privacy concerns, and discrepancies in incentives to collaborate around data between data creators, service providers, and users. This presentation will cover a set of simple steps to help researchers share their data effectively through open data repositories. These steps are derived from my professional experience in provisioning and consuming research datasets over the last 15 years. They are based on generally applicable data characteristics and can be potentially applied at different stages of the research data lifecycle.
Dr Anusuriya Devaraju TERN
Anusuriya Devaraju is a Senior Data Innovation Manager at Terrestrial Ecosystem Research Network (TERN). She has conceptualized and led the management and development of several standard practices and technical solutions in Earth and Environmental Sciences, which have resulted in enhanced data management and discovery.
This paper will discuss the development of the Find & Connect Map of Children’s Homes. The Find & Connect web resource provides information about the history of child welfare in Australia. It links together the histories of institutions who provided care with the archival records they created, and information about how these records can be accessed.
The Map of Children’s Homes provides locations of over 2000 residential institutions for children in Australia from 1790-1990. Launched in 2019, it was the culmination of 18 months of research, technical development, and usability testing. It was developed collaboratively with people who grew up in out-of-home care and their support services.
In this paper, we will discuss why a map was needed on Find & Connect, the research that was needed to put a map together, the technical features and issues, and reflect on some broader findings which have become apparent since going live.
Kirsten Wright University of Melbourne
Kirsten Wright is the Program Manager of the Find and Connect web resource, University of Melbourne. Prior to this, she held a number of roles at Victoria University and worked at the Public Record Office Victoria. Kirsten holds a BA in history and politics and a Master of Information Management and Systems, both from Monash University.
This paper will discuss the development of the Find & Connect Map of Children’s Homes. The Find & Connect web resource provides information about the history of child welfare in Australia. It links together the histories of institutions who provided care with the archival records they created, and information about how these records can be accessed.
The Map of Children’s Homes provides locations of over 2000 residential institutions for children in Australia from 1790-1990. Launched in 2019, it was the culmination of 18 months of research, technical development, and usability testing. It was developed collaboratively with people who grew up in out-of-home care and their support services.
In this paper, we will discuss why a map was needed on Find & Connect, the research that was needed to put a map together, the technical features and issues, and reflect on some broader findings which have become apparent since going live.
Constance Thurley-Hart University of Melbourne
The Field Acquired Information Management Systems (FAIMS) Mobile Platform is open-source software for offline data collection built by researchers for researchers. First released in 2014 for Android only, the platform is currently undergoing a complete rebuild thanks to the Australian Research Data Commons (ARDC) and co-investment from 19 partners (doi:10.47486/PL110). From June 2022, FAIMS 3.0 will support cross-platform data collection (Android, iOS and desktop), offer more flexible synchronisation, integration with Cloudstor, a DIY option for customisation, and a sleek new look. In this talk, we will provide an introduction to the proposed software, the design choices we have made and the challenges of building complex software for the research sector from within it.
We will provide an overview of the cloud-based virtual desktop platform, CoESRA, running on ARDC. We shall run through an analysis pipeline successfully undertaken in CoESRA and published in peer-review publications.
Siddeswara Guru TERN
Researchers and scientists is an extremely diverse community and Humanities/Social Sciences itself may include Psychology, Sociology, Political Science, Linguistics, Social Work, Anthropology. Other fields, though recognized to be in their own, may still loosely fall under Humanities/Social Sciences such as History, Economics, Education, Law, Geography, not to mention Medical Science research. In all these areas, data are important for empirical studies, to develop theories, to validate or invalidate existing theories. Researchers often learn new computing technology or coding to extract, prepare and transform data. Many hours and effort are spend developing IT skills just to get the data in the right form, instead of developing their scientific skills. Monarch is the tool that has saved hours and days of tedious data preparation work for over 30 years in the commercial sector. It would no doubt be as helpful for researchers today who are faced with ever increasing volumes of data.
Clinton Chee Altair
Clinton is fortunate to work in the field he is passionate in, which is Data Analytics / Data Science. His current work has enabled him to interact with many data practitioners and learning about various interesting and diverse projects. Clinton is keen on taking each of these projects and applying Machine Learning techniques to predict relevant outcomes. His background is in Engineering and Physics, leading up to a PhD in Smart Structures, in which he first came across Artificial Neural Networks and Machine Learning. Since graduation he has been working as a Computational Scientist, making use of his Fortran skills and landing in the area of High Performance Computing which led his roles at UNSW, CBA and Altair. Although still a strong Fortran proponent, Clinton now mostly uses Python for his programming needs. His other interests include Quantum Computing and keeping up to date with Machine Learning developments.
Bradley Horton Mathworks
Bradley Horton is a member of the Academic Customer Success team at MathWorks, helping faculty members better utilize MATLAB and Simulink for education and research. Bradley has supported and consulted for clients on projects in process control engineering, power systems simulation, military operations research, and earthquake impact modelling. Before joining MathWorks, Brad spent 5 years as a systems engineer with the Defence Science & Technology Organisation (DSTO) working as an operations research analyst. Bradley holds a B.Eng. in Mechanical engineering and a B.Sc. in Applied mathematics.
Spatial data is essential for understanding many phenomena in natural and social sciences, and maps are used in a variety of fields to visualise data and results in an appealing and interpretive way. I have been dealing with spatial data with (and without) R for nearly 20 years, using a variety of packages and approaches that have evolved over time, regularly finding challenges and new solutions. In this presentation I will try to summarise my long personal journey with spatial data analysis and visualisation while I demostrate how current integration of R with external libraries like leaflet or plotly make interactive mapping easier (and nicer!) than ever.
José Ferrer-Paris UNSW
I am a Research Fellow at the Centre for Ecosystem Science in the School for Biological, Environmental and Earth Sciences at UNSW. I work with risk assessment for threatened species and ecosystems, maps of species and ecosystems and general applications of biodiversity informatics. I have 20 years of experience with programming (R, Python, PHP, JS, Perl, etc), data management (SQL, XML and GraphQL) and geographical information systems. I have studied in Germany and Venezuela, and worked with the Venezuelan Institute for Scientific Research and the South African National Biodiversity Institute. Currently I am a member of the Red List of Ecosystem Thematic Group of the International Union for the Conservation of Nature.
Agricultural field boundaries is an important problem for the digital agricultural services sector. Precise knowledge of the field distributions can help stakeholders across the agricultural sector to provide field based analytics for crop management and monitoring. In this talk I will present the rather long journey we followed in order to use Deep Learning to extract field boundaries from Sentinel 2 satellite images. I will describe the initial problems formulation, the research approach taken, some research results, and how all this evolved to a viable commercial product.
Foivos Diakogiannis University of Western Australia
Xtronomer (aka former Astronomer - Ph.D. Gravitational Astrophysics, the University of Sydney), turned to data scientist. I currently work as a Senior Research Fellow on Data Science, in the International Center for Radio Astronomy Research (UWA) where I work on all things data science. In particular, I specialize on Deep Learning applications of data science problems, from time series wave forecasting, to computer vision (remote sensing), to gravitational waves detection.
Study design is a vital (and often overlooked) part of successful research. We will cover the important aspects of designing experiments and studies, including calculating appropriate sample sizes and randomisation, implemented in R.
What is ResBaz all about? What should a newcomer expect when you rock up to the 2021 Sydney ResBaz? This session will introduce you to the program and explain how to get the best out of your ResBaz week.
Liz Stokes ARDC
Liz is a passionate supporter of ResBaz because it combines nerding out on computational skills in a fun and social community event. She works in the Skilled Workforce and Development Program for the Australian Research Data Commons and is a certified Carpentries Instructor and Trainer.
Karina Nunez
Find out from researchers working at scale why and when to scale your research project to run efficiently and at speed. Supercomputers are available to help accelerate scientific breakthroughs, sometimes to even make them possible. In Australia, researchers have access to supercomputers within universities and research organisations, known as Tier 2 systems. They also have access to publicly funded Tier 1 national research facilities. Access to the national facilities, Pawsey Supercomputing Research Centre and NCI, is free and done via merit allocations. Join panellists, Junming Ho, a Senior Lecturer in the School of Chemistry in UNSW; Samaneh Sadat Setayandeh, a postdoctoral researcher at UNSW with interests focused on the hydrogen storage materials, renewable energy, superconductors, ceramic and radiation-matter interaction; and Duncan Smith, a member of Research Technology Services at the UNSW, to hear about their journey from the lab to supercomputers. The Session will be moderated by Pawsey’s Education and Training Manager Ann Backhaus.
Junming Ho UNSW
Junming Ho is a Senior Lecturer in the School of Chemistry in UNSW. He leads the Modelling and Mechanism Group which specialises in using computational chemistry simulations to design new catalysts and drug molecules.
Find out from researchers working at scale why and when to scale your research project to run efficiently and at speed. Supercomputers are available to help accelerate scientific breakthroughs, sometimes to even make them possible. In Australia, researchers have access to supercomputers within universities and research organisations, known as Tier 2 systems. They also have access to publicly funded Tier 1 national research facilities. Access to the national facilities, Pawsey Supercomputing Research Centre and NCI, is free and done via merit allocations. Join panellists, Junming Ho, a Senior Lecturer in the School of Chemistry in UNSW; Samaneh Sadat Setayandeh, a postdoctoral researcher at UNSW with interests focused on the hydrogen storage materials, renewable energy, superconductors, ceramic and radiation-matter interaction; and Duncan Smith, a member of Research Technology Services at the UNSW, to hear about their journey from the lab to supercomputers. The Session will be moderated by Pawsey’s Education and Training Manager Ann Backhaus.
Samaneh Sadat Setayandeh UNSW
Samaneh Sadat Setayandeh is currently a postdoctoral researcher at UNSW. She is focusing on atomic scale simulations of tungsten borides and other advanced ceramics. The majority of the work in Samaneh’s PhD - in Condensed Matter Physics from Griffith University - was ab initio calculations on the Pd-H2 system, using Quantum Espresso to calculate electron, phonon and superconductivity properties.
Learn about the fundamental concepts in programming using Python and apply them to analyse a sample research dataset.
Charlotte Page UNSW
Learn about the fundamental concepts in programming using R and apply them to analyse a sample research dataset.
Does your research see you working through unstructured and non-numerical data? With the ability to collect, store and analyse different data types all in one location makes, it’s easy to see why NVivo is becoming the tool of choice for many researchers.
Natalie Wall University of Newcastle
Learn about the CloudStor interface and its associated tools and services for managing research data, including SWAN, a cloud service for interactive data analysis using Jupyter Notebooks.
Ewan Coopey Macquarie University
Ewan is a Macquarie University Ancient History and Archaeology PhD candidate and casual academic researching the Roman army and inscriptions in the province of Dalmatia. He is also interested in the application of digital tools in archaeology, namely database design and data management for epigraphic and archaeological data.
Learn about building an electronic data capture form, enabling survey settings, simple longitudinal project setup and access provisions
This presentation will demonstrate a number of in-flight research projects using an extensive REDCap feature set, such as randomisation, advanced reporting (e.g., enrolment tracking) and automated notifications via email and SMS. It will be a great opportunity to be inspired by a range of advanced REDCap features that enable real-life research projects.
Olya Ryjenko University of Sydney
Olya leads the data team in the University of Sydney's clinical trials support office. Her work includes supporting clinical trials researchers in meeting regulatory and governance requirements for managing their data. Prior to working in research support, Olya was a researcher herself, wearing multiple hats as clinical trials coordinator, data manager and clinician in the discipline of speech pathology.
Learn about Data Manipulation and Data Transformation in R using the dplyr and tidyr packages.
Learn about Data Visualisation in R using ggplot2, one of the most popular plotting packages.
Tim Keighley Macquarie University
I have a background in data science and statistical programming. Currently working at Macquarie University as part of a team that creates online courses.
This three-hour hands-on tutorial teaches the fundamentals of using Linux and High Performance Computing, using the NCI Gadi HPC system.
Dask is a parallel computing library that scales the existing Python ecosystem. Dask can scale down to your laptop and up to a cluster. This tutorial will introduce Dask and parallel data analysis with dataframes (tabular data). Prerequisites for this workshop are basic/intermediate knowledge of Python, Jupyter notebooks, and pandas dataframes. We will use a small subset of the tutorial materials available here: https://github.com/dask/dask-tutorial
David McFarlane UNSW
This three-hour hands-on tutorial teaches the fundamentals of using Linux and High Performance Computing, using the NCI Gadi HPC system.
Dask is a parallel computing library that scales the existing Python ecosystem. Dask can scale down to your laptop and up to a cluster. This tutorial will introduce Dask and parallel data analysis with dataframes (tabular data). Prerequisites for this workshop are basic/intermediate knowledge of Python, Jupyter notebooks, and pandas dataframes. We will use a small subset of the tutorial materials available here: https://github.com/dask/dask-tutorial
Oksana Tkachenko UNSW
This three-hour hands-on tutorial teaches the fundamentals of using Linux and High Performance Computing, using the NCI Gadi HPC system.
Dask is a parallel computing library that scales the existing Python ecosystem. Dask can scale down to your laptop and up to a cluster. This tutorial will introduce Dask and parallel data analysis with dataframes (tabular data). Prerequisites for this workshop are basic/intermediate knowledge of Python, Jupyter notebooks, and pandas dataframes. We will use a small subset of the tutorial materials available here: https://github.com/dask/dask-tutorial
Svetlana Tkachenko UNSW
Learn about Data Visualisation in Python using the Matplotlib and seaborn libraries.
George Milunovich Macquarie University
I work in the areas of Predictive Analytics, Forecasting, Econometrics and Empirical Finance. In my research I investigate a wide range of issues such as interdependences between various financial markets, modelling of volatility, and the identification of structural/causal models. In recent work I incorporate machine learning methods into econometric and time series forecasts.
Michael Falk University of Sydney
Michael Falk is Community Technical Adviser at Heurist. He works with Humanities researchers around the world to design their research databases and build beautiful websites to reach a wider audience with their work. By training he is a literary scholar, with particular interests in distant reading and the early modern literatures of the Indo-Pacific.
Find out from researchers working at scale why and when to scale your research project to run efficiently and at speed. Supercomputers are available to help accelerate scientific breakthroughs, sometimes to even make them possible. In Australia, researchers have access to supercomputers within universities and research organisations, known as Tier 2 systems. They also have access to publicly funded Tier 1 national research facilities. Access to the national facilities, Pawsey Supercomputing Research Centre and NCI, is free and done via merit allocations. Join panellists, Junming Ho, a Senior Lecturer in the School of Chemistry in UNSW; Samaneh Sadat Setayandeh, a postdoctoral researcher at UNSW with interests focused on the hydrogen storage materials, renewable energy, superconductors, ceramic and radiation-matter interaction; and Duncan Smith, a member of Research Technology Services at the UNSW, to hear about their journey from the lab to supercomputers. The Session will be moderated by Pawsey’s Education and Training Manager Ann Backhaus.
Duncan Smith UNSW
Duncan Smith is a member of Research Technology Services at UNSW and has been heavily involved with the on-campus computational cluster Katana since its inception.
The Field Acquired Information Management Systems (FAIMS) Mobile Platform is open-source software for offline data collection built by researchers for researchers. First released in 2014 for Android only, the platform is currently undergoing a complete rebuild thanks to the Australian Research Data Commons (ARDC) and co-investment from 19 partners (doi:10.47486/PL110). From June 2022, FAIMS 3.0 will support cross-platform data collection (Android, iOS and desktop), offer more flexible synchronisation, integration with Cloudstor, a DIY option for customisation, and a sleek new look. In this talk, we will provide an introduction to the proposed software, the design choices we have made and the challenges of building complex software for the research sector from within it.
Jens Klump
Jens Klump is a geochemist by training and leads the Exploration Through Cover Group in CSIRO Mineral Resources based in Perth, Western Australia. In his work on data infrastructures, Jens covers the entire chain of digital value creation from data acquisition to data analysis with a focus on data in minerals exploration. This includes automated data and metadata capture, sensor data integration, both in the field and in the laboratory, data processing workflows, and data provenance, but also data analysis by statistical methods, machine learning and numerical modelling.
Research Imaging New South Wales (RINSW) is a strategic initiative developed by UNSW in collaboration with the South Eastern Sydney Local Health District. This facility for human imaging, located in the Prince of Wales Hospital, is providing researchers with state-of-the-art imaging capabilities for world-class basic, translational and clinical imaging research. This presentation will introduce the imaging facility and highlight data capturing processes from meta data to images, touch on data storage, processing pipelines, hospital vs. research electronic medical record (EMR) keeping and picture archiving systems (PACS). The entire data collection and analysis workflow will be demonstrated on two examples, quantitative hepatic iron assessment and combined EEG and MRI for identifying unspecified foci of epileptic seizures.
Dr Daniel Flanagan UNSW, Sydney Childrens' and Prince of Wales Hospital
We will provide an overview of the cloud-based virtual desktop platform, CoESRA, running on ARDC. We shall run through an analysis pipeline successfully undertaken in CoESRA and published in peer-review publications.
Dr Ivan Hanigan University of Sydney
The Single Cell App is a cloud-based application that allows visualisation and comparison of scRNA-seq data and is scalable according to use. Users upload their own or publicly available scRNA-seq datasets after pre-processing to be visualised using a web browser. The data can be viewed in two colour modes, Cluster - representing cell identity, and Values – level of expression, and data queried using keyword or gene identification number(s). Using the app to compare four different studies we determined that some genes frequently used as cell-type markers are in fact study specific. These differences, identified using the Single Cell App, highlight the need for resources to enable researchers to find common and different patterns of cell specific gene expression. Thus, the Single Cell App enables researchers to form new hypothesis, perform comparative studies, allows for easy re-use of data for this emerging technology to provide novel avenues to crop improvement.
Felipe Ayora BizData
Felipe is the Director for Research and Advanced Computing at BizData. He has over 20 years of experience solving complex technical problems for customers in research, education, health, financial services, oil and gas, and other industries. Before BizData, Felipe had a career of almost 15 years with Microsoft, more recently with the Azure HPC Engineering team at Microsoft.
NCI is one of the tier 1 national supercomputer facility. Gadi is Australia’s most powerful supercomputer, a highly parallel cluster comprising more than 150,000 processor cores on ten different types of compute nodes. Gadi accommodates a wide range of tasks, from running climate models to genome sequencing, from designing molecules to astrophysical modelling.
The Pawsey Supercomputing Research Centre is a tier 1 publicly funded national supercomputing Centre, located in Perth. The Centre provides free access to supercomputing, data, visualisation and cloud infrastructure and expertise. We just welcomed Australia’s new supercomputer Setonix, scheduled to deliver 50 petaFLOPS of compute power for Australian researchers. We have proudly supported Australian researchers on a vast array of projects, from developing new tools to assess patient risk with machine learning, to guiding the experimental development of safe, long-life, high-capacity rechargeable batteries, to underpinning research that helps protect vulnerable species, including the Quokka, to playing a key role in creating a new atlas of the Universe. And we continue to empower students by building their capacity in data literacy. Ann will present the opportunities Pawsey has to offer to your research project and introduce you our new supercomputer, Setonix, an HPE Cray EX system built on the same architecture used in world-leading exascale supercomputer projects. Setonix will include more than 200,000 AMD compute cores across 1600 nodes, over 750 next-generation AMD GPUs, and more than 548 TB of CPU and GPU RAM, connected by HPE’s Slingshot interconnect.
Chris Wilkinson NCI Australia
Chris Wilkinson has a background in journalism and media production and has been with NCI Australia for over five years. First and foremost a storyteller, Chris translates the incredible scientific achievements made possible by high-performance computing and data services in Australia and shares these amazing stories with the world through moving images, research highlights and other media.
Sam Ryan Intersect
Machine learning and AI technologies have been the subject of a lot of hyperbole recently. They are valuable tools, but there are things that researchers need to be aware of to get the most out of the techniques. This talk gives an introduction to machine learning and AI from the point of view of the practitioner and looks under the covers to give tips to inexperienced and experienced users of machine learning alike.
James Pearce BizData