Galaxy Australia’s role in responding to the COVID-19 pandemic

Mr Simon Gladman1, Dr Nicholas Rhodes2, Dr Gareth Price2, Professor Andrew Lonie3

1University of Melbourne, Carlton, Australia
2QCIF Facility for Advanced Bioinformatics, St Lucia, Australia
3Australian BioCommons, Carlton, Australia


The global Galaxy Project responded to the urgent need for insight into the SARS-COV-2 virus through its global partners to help build a truly global, democratised, reproducible and transparent multifaceted approach to systematic analyses of the virus. Galaxy Australia contributed to this effort through deployment of specific SARS-COV-2 analytical workflows at the Pawsey Supercomputing, for access to all Australian researchers.


Galaxy Australia in conjunction with the Pawsey Supercomputing centre were able to deploy a Galaxy Pulsar (Galaxy remote deployment) on the NIMBUS cloud, complete with tools and workflows for analysis of DNA sequencing data from SARS-COV-2 samples. Galaxy Australia was configured to prioritise user requests for tools associated with SARS-COV-2 workflows to be directed to Pawsey for rapid analysis turnaround.


This talk will describe the deployment at Pawsey, the linkages and complementary analysis established at Galaxy Australia, Galaxy Main (USA) and Galaxy Europe, highlighting Galaxy Australia’s role in enabling research into a global problem. Up to date details of the utilisation of the workflows will also be presented.


In response to a global need, Galaxy Australia and Pawsey Supercomputing centre were able to demonstrate agility and timeliness to the growing threat of SARS-COV-2. The workflows deployed on Galaxy Australia were complemented by additional workflows on the partner usegalaxy.* global platforms, demonstrating the power of open source democratised science.


Simon Gladman works at Melbourne Bioinformatics and is Chief Engineering of Galaxy Australia. Simon has contributed actively to the global Galaxy community for 10 years and helps shape the direction and support Australian researchers garner from their use of the national Galaxy Australia platform.

Coastal image classification and analysis based on convolutional neural networks and pattern recognition

Dr Bo Liu1,2, Bin Yang2, Professor Giovanni Coco1, Huina  Wang2, Sina Masoud-Ansari1, Professor Mark  Gahegan1

1Univ. Of Auckland, Auckland, New Zealand
2Beijing University of Technology, Beijing , China

The study of coastal processes is critical for the protection and development of beach amenities, infrastructure and properties. Many studies of beach evolution rely on data collected using remote sensing and show that beach evolution can be characterized by a finite number of “beach states”. However, due to practical constraints, long-term data displaying all beach states are rare. Also, when the dataset is available, the accuracy of the classification is not entirely objective since it depends on the operator. To address this problem, we have collected hourly coastal images and corresponding tidal data for more than 20 years (Nov. 1998-Aug. 2019). We classified the coastal images into 8 categories according to the classic beach state classification, defined as 1)reflective, 2)incident  scaled  bar, 3) non-rhythmic,  attached  bar, 4)attached rhythmic  bar, 5)offshore  rhythmic  bar, 6)non-rhythmic,  3-D  bar, 7)infragravity  scaled  2-D  bar, 8)dissipative. Classification models are usually based on convolutional neural networks. After image pre-processing with data enhancement, we have compared Densenet, Resnet, Resnext and improved Resnext models. The improved Resnext obtained the best and most stable classification with an accuracy of 94.58% and good generalization ability. The classification results of the whole dataset are transformed into time series data. FP-Growth and MDLats algorithms are used to find frequent patterns and motifs which represent the pattern of coastal morphology changes within a certain period of time. Combining the pattern of coastal morphology change and the corresponding tidal data, we also analysed the characteristics of beach morphology and the changes in morphological dynamics states.


Bo Liu is a visiting scholar at School of Computer Science, the University of Auckland, and an associate professor of School of Software Engineering, Beijing University of Technology. She received Ph.D. degree from the Department of Automation, Tsinghua University. She once worked in NEC Laboratory China as a researcher and at the University of Chicago and Argonne National Laboratory as a Research Professional. She joined Beijing University of Technology in 2015 as an associate professor. Her research interests include big data, data mining, machine learning, cloud computing, scientific workflow and Semantic Web. She has authored over 100 articles and inventions.

Creating spatial linked data collections for social science research using

Mr Marco Fahmi1, Associate Professor Amir Aryani2, Mr Les Kneebone3, Dr Tom Verhelst1

1Griffith University, Logan, Australia
2Swinburne University of Technology, Hawthorn, Australia
3Analysis & Policy Observatory, Hawthorn, Australia

Data CO-OP is a platform that facilitates collaboration between researchers and community groups to create collective impact through the sharing of spatial social data. To achieve this goal, Data CO-OP is creating Linked Data versions of a number of key government, non-profit and community-generated data collections using JSON-LD format.

These collections will use a shared JSON-LD Context to ensure terms and concepts are consistent to ensure data analyses are sound. As a starting point, Data CO-OP used ABS Census data (one of the most widely used collections by Australian social scientists) to map properties to (one of the most commonly used schemas for JSON-LD) and create a core Context that can be later expanded as more data collections are added to the platform.

The ABS Census data collection contains more than 15 thousand properties that need to be captured in the JSON-LD Context. Automated and semi-automated methods were used to map each property to one, two or three values in’s structure and create the core Context and convert ABS Census data into JSON-LD format.

Over sixty categories are needed to fully capture ABS Census data properties. This mapping activity used the top dozen categories to map to and create a core Context. The mapping covers 93% of the 15 thousand ABS Census data properties.

The mapping used to generate a core Context is promising. Current work is to validate Its usefulness by working with researchers on specific use cases with the intend to increase coverage to 100%.


Marco Fahmi is a digital research expert. His expertise is in technology- and data-driven research with experience in social sciences, humanities and ecological disciplines. He is currently leading efforts to create spatial linked data collections for social science research and data synthesis initiatives with state government to drive research-informed policy and decision making.

A profession for eResearch

Dr Nick Tate1

1University Of Queensland

There has been significant discussion around the benefits of formalising eResearch ICT support roles with reference to the SFIA (Skills Framework for the Information Age) Framework. To date, there are few, if any, published eResearch roles which decompose into a combination of SFIA skills and Levels of Responsibility.

The benefits of adopting a standardised approach to these role definitions are substantial. Standardised roles will facilitate an equivalence not only between eResearch roles within the “not for profit” research sector but also with other research organisations and with the wider body of ICT/digital skills and roles.

This will improve the career prospects of eResearch ICT staff by improving the portability and recognition of their skills and experience. And, in turn, this will make the role of eResearch ICT support person more attractive at a time when ICT skills are in considerable demand leading to shortages.

To address this issue, it is proposed to run a Birds of a Feather (BoF) session which presents attendees with a range of potential eResearch ICT roles together with options for possible breakdown into SFIA skills and Levels of Responsibility.

After the session, it is proposed that the results should be collated and summarised before being shared with each participant. The summarised results would then be shared with the SFIA Foundation, who are currently seeking input for the development of SFIA V8 and with the Commonwealth Government’s project on the definition of ICT roles in the Australian Public Service.


Nick has 45 years’ IT experience and 20 years in Cybersecurity. He headed up ICT at two London banks and was IT Director and head of AusCERT at UQ.  He is co-founder of the eResearch Australasia Conference and was Director of the Commonwealth funded Research Data Storage Infrastructure project (RDSI). Nick is Vice-President of the Australian Computer Society with responsibility for professional standards, degree certification and certification. As President of the South East Asia Computer Confederation (SEARCC), he leads an APEC project on ICT Skills Frameworks. He is a member of the SFIA Council and an Adjunct Professor at UQ.

Australian Imaging Service (AIS): Building a national federation

Dr Ryan Sullivan1, Australian Imaging Service1,2,3,4,5,6,7,8,9,10,11,12, A/Prof David Abbott2,9, Michael Cartwright10, Dr Oren Civier2,8, Dr Thomas Close1,2, Mr Alasair Ferguson4, Dr Andrew Mehnert2,12, Dr Aswin Narayanan2,11, Mr Dean Taylor11, Mr Chris Williams6, Mr Craig Windell6, Mr Fang Xu1

1The University of Sydney
2National Imaging Facility
3Australian Research Data Commons
4Macquarie University
5Queensland Cyber Infrastructure Foundation
6Queensland University of Technology
8Swinburne University
9The Florey Institute of Neuroscience and Mental Health
10University of New South Wales
11University of Queensland
12University of Western Australia

Universities and clinical sites across Australia share common challenges in managing large volumes of imaging data, balancing patient privacy, and the value earned through secondary-use by trusted research communities. The Australian Imaging Service (AIS) will transform the imaging sector by leveraging institutional investments and providing enhanced data management and analysis. The distributed federation will consist of multiple institutional Trusted Data Repository (TDR) deployments linked with a federated search layer, common community practice, support for expanded data types, and a Trusted Tool Repository (TTR) ensuring ongoing ownership and accountability of data.

The 2020 project consists of 4 streams:

Building on independent but convergent initiatives, we are deploying standardized AIS nodes at USYD, Monash, MQ, QUT, UNSW, UQ, and UWA across commercial cloud, NECTAR, Pawsey, and on-premise infrastructure, built around XNAT. We aim to reach IRAP (Protected), HIPAA, and GDPR compliance to allow better integration with clinical systems.

Expansion of containerized pipelines will create larger toolsets for image analysis and QC, including a TTR, vetted by the National Imaging Facility.

Expansion of supported imaging modalities and open data formats to cover a wider research base.

Integration with key related platforms including CLARA for machine learning and REDCap.

We will present on our strategy and approaches, covering technologies, standards, clinical practices, containerization, and sustainability in order to facilitate discussion. We welcome new entrants into the federation along with input from potential user groups wishing to shape this national platform through the creating working groups around standard analysis, QC/QA, ethics, and ML.


Dr Ryan Sullivan is the Product Manager overseeing digital platforms for Characterization research at the University of Sydney. He sits across the Research Technology Group in ICT and the Operations team of the Core Research Facilities.

Ryan leads the Australian Imaging Service platform and works to bridge the research-clinical gap across all facets of characterization.

A holistic, credit-based approach to researcher training

Dr Monica Kerr1, Marium Afzal Khan2

1University of Adelaide, Adelaide, Australia
2Intersect Australia, Sydney, Australia

Universities have a duty of care to equip Higher Degree by Research students (HDRs) with the skills required to build careers within and outside of academia. Underscored in the 2016 ACOLA Review, transferrable skills training is now an integral part of a contemporary research education program. The Career and Research Skills Training (CaRST) program is the University of Adelaide’s approach to deliver more comprehensive research training and career development for HDRs. Embedded into the graduate research degree and complementary to the main research project, CaRST incorporates eResearch skills training along with a number of other personal and professional skills that are valuable for success in the modern workplace.


CaRST is structured around the four domains of the Vitae Researcher Development Framework (RDF), namely knowledge & intellectual abilities; personal effectiveness; research governance and organization; and engagement, influence and impact. The program implements a credit system for HDRs through which they can track their development across various domains and also incentivizes them to diversify their skills. Traditional eResearch training, such as Intersect’s software carpentry-style courses for programming languages, is complemented by other technology-related training courses that are valuable for researchers (e.g., creating research impact through social media).

In this presentation, we will discuss the CaRST framework in detail, how eResearch training can leverage this system, and some observations from the data about how HDRs choose to structure their training and development. Lastly, we will talk about a proposed framework to evaluate the impact of such a program.


Dr Monica Kerr is the inaugural Director of the University of Adelaide’s Career and Research Skills Training (CaRST) program for Higher Degree by Research students (HDRs). Monica specialises in developing researchers to enhance career and research outcomes. She is an experienced leader, having previously held a senior management position at one of the oldest scientific organisations in the US, the New York Academy of Sciences, and has led initiatives to create industry-ready graduates and student-led startups at the CRC for Cell Therapy Manufacturing and UniSA Ventures, respectively. Monica obtained her PhD in Cell & Developmental Biology from Harvard Medical School.

Secure Research Infrastructure as a Service: Monash Secure Data Enclaves

Dr Amr Hassan1, Mr Daniel Langenhan1, Mr Matthew Barry1

1Monash University, Clayton, Australia

With the increasing focus on security controls within a university setting, it is imperative that universities offer the right balance between commoditised services for the enterprise and bespoke services for research. Delivering this within an operating model where common security postures and practices can be maintained, and pairing this to the risk appetite of the institution is a challenge. The potential reputational damage, legal, and economic consequences for research subjects, the researcher’s institution, and the researcher remains front of mind.

Secure Data Enclaves (SDE) is a software-defined, secure, and centralised private cloud infrastructure that aims to give Monash research users a safe environment to host, process, and analyse their sensitive data. From inception, the design was focussed around creating a capability with security at its core, that did not require the user to sacrifice their overall experience.

On the infrastructure level, SDE offers capabilities such as:

– Software-Defined Micro-segmentation and Network virtualisation,

– Software-Defined-Storage with advanced capabilities such as Erasure Coding, and Stretch Clusters,

– Encryption-at-Rest and Multi-tenancy with full segregation between different workloads,

– Privileged Access Model with a dedicated identity zone; and

– Full Storage Auditing Capabilities.

The platform architecture and design enables the team to offer each workload its dedicated enclave with well defined and monitored traffic routes to ensure that only authorised access is allowed.  Within our presentation, we will discuss the design pattern of the platform and how it can be used to address the challenges of hosting, analysing and processing sensitive data at scale.


Dr Amr Hassan is the Delivery leader for Technology Services and eResearch at Monash University. He leads the infrastructure platforms team at eSolutions. He holds an interdisciplinary PhD in Computational Sciences, an M.Sc in Scientific Computing, and a B.Sc. of Computer Science.

Nailed it: Moving digital skills training online

Dr Sara King1, Dr Mark Crowe2, Dr  Darya Vanichkina3, Dr Liz Stokes4, Dr Rebecca Lange5, Dr Anastasios Papaioannou6, Ann Backhaus7

1AARNet, Adelaide, Australia, 2QCIF, Brisbane, Australia, 3University of Sydney, Sydney, Australia, 4ARDC, Sydney, Australia, 5Curtin University, Perth, Australia, 6Intersect, Sydney, Australia, 7Pawsey Supercomputing Centre, Perth, Australia

Digital skills training across AUNZ has moved online. While not necessarily ‘new’, the transition was abrupt and impacted by the social complexities of responding to the coronavirus pandemic. Working from home infrastructure meant training could continue in theory, but represented previously unexplored avenues for many of us.

Over the last several months, there have been endless discussions about successes, achievements, and recommendations about the best ways to deliver online training. In the ENRICH Community of Practice alone, there have been almost 3,000 messages exchanged this year, and this represents just one of many ways in which the eResearch skills trainer community in Australia has come together (virtually) to share emerging best practices for distributed and virtual skills instruction.

During this facilitated session we’d like to flip this conversation and draw from the breadth of experiences across the community to share our fails, embarrassments, and utter disasters – and how we picked ourselves up, learned from them, and had another go! We will use padlet – a tool for flipped learning – to enable attendees to share stories anonymously, and upvote the most common/egregious/relatable ones for focussed discussion.

Our target audience is the trainer seeking a community of practice offering a candid assessment of the challenges of pivoting training to online delivery, a support network and mentorship. We will provide a platform for those, and others in the broader community, to share their stories and work together to continue to create positive and productive training experiences for our research community.


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 to be adapted for Carpentry training workshops. 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.

Galaxy Australia and CloudStor (AARNet) – creating linkages between two national resources

Dr Nuwan Goonasekera2, Mr Simon Gladman2, Dr Frankie Stevens3, Dr Gareth Price1

1QCIF Facility for Advanced Bioinformatics, St Lucia, Australia
2University of Melbourne, Carlton, Australia
3AARNet, Milton, Australia


Galaxy Australia, the life science platform that allows reproducible, transparent analyses through a web interface and Cloudstor, AARNet’s cloud research data storage platform, have brought users of these platforms together by enabling easy and secure data transfer options between these national platforms.


The “Import from Cloudstor” tool allows users of Galaxy Australia, after a simple configuration of their Cloudstor storage allocation, to navigate through their folders to import files, directories or multi-directories of files into their Galaxy History. Once their data has been analysed the ”Send data to Cloudstor” tool allows the user to securely transfer any files back to their Cloudstor allocation.


Running on the latest version of Galaxy (20.05), researchers analysing data can now rely on  seamless interaction and movement of their data to / from their AARNet provided Cloudstor personal account.


The development of functionality to connect a long standing national platform (AARNet) with the rapidly growing user base of Galaxy Australia demonstrates the advantages of national platforms working to service integration, for the benefit of all Australian researchers.

This talk will highlight the functionality of both tools and the development and implementation path taken in deploying these enhancements to the Galaxy Australia platform.


Dr Gareth Price is Head of Computational Biology at QCIF Facility for Advanced Bioinformatics. In this role Gareth manages the diverse spectrum of researcher lead questions involving genomic data, provides training in genomic data analysis, as well as leading Galaxy Australia ( as Platform Manager.

Gareth has 20 years’ experience as a Bioinformatician and Genomics Scientist.

Gareth’s view is that research is at its best when coupled with the most accurate, highest throughput and innovative technology and analysis modalities.

AARNet’s Review of the Medical Research Institute Sector

Ms Genevieve Rosewall1

1AARNet, Carlton, Australia

Australia’s Academic and Research Network (AARNet) strives towards a long-term vision for a globally networked data-sharing ecosystem that accelerates knowledge creation and innovation. This vision includes reinforcing the resilience of AARNet’s infrastructure and building out new capabilities to meet evolving digital needs. AARNet has a strategic priority to support and invest in health and medical research infrastructure, and aims to remove barriers to access to and sharing, movement and analysis of data for health and medical research.

Rapid advances in health information technology are driving transformation in health research, enabling more complex and efficient research to be conducted. Medical Research Institutes (MRIs) are internationally recognised leaders in health and medical research, covering a broad range of human health issues. To understand requirements across the sector, AARNet engaged with over 35 MRIs to discuss their digital practices, requirements and pain points.

This presentation will outline the engagement activity AARNet has conducted with MRIs over the past few months – consultations with stakeholders to uncover challenges and identify commonalities in requirements of organisations and opportunities for collaboration and growth. The sector analysis and summary that was completed during this engagement will be presented along with potential solutions and actions identified to assist the medical research sector. This presentation will inform the eResearch community of digital challenges and issues faced by those conducting health and medical research across Australia.


As the Health and Medical Community Liaison at AARNet Genevieve works closely with researchers to understand the digital research requirements of the Health & Medical community. Working nationally Genevieve advises on service development and assists with the deployment of technologies and workflows to meet the needs of Australia’s Health & Medical research community.


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    About the conference

    eResearch Australasia provides opportunities for delegates to engage, connect, and share their ideas and exemplars concerning new information centric research capabilities, and how information and communication technologies help researchers to collaborate, collect, manage, share, process, analyse, store, find, understand and re-use information.

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