Machine learning for the rest of us

Dr Chris Hines1

1Monash Eresearch Centre, Clayton, Australia

 

Neural Networks are the new hawtness in machine learning and more generally in any field that  relies heavily on computers and automation. Many people feel its promise is overhyped, but  there is no denying that the automated image processing available is astounding compared to  ten years ago. While the premise of machine learning is simple, obtaining a large enough  labeled dataset, creating a network and waiting for it to converge before you see a modicum of  progress is beyond most of us. In this talk I consider a hypothetical automated kiosk called  “Beerbot”. Beerbot’s premise is stated simply: keep a database of how many beers each person  has taken from the beer fridge. I show how existing open source published networks can be  chained together to create a “good enough” solution for a real world situation with little data  collection or labeling required by the developer and no more skill than a bit of basic python. I  then consider a number of research areas where further automation could significantly improve  “time to science” and encourage all eResearch practitioners to have a go.


Biography:

Chris has been kicking around the eResearch sector for over a decade. He has a background in quantum physics and with the arrogance of physicists everywhere things this qualifies him to stick his big nose into topics he knows nothing about.

Transforming Research Code to A Modern Web Architecture – Pipetools

Paulus Lahur, Kieran Lomas

CSIRO, Clayton, Australia, paulus.lahur@csiro.au

CSIRO, Clayton, Australia, kieran.lomas@csiro.au

 

SUMMARY

In this paper, we outline the process of transforming research code to a web application, using Pipetools project as the study case. The target is to reach a wide audience of users who can benefit from the code. We are constructing infrastructure and code that support and encapsulate the research code to significantly improve its usability, as well as expand its modes of usage. Currently the project is moving along at reasonable pace. We would like to share challenges that we face and the thought process in solving them. The lessons learned here will hopefully benefit researchers and software developers working in similar projects.

WHY WEB APPLICATION?

Research code is a highly valuable asset hidden deep inside research institutions. It typically runs on a very specific device and environment, and is accessible only to a few researchers. Throughout the course of the research, algorithms and codes are accumulated and improved. As the research matures, the potential benefit to other people increases. In many cases, there will be people out there who are willing to give money to be able to use the software. The problem is, the software is practically usable only to those who makes it, or at least to those who have intimate understanding of how it works. In order to make the software usable to a wider audience, another stage of software development is required. More code needs to be built around the research code in order to improve user experience.

There are two major approaches here. The first one is to make “native application,” that is, software that is native to a certain operating system. In fact, the research software itself belongs to this type. The other approach is to turn it into web application, that is, software that runs on remote machine. Although there are many pro s and cons for either approach, we opt for the latter, because it is accessible to people on various operating systems, and is therefore easier to support and maintain. Software licensing and protection becomes simpler. Rolling out a new version is also trivial. Furthermore, web application also opens door to collaborative work, where a number of people, possibly on different parts of the World, are working on the same set of data.

THE SYSTEM

In order to develop an effective solution, we need to create a modular system, where developers can focus on specific modules. This is outlined in Figure 1. In essence, the development is split into these parts:

  • Front End. It deals with user interface. It translates user commands and send them to Back End.
  • Back End. It receives commands from Front End and calls the research code to do the actual computation.
  • Infrastructure. It deals with services that enable Front and Back Ends to work. This includes containers, as well as continuous integration and deployment.

Each parts have their own challenges. Details of the system will be presented in the paper.

Figure 1: Simplified layout

ACKNOWLEDGEMENT

Research code: Lionel Pullum (Mineral Resources, Clayton VIC) Project manager: Andrew Chryss (Mineral Resources, Clayton VIC) Team lead on IMT side: Daniel Collins (IMT, Kensington WA)

Front End: Kieran Lomas (IMT, Clayton VIC)

Back End: Paulus Lahur, Sam Moskwa (IMT, Clayton VIC)

Infrastructure: Dylan Graham, Andrew Spiers, Sam Moskwa (IMT, Clayton VIC)


Paulus Lahur is CSIRO staff since 2015. He is in Scientific Computing of IMT.

Framework for fully automated analysis of neuroimaging data

Thomas G. Close1,2, Francesco Sforazzini1, Phillip G. D. Ward1,3,4, Zhaolin Chen1,5, Gary F. Egan1,3,4

1Monash Biomedical Imaging, Melbourne, Australia, tom.close@monash.edu

2Australian National Imaging Facility, Australia

3Australian Research Council Centre of Excellence for integrative Brain Function, Melbourne, Australia

4Monash Institute of Cognitive and Clinical Neurosciences, Monash University, Melbourne, Australia.

5Department of Electrical and Computer Systems Engineering, Monash University, Melbourne, Australia

 

INTRODUCTION

Despite the availability of well-established analysis packages, designing comprehensive and portable neuroimaging workflows is challenging due to the wide variety of tools, parameters, and scanner configurations involved. Abstraction of Repository-Centric ANAlysis (Arcana) (https://arcana.readthedocs.io) is a Python framework for designing complex workflows that are comprehensive, portable between sites and scalable to large studies. Several neuroimaging workflows, including fibre tracking and vein analysis, were implemented using Arcana in the NiAnalysis package (https://github.com/mbi-image/nianalysis), and run over a large cohort to demonstrate the scalability of this approach. These workflows are integrated with Monash Biomedical Imaging’s XNAT repository [1] and can be triggered on data ingest to fully automate analyses.

METHODS

Arcana builds on Nipype [2] to encapsulate repository data within Python classes (Fig. 1). Central to its design is the Study class, which specifies all products, and the pipelines to produce them, that can be derived from a specific set of acquisitions. Study objects aggregate modular repository (XNAT [1], BIDS [3], or a custom directory format), execution (linear, multi-process and SLURM) [2] and data-matching components, in order to manage the derivation of products on demand.

Imaging contrast or modality-specific analyses are implemented in Arcana by sub-classing the Study class to specify new products and pipelines (Fig. 1). Multi-contrast/modality studies can be represented by combining Study classes in MultiStudy classes.

Susceptibility weighted imaging (SWI) (1.8 mm, 256x232x72, TE=20ms, TR=30ms), MPRAGE (1 mm, 256x 240×192, TR=2300ms, TE=2.07ms), and dMRI (2 mm, 110x100x60, TE = 95ms, TR=8200ms, 33 directions with b=1500 mm2/s and 3 b=0) datasets were acquired for 544 healthy elderly subjects.

RESULTS

Pipelines for producing composite vein masks from QSM, SWI and T1-weighted MRI [4], and white matter tractograms from diffusion-weighted MRI [5] were implemented in the Arcana framework and applied to cohort of healthy elderly subjects. Composite vein masks were produced for 535 subjects without manual intervention within 13k compute hours on a cluster of Intel Xeon CPU E5 2.50GHz nodes. Data is pulled from, and derived products pushed to, an XNAT repository with processing jobs submitted to MASSIVE [6].

DISCUSSION

The encapsulation of repository data and pipeline generation by Arcana enables workflow designers to create portable, comprehensive workflows while focusing purely on the core logic of their analysis. Arcana’s modular pipeline and inheritance architecture promotes code reuse through the sharing of common segments (e.g. registration) and modifications of existing workflows. Intermediate products are saved in the repository and can be reused by subsequent analyses, saving computation time and manual quality control checks.

When using an XNAT repository, it is possible to trigger Arcana workflows on data ingest and thereby fully automate the analysis. This automation is makes it practical to analyse data from large studies as they are acquired and identify any issues with the acquisition protocol that might arise (e.g. from scanner upgrades or hardware faults).

Figure 1: UML description of the Arcana framework and its application to neuroimaging analysis.
Boxes: Python classes (blue=core, green=interchangeable, grey=specialised). Arrows: orange=data, magenta=processing, diamond=aggregated-in, triangle=subclass-of. Study.data(name) generates the requisite pipelines (specified in Study.data_specs) to produce requested data and uses the runner to execute them. Data is pulled and processed, then the products are pushed back to the repository.

CONCLUSION

By managing the complete flow of data from/to a repository in a flexible and extensible manner, Arcana enables the automation of complex analyses of large-scale neuroimaging studies.

REFERENCES

  • Marcus, D.S., Olsen, T.R., Ramaratnam, M., & Buckner, R.L. (2007), ‘The extensible neuroimaging archive toolkit’. Neuroinformatics, vol. 5, pp. 11–33.
  1. Gorgolewski, K., Burns, C.D., Madison, C., Clark, D., Halchenko, Y.O., Waskom, M.L., & Ghosh, S.S. (2011), ‘Nipype: A Flexible, Lightweight and Extensible Neuroimaging Data Processing Framework in Python’. Frontiers in Neuroinformatics, vol. 5.
  2. Gorgolewski, K.J. Auer, T. Calhoun, V.D. Craddock, R.C. Das, S. Duff, E.P. et al. (2016): ‘The brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments’. Scientific Data, vol. 3.
  3. Ward, P.G.D. Ferris, N.J. Raniga, P. Dowe, D.L. Ng, A.C.L. Barnes, D.G. & Egan, G.F. (2018): ‘Combining images and anatomical knowledge to improve automated vein segmentation in MRI’. NeuroImage, vol. 165, pp. 294–305.
  4. Tournier, J.D. Calamante, F. & Connelly, A. (2012): ‘MRtrix: Diffusion tractography in crossing fiber regions’. International Journal of Imaging Systems and Technology, vol. 22, pp. 53–66.
  5. Goscinski, W.J. McIntosh, P. Felzmann, U. C. Maksimenko, A. Hal, C.J.l. Gureyev, T. D. Thompson, D. Janke, A. Galloway, G. Killeen, N.E.B. Raniga, P. Kaluza, O., Ng, A., Poudel, G., Barnes, D., Nguyen, T., Bonnington, P. and Egan, G.F. (2014). ‘The Multi-modal Australian ScienceS Imaging and Visualisation Environment (MASSIVE) high performance computing infrastructure: applications in neuroscience and neuroinformatics research’ Frontiers in Neuroinformatics

Biography:

Tom completed his PhD on global tractography methods from diffusion MRI at the University of Melbourne. He became interested in neuroinformatics during a post-doc at the Okinawan Institute of Science and Technology, Japan, where he worked on standardising model descriptions of neural systems. Since returning to Melbourne, he has been developing robust and reproducible informatics workflows for the analysis of neuroimaging data at Monash Biomedical Imaging.

Untitled Article

Dr Paulus Lahur1, Mr Kieran Lomas1

1CSIRO, Clayton, Australia, paulus.lahur@csiro.au, kieran.lomas@csiro.au

 

SUMMARY

In this paper, we outline the process of transforming research code to a web application, using Pipetools project as the study case. The target is to reach a wide audience of users who can benefit from the code. We are constructing infrastructure and code that support and encapsulate the research code to significantly improve its usability, as well as expand its modes of usage. Currently the project is moving along at reasonable pace. We would like to share challenges that we face and the thought process in solving them. The lessons learned here will hopefully benefit researchers and software developers working in similar projects.

WHY WEB APPLICATION?

Research code is a highly valuable asset hidden deep inside research institutions. It typically runs on a very specific device and environment, and is accessible only to a few researchers. Throughout the course of the research, algorithms and codes are accumulated and improved. As the research matures, the potential benefit to other people increases. In many cases, there will be people out there who are willing to give money to be able to use the software. The problem is, the software is practically usable only to those who makes it, or at least to those who have intimate understanding of how it works. In order to make the software usable to a wider audience, another stage of software development is required. More code needs to be built around the research code in order to improve user experience.

There are two major approaches here. The first one is to make “native application,” that is, software that is native to a certain operating system. In fact, the research software itself belongs to this type. The other approach is to turn it into web application, that is, software that runs on remote machine. Although there are many pro s and cons for either approach, we opt for the latter, because it is accessible to people on various operating systems, and is therefore easier to support and maintain. Software licensing and protection becomes simpler. Rolling out a new version is also trivial. Furthermore, web application also opens door to collaborative work, where a number of people, possibly on different parts of the World, are working on the same set of data.

THE SYSTEM

In order to develop an effective solution, we need to create a modular system, where developers can focus on specific modules. This is outlined in Figure 1. In essence, the development is split into these parts:

  • Front End. It deals with user interface. It translates user commands and send them to Back End.
  • Back End. It receives commands from Front End and calls the research code to do the actual computation.
  • Infrastructure. It deals with services that enable Front and Back Ends to work. This includes containers, as well as continuous integration and deployment.Each parts have their own challenges. Details of the system will be presented in the paper.

Figure 1: Simplified layout

ACKNOWLEDGEMENT

Research code: Lionel Pullum (Mineral Resources, Clayton VIC) Project manager: Andrew Chryss (Mineral Resources, Clayton VIC) Team lead on IMT side: Daniel Collins (IMT, Kensington WA)

Front End: Kieran Lomas (IMT, Clayton VIC)

Back End: Paulus Lahur, Sam Moskwa (IMT, Clayton VIC)

Infrastructure: Dylan Graham, Andrew Spiers, Sam Moskwa (IMT, Clayton VIC)


Biography:

Paulus Lahur is CSIRO staff since 2015. He is in Scientific Computing of IMT.

Access to the Atlas of Living Australia’s data and tools using ALA4R

Ms Peggy Newman1

1Atlas of Living Australia, Carlton, Australia, Peggy.Newman@csiro.au 

 

The Atlas of Living Australia (ALA) [1] is almost 10 years old. Its primary goal was always clear: to aggregate biodiversity data and make it available for reuse, and it currently holds around 75 million occurrence records for more than 120 000 species. Now in the heyday of big data the ALA finds itself able to comfortably provide large, interesting, standardised datasets to anyone who wants them through a ‘data as a service’ model. Internal infrastructure and external services comprise of the same set of APIs.

In that time the open source R language has become a tool of choice for researchers for statistical computing, publication grade visualisation and reproducible research. The CRAN repository hosts more than 12,000 R packages, amongst which ecology and spatial research are well represented. ALA4R joins a newer brigade of packages which provide an R wrapper to ALA’s APIs for convenient data retrieval.

ALA4R’S core functions reflect ALA’s core functions: searching for information about species and names, providing taxon information, and downloading occurrence and environmental/contextual information. The package caches datasets locally to minimise network traffic. This presentation demonstrates some of ALA4R’s functionality using two case studies.

REFERENCES

  • Atlas of Living Australia (ALA) – https://www.ala.org.au/
  1. R – https://www.r-project.org/
  2. ALA4R Package – https://cran.r-project.org/package=ALA4R

Biography:

Peggy Newman is a Project Manager at the Atlas of Living Australia with a background in software engineering and database development.

https://orcid.org/0000-0002-9084-5992

Delivering Software Solutions to Astronomy Researchers

Prof. Jarrod Hurley1, Dr Jenni Harrison2, Dr Rory Smith4Dr Greg Poole3

1Swinburne University of Technology, Melbourne, Australia, jhurley@swin.edu.au

 2Pawsey Supercomputing Centre, Perth, Australia, jenni.harrison@pawsey.org.au

3Swinburne University of Technology, Melbourne, Australia, gpoole@swin.edu.au

4Monash University, Melbourne, Australia

 

DESCRIPTION

Astronomy Data and Computing Services (ADACS) was established in early 2017 by Astronomy Australia Limited (AAL) to empower the national astronomy community to maximize the scientific return from their data and eResearch infrastructure. ADACS is delivered through a partnership that has been created between Swinburne University, Curtin University and the Pawsey Supercomputing Centre – comprising Melbourne-based and Perth-based nodes.

A key element of ADACS is to provide professional software development and data management services to astronomy researchers. By developing partnerships between researchers and computational scientists – adding professional software engineering, project management, system analysis and design methodologies to projects – we aim to address the quality and performance benchmarks that can be lacking in platforms developed by researcher-only teams. Targeted eResearch fields include big-data analysis and processing, optimization of workflows for high-performance computing, parallel computing techniques, data-sharing and dissemination, large-scale visualization and construction of real-time data analysis platforms. The long-term goal is to provide a central hub for resources in these areas that can be accessed by astronomers – embedding the service within projects to develop nationally significant software pipelines and data platforms.

The proposed session is aligned with the Research Software Engineering stream and specifically the Software as a Service and Development Methods, Tools & Practices themes.

Astronomers apply for ADACS services through a merit-based allocation scheme that is operated twice per year, first submitting an expression of interest, then working with an ADACS member to develop the technical requirements for their project and finally submitting a full proposal which is considered by an independent Time Allocation Committee drawn from the national astronomy community by AAL. Proposals are ranked on merit and matched against the developer weeks (and expertise) available (generally the equivalent of 2-3 full-time developers per year). To date the scheme has focused on short to mid-range projects with an over-subscription rate of 300-500%. This clearly demonstrates a need for such services and a lack of provision in the past. Projects have ranged from developing graphics programming unit (GPU) algorithms for speeding up gravitational wave analysis to enhancing the user interface and back-end for citizen science projects.

A key aspect for the success of these projects is a constructive working relationship between the computational scientists and the researcher (the sponsor) and how this operates within a project management framework. Such a framework can be foreign environment to a researcher, e.g. working in sprints, providing user-stories upfront, so there is a need to be adaptable on both sides. In this session we aim to explore this relationship, providing ADACS case studies from both perspectives, with the aim of sharing our experiences to date and starting discussions with others who have worked through similar experiences. We are also interested in discussions around how we ensure the long-term sustainability of such schemes, how the ongoing needs of delivered projects should be managed and how we can prioritise larger-scale technically challenging projects while still meeting the needs of the general research community.

The proposed BoF session is intended to be 40 minutes in duration.

The proposed format of the session is a mixture of presentations, contributed talks and facilitated discussion as follows:

  • Introduction to ADACS and the methodology behind the delivery of software as a service to researchers within the national astronomy community [10 mins];
  • Case study of an ADACS development project from the developer perspective, focusing on project management, techniques applied and delivered outcomes [10 mins];
  • Case study of an ADACS development project from the researcher perspective, focusing on the science goals, project interaction experience and application of the delivered outcome [10 mins];
  • Facilitated discussion on the developer-researcher relationship when delivering software as a service to a research community, including best practice and lessons learnt to date [10 mins].

The case study from a researcher perspective will be sourced from the pool of completed ADACS projects as a contributed talk. The introduction, case study from a developer perspective and discussion will be provided/convened by the listed convenors/presenters who are all ADACS members.

The targeted audience for the session includes researchers and technical staff with an interest in bringing professional software development practices into the methodology of the scientific research community. The audience need not be astronomy specific. In fact, a primary goal for the facilitated discussion is to initiate conversations aimed at translating support services across scientific domains, promoting collaboration and skill sharing between like-minded entities.

ADDITIONAL INFORMATION

An example of a success story for an already completed ADACS project can be found here:

Below are two examples of ADACS projects currently under development. Both are on track for completion by end of June 2018.

  1. An Automated Data Reduction Pipeline for AAO Data Central

Lead Researcher – Simon O’Toole (Australian Astronomical Observatory: AAO)

Development – ADACS Perth node

Summary: This project will create a data reduction pipeline using python and django to manage CLI functions of an application 2DFDR using a restful API. The API will be accessible by the AAO team in addition to their partners.

  1. GPU Acceleration of Gravitational Wave Signal Models

Lead Researcher – Rory Smith (Monash)

Development – ADACS Swinburne node

Summary: This project will develop a CUDA-based GPU implementation of highly parallelizable gravitational-wave signal models to alleviate the computational bottleneck in Laser Interferometer Gravitational wave Observatory (LIGO) parameter estimation codes. Parameter estimation is an optimal tool for gravitational-wave signal detection but the current high cost prohibits use as a search pipeline.


Biography:

Professor Jarrod Hurley has led the supercomputing program at Swinburne for the past decade and is the manager of the NCRIS-funded OzSTAR national facility. Hurley obtained his PhD in astrophysics at the University of Cambridge (UK) before research positions as a Hubble Fellow at the American Museum of Natural History (USA) and at Monash University. Hurley has a strong research background in computational astrophysics, specialising in realistic N-body simulations of star cluster evolution. He was a founding member of the Astronomy Supercomputing Time Allocation Committee (ASTAC), a former steering committee member for the Australia National Institute for Theoretical Astrophysics (ANITA), a member of the Astronomy eResearch Advisory Committee (AeRAC) for Astronomy Australia Limited (AAL) and manager of the Swinburne node of the Astronomy Data and Computing Services (ADACS) initiative. Hurley is passionate about creating a HPC environment that readily adopts new technology and enables researchers to meet their research goals.

BoF for RSEs: Recognition and Career Development for Researchers who Code

Ms Kerri Wait1, Dr Rebecca Lange2, Ms Amanda Miotto3, Dr Manodeep Sinha4,5, Dr Jens Klump6, Mr Rowland Mosbergen7, Dr Steven Manos8, Ms Heidi Perrett9

1 Monash eResearch Centre, Monash University, Australia, kerri.wait@monash.edu

2 Curtin Institute for Computation, Curtin University, Perth, Australia, rebecca.lange@curtin.edu.au

3 eResearch Services Griffith/QCIF, Griffith University, Nathan, Australia, a.miotto@griffith.edu.au

4 Centre for Astrophysics & Supercomputing, Swinburne University of Technology, Australia, msinha@swin.edu.au

5 ARC Centre of Excellence for All Sky Astrophysics in 3 Dimensions (ASTRO 3D)

6 CSIRO Mineral Resources, Perth, Australia, jens.klump@csiro.au

7 University of Melbourne, Parkville, Australia, rowland.mosbergen@nectar.org.au

8 University of Melbourne, Australia,  smanos@unimelb.edu.au

9 eResearch Support Services, Griffith University, Nathan, Australia, h.perrett@griffith.edu.au 

 

DESCRIPTION

This BoF is to build awareness of the Research Software Engineer (RSE) community and to identify volunteers to help implement the practical solutions for the RSE community that have been identified at the pre-conference workshop. If you are an academic/researcher who codes but are lacking recognition and metrics needed to progress your academic career; a professional software engineer working in the research space; or a  system administrator who maintains research systems, you should attend.

The term RSE, originally coined by the UK RSE association (rse.ac.uk), says the following about RSEs: “A growing number of people in academia combine expertise in programming with an intricate understanding of research. Although this combination of skills is extremely valuable, these people lack a formal place in the academic system.”

Inspired by the success of the RSE Association in UK, we are seeking to establish an Australasian Chapter of the RSE Association. Together with international bodies and support from our national organisations such as AeRO, NeSI, CAUDIT, the Australian Research Data Commons (ARDC), and research institutions, we aim to campaign for the recognition and adoption of the RSE role within the research ecosystem. Alongside this, appropriate recognition, reward and career opportunities for RSEs are needed. We plan to organise regular events to allow RSEs to meet, exchange knowledge and collaborate on methods to create these opportunities.

We ran an initial Expression of Interest survey in 2017 among Australian and New Zealand researchers and found that majority of the respondents prioritised:  (1) Increased recognition of the RSE role, (2) More appropriate, consistent and representative position descriptions and KPIs, and (3) Community development through regular events and gatherings.

Please join us on this event to actively work on how we can grow this community and advocate for others. Together, we can build a sustainable community that benefits research software engineers, and ultimately contributes to more efficient and reproducible research.

FORMAT

A quick presentation of “Who is an RSE?”, the problems that RSEs face, the status of different institutions with regards to employing RSEs and suggested solutions will kick off the BoF. There will then be a breakout session to identify who would like to volunteer their time for which solution.

REFERENCES

  • Research Software Engineers Association. Available from: http://rse.ac.uk/, accessed 6th June

Biography:

Kerri Wait is an HPC Consultant at Monash University. As an engineer, Kerri has a keen interest in pulling things apart and reassembling them in novel ways. She applies the same principles to her work in eResearch, and is passionate about making scientific research faster, more robust, and repeatable by upskilling user communities and removing entry barriers. Kerri currently works with the neuroscience and bioinformatics communities.

3 New Services Streamlining Access to eResearch Capabilities

Mr John Scullen1, Elleina Filippi

1Australian Access Federation, Brisbane, Australia, john.scullen@aaf.edu.au

 

For the past nine years, Australian researchers have seamlessly accessed hundreds of eResearch capabilities connected via the Australian Access Federation (AAF). The AAF continues to enhance identity and access solutions that underpin research applications. These enhanced solutions lead to greater uptake and accessibility of research services, data, and facilities.

This presentation will explore three key initiatives that will expand the access and authentication options available to Australian researchers:

Enhanced International Connectivity through eduGAIN

eduGAIN[1] is a global initiative to connect federations around the world. It enables researchers, educators, and students in one country to collaborate with colleagues and securely access applications in other countries. By participating in eduGAIN, the AAF is able to provide Australian researchers with global collaboration opportunities to advance their research. eduGAIN also enables international collaboration partners to access Australia’s NCRIS capabilities (via participating international federations).

The significant effort to connect the AAF to eduGAIN in 2017 is beginning to yield positive outcomes. Connecting the Murchison Widefield Array telescope to eduGAIN has simplified access to astronomical data from the southern hemisphere for a global team of researchers.

Australia’s eduGAIN connection is helping to accelerate innovation by enabling experts to conduct cross-border collaboration around shared data sets.

Simplified AAF ConNectivity with Rapid Identity Provider

Rapid Identity Provider (IdP) is a new SaaS platform that lowers technical barriers, simplifies connectivity to the AAF and takes away most of the maintenance commitment that comes with running your own identity provider. If your organisation isn’t already connected, Rapid IdP provides the fastest and easiest way to connect to hundreds of research applications around Australia and around the world.

Discover how Rapid IdP overcomes the challenges of running an on-premise identity provider and releases identity management teams to focus their expertise on helping researchers tackle bigger challenges.

Added flexibility via OpenID Connect

OpenID Connect (OIDC) is an emergent specification in the identity space which provides a simple identity layer on top of the OAuth 2.0 authorisation framework.

OIDC is an attractive option for developers (in particular the NCRIS capabilities) as it is applicable for multiple application environments (including mobile) and integrates directly into application code. Adoption of OIDC by large commercial players such as Google and Microsoft is driving widespread usage.

Find out about the OIDC proxy service and how it creates new possibilities for the Australian research community.

[1] edugain.org


Biography:

John joined AAF in February 2016 to lead the development of new processes and tools in the Next Generation AAF project. His role has since expanded to oversee the AAF’s project portfolio and managed service offerings.

With 25 years’ experience in the higher education sector, John has a strong track record of successfully delivering large, complex projects and in developing innovative approaches technology solutions.

DevOps in eResearch

Mr Sven Dowideit1

1CSIRO, Brisbane, Australia

DESCRIPTION

# DevOp learnings

This workshop contains short talks, and discussion on specific tools, techniques, and experiences delivering tools and services to users.

There will be 6 themes, allowing about 30mins for some short talks/demos, and then group discussion:

  • Security as a service
  • Continuous integration and delivery
  • Monitoring, alerting, and logging
  • Moving to the cloud
  • Containerization, orchestration, kubernetes, CaaS systems
  • Keeping your research service running for the next 10 years

WHO SHOULD ATTEND

Anyone that uses a computer to do research related work – predominantly on Linux systems.

WHAT TO BRING

Laptops are useful, but not compulsory


BIOGRAPHY

Sven Dowideit is doing DevSecOps in O&A CSIRO, and previously spent 5 years working in the application container startup space, having lead both the Boot2Docker project and the RancherOS container Linux project.

 

Workshop for RSEs: Recognition and Career Development for Researchers who Code

Mr Rowland Mosbergen1, Mr Nicholas May2, Dr Georgina Rae3, Dr Manodeep Sinha4,5, Dr Lance Wilson6, Dr Steven Manos7

1ARDC, Parkville, Australia, rowland.mosbergen@nectar.org.au
2RMIT University, Melbourne, Australia, nicholas.may@rmit.edu.au
3NeSI, Auckland, New Zealand, georgina.rae@nesi.org.nz
4Centre for Astrophysics & Supercomputing, Swinburne University of Technology, msinha@swin.edu.au
5ARC Centre of Excellence for All Sky Astrophysics in 3 Dimensions (ASTRO 3D)
6Monash eResearch Centre, Monash University, Clayton, Australia, lance.wilson@monash.edu
7University of Melbourne, smanos@unimelb.edu.au

 

GENERAL INFORMATION

  • Workshop Length: 1 day
  • Hands-on component: No technical hands-on components
  • Attendees: All welcome.

DESCRIPTION

This workshop will bring together people who identify as Research Software Engineers (RSE), as well as leaders, policy makers and academics who are keen to see this community grow and be recognised. This one day workshop is the first time a community gathering will take place. The ambition is to build recognition and better define career opportunities for RSEs.

The term RSE was originally coined by the UK RSE association (rse.ac.uk), who say the following about RSEs: “A growing number of people in academia combine expertise in programming with an intricate understanding of research. Although this combination of skills is extremely valuable, these people lack a formal place in the academic system.” In Australia, the term RSE includes academics/researchers who code but are lacking recognition and metrics needed to progress their academic career; professional software engineers working in the research space; and system administrators who maintain research systems.

Inspired by the success of the RSE Association in the UK, we are seeking to establish an  Australasian Chapter of the RSE Association. Together with international bodies and support from our national organisations such as AeRO, NeSI, CAUDIT, ARDC, and research institutions, we aim to campaign for the recognition and adoption of the RSE role within academia, alongside the need for appropriate recognition, reward and career opportunities. We plan to organise regular events to allow RSEs to meet, exchange knowledge and collaborate.

We ran an initial Expression of Interest survey in 2017 among Australian and New Zealand researchers and found that majority of the respondents prioritised: (1) Increasing recognition of the RSE role, (2) Building more appropriate, consistent and representative position descriptions and KPIs, and (3) Developing a stronger community through regular collaborative events and gatherings.

Please join us on this event to actively work on how we can grow this community and advocate for others. Together, we can build a sustainable community that supports RSEs, that ultimately advances our reputation in data-intensive research, and contributes to more efficient and reproducible computational research.

WORKSHOP OUTLINE

  1. Introduction and background on RSE landscape, including meetings held, institutional review.

30 minutes

  1. Introductions and Lightning Talks from delegates

60 minutes

  1. Break

30 minutes

  1. Practical solution brainstorming breakout session, including current sustainable career stories

90 minutes

  1. Break

60 minutes

  1. Virtual meeting time to connect with other RSEs nationally to assign champions/steering committee members

60 minutes

  1. Virtual breakout to organise into smaller teams to start planning implementation strategies

30 minutes

  1. Break

30 minutes

  1. Write up details of the day and close

60 minutes

WHO SHOULD ATTEND

This workshop is for building a community for academics/researchers who create and maintain research software, but are lacking recognition and metrics needed to progress their academic career. Professional software engineers working in the research space, research support team members that work closely with researchers, system administrators who maintain research systems; academics who rely on such expertise; eResearch leaders and policy makers.

WHAT TO BRING

Attendees need to bring enthusiasm and a willingness to volunteer their thoughts and their time. A lightning talk to introduce attendees and their tools for research.

 


BIOGRAPHY

Rowland is the Manager of Community Platforms at the ARDC. He has 20 years experience in IT along with 8 years experience in research computing.

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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.

Conference Managers

Please contact the team at Conference Design with any questions regarding the conference.

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