2019 eResearch Australasia Conference – Lightning Talks – Tuesday 22 October

Harnessing The Wisdom of Crowds: The SWARM Project

Prof. Richard O. Sinnott1 & the SWARM Team1

1University of Melbourne, rsinnott@unimelb.edu.au


The Smartly-assembled,  Wiki-style Argument Marshalling (SWARM) project was funded by the   US   Intelligence   Advanced   Research   Projects   Activity   (IARPA)   as   part   of   the Crowdsourcing Evidence, Argumentation, Thinking and Evaluation (CREATE) program. The project  formally  commenced  in January  2018 and has been awarded  (up to $19m).  The SWARM is one of 4-projects funded globally through the IARPA CREATE program. These projects are tasked with suporting improved reasoning to aid the intelligence community by leveraging the wisdom of crowds. Whilst previous IARPA programs have demonstrated the benefits in leveraging the wisdom of crowds to get improved answers, the actual reasoning and deliberation in what makes a good answer remains unclear. This is the primary goal of SWARM.

The evaluation of the SWARM platform and the other platfoms is currently being undertaken by an independent crowd managed by IARPA and their Test & Evaluation team. This crowd will be organised into separate teams. Each team will be assigned a set of questions that require reasoning and evaluation to come up with the most highly regarded answers over several months, i.e. those answers (hypotheses) with the best reasoning and presentation.

This presentation will cover the overarching goals of SWARM and the underpinning technical solutions that have been developed. This includes the mobile applications that have been developed  to encourage  crowd  participation.  The talk will also briefly  include  early (non- funded SWARM work) exploring the extent that deep learning approaches can be used for automation of the assessment of collective reasoning.


Professor Richard O. Sinnott is the Director of eResearch at the University of Melbourne and Chair of Applied Computing Systems. In these roles he is responsible for all aspects of eResearch (research-oriented IT development) at the University. He has been lead software engineer/architect  on  an  extensive  portfolio  of  national  and  international  projects,  with specific focus on those research domains requiring finer-grained access control (security). He has over 300 peer reviewed publications across a range of applied computing research areas.

Visualisation of research activity in Curtin’s virtual library

Mr Peter Green1, Dr Pauline  Joseph1, Ms Amanda  Bellenger1, Mr Aaron  Kent1, Mr Matthew Robinson1

1Curtin University, Perth, Australia, P.Green@curtin.edu.auP.Joseph@curtin.edu.auA.Bellenger@curtin.edu.au,  Aaron.J.Kent1@gmail.com,  Matt.Robinson@curtin.edu.au 


Curtin University Library manages authenticated access to its online journal, book and database collections using the URL re-writing proxy service called EZproxy. EZproxy mediates the request between user and publisher platform via the Library. The proxy service is widely deployed in libraries worldwide and has been a standard authentication solution for the industry for many years. The EZproxy software creates a log entry for each request in the Combined HTTP Log format[2]. The log files are extensive, with approximately 30 million lines written per month. The log files capture information for each request such as the IP address, client ID, date and time, HTTP request and response and so forth. The Curtin Library has retained at least five years of the log files.

This large dataset presents an opportunity to learn more about the information seeking behaviour of Curtin Library clients, but also presents a challenge. Traditional analysis of such data tends to produce aggregated usage statistics that do not reveal activity at a granular level. Immersive visualisation could provide a means to see the data in a new way and reveal insights into the information seeking behaviour of Curtin Library clients. In collaboration with Dr Pauline Joseph, Senior Lecturer (School of Media, Creative Arts and Social Inquiry) the Curtin Library proposed this work for funding under the Curtin HIVE[3] Research Internships program. The proposal was successful and a computer science student, Aaron Kent, was employed for a ten week period to produce visualisations from the EZproxy log file dataset.

The data was anonymised to protect client confidentiality whilst retaining granularity. The number of lines in the log file were reduced by removing ‘noise’. The Unity3D[4] software was chosen for its ability to provide visualisations that could be displayed on the large screens of the HIVE but also desktop screens. Many possibilities were discussed for visualisations that might give insight into client behaviour, but two were chosen for the internship.

The first visualisation focusses on the behaviour of individual users in time and space and represents each information request using an inverted waterfall display on a global map as illustrated by Figure 1. Different sizes and shapes are used to present different client groups and the size of the information request is reflected in the size of the object. Geolocation information is used to anchor each request on the map.

Figure 1: Global user visualisation

The second visualisation focusses on the usage of particular resources over time and represents each information request as a building block in a 3D city as illustrated by Figure 2. The different client groups and the volume of requests are illustrated over time by location and size against each particular scholarly resource.

Figure 2: Scholarly resource visualisation

The successful visualisation prototypes have shown that the EZproxy log file data is a rich source of immersive visualisation and further development will yield tools that Curtin Library can use to better understand client information seeking behaviour.


  1. EZproxy Documentation. Available from: https://www.oclc.org/support/services/ezproxy/documentation/learn.en.html accessed 8 June 2018.
  2. Combined Log Format. Available from: http://fileformats.archiveteam.org/wiki/Combined_Log_Format accessed 8 June 2018.
  3. Curtin HIVE (Hub for Immersive Visualisation and eResearch). Available from: https://humanities.curtin.edu.au/research/centres-institutes-groups/hive/ accessed 8 June 2018.
  4. Unity3D. Available from: https://unity3d.com/ accessed 8 June 2018.


Peter Green is the Associate Director, Research, Collections, Systems and Infrastructure in the Curtin University Library, Australia. He is responsible for providing strategic direction, leadership and management of library services in support of research, the acquisition, management, discovery and access of scholarly information resources, and information technology, infrastructure and facilities.

We attended Library Carpentry, what next?

Ms Janice Chan1

1Curtin University, Perth, Australia, Janice.Chan@curtin.edu.au


In 2017, a few Curtin Library staff ran a series of Library Carpentry[1] workshops. The workshops were well-attended by library staff. Feedback from these workshops suggested attendees recognised the need to develop data and computational skills, and expressed interest to discuss how they can apply the skills to their day-to-day work.

Base on the HackyHour model[2], a regular meetup called “Library HackyHour” has been established in 2018. Using the Curtin Makerspace[3] as a neutral platform, Curtin Library staff and Curtin School of Media, Creative Arts, and Social Inquiry staff and students get together every fortnight to share ideas, get help, discuss a problem, and work on projects with like-minded colleagues.

Some of the activities in Curtin Library HackyHour have included lightning talks, learning group for a specific programming language, discussion of work problems related to data and automation, and exploration of open datasets in preparation for future hackathons.

This lightning talk is relevant to this year’s conference because libraries play a key role in supporting eResearch. This is an example of how a workplace can foster a peer-to-peer learning community which is inexpensive, has low barrier of entry to any library staff (and academics training future library staff) who want to become digitally fluent and be better equipped to support researchers now and into the future.


  1. http://librarycarpentry.org/
  2. https://github.com/amandamiotto/HackyHourHandbook
  3. https://maker.library.curtin.edu.au/



Janice Chan is Coordinator, Research Services at Curtin University, Perth, Western Australia. Janice’s experience is in repository management and scholarly communications. She is interested in open research, metrics and impact assessment, research data management, library-led publishing, data analysis and visualisation, and innovative practice in library service delivery.

An Open Question: A comparison of proprietary and open-access teaching materials for researchers

Weisi Chen

Intersect Australia, Sydney, Australia


Intersect Australia has been a significant eResearch training provider for several years. Since the first courses in eResearch tools like HPC and Microsoft Excel, the Intersect repertoire has expanded to over 25 distinct courses, delivered at our 12 member universities, hundreds of times per year to thousands of researchers.

Intersect began utilising open access training materials in 2015: teaching Software Carpentry’s Creative Commons licensed courseware in Python, Matlab, R, Unix, and Git. Shortly thereafter, two Intersect eResearch Analysts were accredited as Software Carpentry instructors. The following year this was expanded with four more accredited instructors, and in 2017, a further six instructors were accredited and Intersect joined the Software Carpentry Foundation as a silver member, a status we recently reaffirmed.

Throughout this period, Intersect has continued to maintain a proprietary catalogue of Intersect-developed courses taught alongside the Software Carpentry materials.

In this presentation, we will explore the differences, if any, in the reception of Intersect developed course material and openly available Software Carpentry material by course attendees. The differences in cost to maintain proprietary courseware or utilise openly available materials is explored. We will also analyse differences between the delivery of the two sets of courses based on other variables, such as the experience level and teaching style of the trainer.

This presentation will be valuable to similar organisations who are grappling with the logistics of running eResearch training courses, and deciding on strategies regarding developing their own material or using material that already exists in the public domain.

As one of Australia’s most recognised eResearch training organisations, Intersect hopes that other, similar organisations may be able to benefit from our experiences, so that the research community can ultimately benefit from high-quality training from a diverse range of providers.

10 Sports Science Things – building a strong data management culture

Mr Cameron Barrie1, Mrs Linda Forbes1

1Victoria University, Footscray, Australia


Victoria University has a strong track record in producing high quality research in sports science. We are noted as one of the best institutions to study or conduct research into sport science and are ranked Top #20 in the World[1] and produce research well above world average in Human Movement and Sports Science. We have built strong connections to industry e.g. AFL and FIFA (World Cup soccer), and are data-intensive in this discipline area.  But what are we doing to make this research data more FAIR (Findable, Accessible, Interoperable and Re-usable)?

Sports science has not had a 23 Research Data Things focus to date and it was decided that producing a 10 Sports Science Data Things guide. Creating the guide would be a good opportunity for VU Library to engage with this group of researchers around the issues or challenges Sports Researchers have around managing their data e.g. storage, description, documentation, archiving etc. 10 Sports Things also starts a conversation around the opportunities that exist when you add value to datasets such as: increased collaboration with other researchers (nationally & internationally), further engagement with industry (enhanced translation), exploiting Australia’s data advantage in this discipline, and accelerating innovation to broaden the impact of our research output.

10 Sports Science Data Things is a self-paced learning program that provides an opportunity for our sports researchers and research students to explore issues surrounding the management of research data.

The activities in this learning program aim to encourage better data management practices and get them thinking about possibilities they may not have considered.

[1] https://www.vu.edu.au/study-at-vu/why-choose-vu/our-global-ranking


Cameron Barrie, Research Services Librarian with Victoria University, provides support to researchers and research students across the university. He has nearly 20 years work experience in academic libraries and is passionate about the role research plays in driving innovation. He has a particular interest in new technologies and finding more efficient ways to get things done.

Linda Forbes, College Librarian for Sport & Exercise Science and Engineering & Science. She provides advice and leadership in library liaison and collaborative work with teaching and research staff. She is passionate about library and educational environments and their ability to extend participatory learning and building connected communities through library programs and services.

Managing data provenance for gravitational wave data analysis

Mr Patrick Clearwater1,2,3, Dr Surya Nepal3, Prof Andrew Melatos1,2

1The University Of Melbourne, Melbourne, Australia, p.clearwater@student.unimelb.edu.au 

2ARC Centre of Excellence for Gravitational Wave Discovery (OzGrav), Australia

3Data61, CSIRO, Marsfield, Australia


First detected in 2015 by the Laser Interferometer Gravitational-wave Observatory (LIGO), gravitational waves are an exciting new area in astronomy, allowing astrophysicists to directly observe hitherto-invisible objects in the sky. However, this breakthrough brings with it a plethora of challenges in managing the terabytes of data LIGO produces. Many of the expected future detections will be from using complex signal processing algorithms to search large parameter spaces. To make such a detection scientifically credible, understanding data provenance—what original source data were used, and exactly how they were processed—is crucially important. In particular, without a thorough record of what was done to produce a scientific result, that result can neither be reproduced, nor can it be extended by other researchers.

One approach to solving this problem is through a virtual laboratory — an environment that knows what data are available, and understands the semantics of the tools used to process it. As well as addressing the data provenance problem, this approach also allows the existing LIGO software suite to be repackaged in an easy-to-use way that makes it accessible to astronomers who are not necessarily gravitational wave domain experts. We discuss some of the work that has been done to apply these techniques to gravitational wave astronomy, as well as how a gravitational wave virtual laboratory could solve the data provenance problem.


Patrick Clearwater is a PhD student at in the Astrophysics group, School of Physics at the University of Melbourne. His research interests lie in analysing gravitational wave data to find evidence of signals at very low signal to noise, such as those expected from neutron stars; as well as building tools to make such searches computationally efficient, easy to use, and reproducible. He is a member of the ARC Centre of Excellence for Gravitational Wave Discovery (OzGrav) and the LIGO Scientific Collaboration.

Digital Earth Australia’s approach to FAIR Data and Open Architectures via the Open Data Cube, Cloud Optimized GeoTIFFs and STAC

Mr David Gavin1,2

1Geoscience Australia, Symonston, Australia,

2Digital Earth Australia, Symonston, Australia, David.Gavin@ga.gov.au


Digital Earth Australia is embracing emergent industry and community trends by releasing digital Satellite Observation products directly to the public and providing a variety of tools for users to derive new insights from the data. This is achieved via:

  1. AWS Simple Storage Service (S3);
  • Cloud Optmized GeoTIFF (COG) format;
  • SpatioTemporal Asset Catalog (STAC);
  • OGC Web Services;
  • The Open Data Cube initiative.

Why it is relevant?

Digital Earth Australia aims to supply Australian Earth Observation (EO) data to: the international research community, the Australian Public, Australian Government and to Australian industry clients. The guiding principles of our work is to deliver access to “Big EO Data” directly to users who don’t have the resources to store petabytes of data themselves and provide the data in an open and interoperable format/standard to allow users to bring their tools to the data.


David has been working for Geoscience Australia for over 10 years, working as a Web Application Developer, Web System’s Administrator, AWS Engineer and Agile Team Leader.

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