Tag Archives: Visualisation

The Monash Country Lines Archive on R@CMon

The Monash Country Lines Archive (MCLA) is a collaborative project between the Monash Indigenous Centre (MIC), Faculty of Arts and the Faculty of Information Technology with a team of researchers, digital animators and students. The MCLA aims to support the indigenous Australian communities in the preservation of stories that combine their history, knowledge, poetry, songs, performance and language. MCLA began working with the Yanyuwa people of Borroloola, NT, creating a number of animations between 2007 and 2010. It was these animations that caught the attention of Dr Alan Finkel, the then Chancellor of Monash University. In 2011, the Alan and Elizabeth Finkel Foundation supported the project for a further five years.

Render from “Why We All Die” 2015 ©MCLA & Taungurung Dolodanin-dat Animation Group.

Since its foundation in 2011, the MCLA has produced nine short-form animated films ranging from four minutes to twenty-four minutes in length while working with the communities through every step of the animation process; script, storyboards, character and landscape concepts and construction, animation, rendering, sound and post-production. Initially, producing these animations was challenging due to their heavy computational requirements. The MCLA team didn’t have access to any dedicated render-farm resources as would be normal for a commercial animation studio, so all rendering works were done on individual desktops and laptops. This resource limitation forced the MCLA team to compromise advanced rendering techniques in order to quickly render a large number of scenes while still maintaining a certain level of production quality.

Render from “Jibi the Giant Spirit Birds” 2013 ©MCLA & Nyamba Buru Yawuru.

Render frame from “Jibi the Giant Spirit Birds” 2013 ©MCLA & Nyamba Buru Yawuru.

In 2013, the MCLA team gained access to the NeCTAR Research Cloud, giving them a much needed rendering capacity boost. The R@CMon team assisted the MCLA in deploying and dynamically scaling their workflow into a distributed rendering workflow in the research cloud. Modelling, animation and rendering software have been licensed and configured on this virtual render farm. The farm has been configured so that MCLA can easily access it remotely to submit jobs and inspect their renders. The MCLA then started applying advanced rendering techniques in their workflow, techniques that weren’t possible on their previous setup. After several years of usage, demands for MCLA to produce more and more high quality visualisations also increased. This required the render farm to scale more, much more, and it did.

Render frame from “Janyju the Red Lizard” 2014 ©MCLA & Nyamba Buru Yawuru.

Render frame from “Janyju the Red Lizard” 2014 ©MCLA & Nyamba Buru Yawuru.

Access to the research cloud-backed render farm removed a huge limitation for the MCLA, inspiring them to produce more animations for the indigenous Australian communities without compromising on quality. The R@CMon team will continue to support the MCLA going forward and will be there when the time comes that the farm needs more power. The MCLA is composed of Dr John Bradley, Dr Shannon Faulkhead, Brent D McKee, Dr Tom Chandler and Chandara Ung.

VISIONET on R@CMon (Update)

Back in early 2014, the R@CMon team assisted SBI Australia to deploy the VISIONET (Visualizing Transcriptomic Profiles Integrated with Overlapping Transcription Factor Networks) visualisation web service on the Monash node of the NeCTAR Research Cloud. Since then, VISIONET has been further enhanced to support more complex transcription factor network topologies. To date, VISIONET has been published in two papers.

Nim, H.T., Boyd, S.E., and Rosenthal, N.A. (2014). Systems approaches in integrative cardiac biology: Illustrations from cardiac heterocellular signalling studies. Progress in Biophysics and Molecular Biology 117, 69-77.

Nim, H.T., Furtado, M.E., Costa, M.W., Rosenthal, N.A, Kitano, H., and Boyd, S.E.. (2015). VISIONET: intuitive visualisation of overlapping transcription factor networks, with applications in cardiogenic gene discovery. BMC Bioinformatics.

The R@CMon team will continue supporting SBI Australia with its plan to further develop the VISIONET web service this year.

Rail Network Catastrophe Analysis on R@CMon

Monash University, through the Institute of Railway Technology (IRT), has been working on a research project with Vale S.A., a Brazilian multinational metals and mining corporation and one of the largest logistical operators in Brazil, to continuously monitor and assess the health of the Carajás Railroad Passenger Train (EFC) mixed-use rail network in Northern Brazil. This project will identify locations that produce “significant dynamic responses” with the aim for proactive maintenance to prevent catastrophic rail failure. As a part of this project, IRT researchers have been involved in (a) the analysis of the collected data and (b) the establishment of a database with visualisation capabilities that allows for the interrogation of the analysed data.
irt-vale-vis-01

GPU-powered DataMap analysis and visualisation on R@CMon.

Researchers use the DataMap analysis software for data interrogation and visualisation. DataMap is a Windows-based client-server tool that integrates data from various measurements and recording systems into a geographical map. Traditionally they have the software running on a commodity laptop with a dedicated GPU connecting to their database server. To scale to larger models, conduct more rigorous analysis and visualisation, as well as support remote collaboration, the system of tools needed to go beyond the laptop.
The R@CMon team supported IRT in deploying the software on the NeCTAR Research Cloud. The deployed instance runs on the Monash-licensed Windows flavours with GPU-passthrough to support DataMap’s DirectX requirements.
irt-vale-vis-02

GPU-powered DataMap analysis and visualisation on R@CMon.

Through the Research Cloud IRT researchers and Vale S.A. counterparts are able to collaborate for modelling, analysis and results using remote access to the GPU-enabled virtual machines.
“The assistance of R@CMon in providing virtual machines that have GPU support, has been instrumental in facilitating global collaboration between staff located at Vale S.A. (Brazil) and Monash University (Australia).”
Dr. Paul Reichl
Senior Research Engineer and Data Scientist
Institute of Railway Technology

VISIONET on R@CMon

VISIONET (Visualizing Transcriptomic Profiles Integrated with Overlapping Transcription Factor Networks) is a visualisation web service for cellular regulatory network studies. It’s been developed as a tool for creating human-readable visualisations of transcription factor networks from user’s microarray and ChiP-seq input data. VISIONET’s node-filtering feature provides a more human-readable large networks visualisation compared to CellDesigner and Cytoscape

Gata4_Tbx20

Gata4-Tbx20 transcription factor network.

R@CMon helped SBI Australia in porting the VISIONET web service into the NeCTAR Research Cloud, enabling rapid development and customisation. VISIONET’s .NET-based framework is now running on a Windows Server 2012 instance inside R@CMon, and it’s now using persistent storage (Volumes) for storing large generated network visualisations. VISIONET is now publicly available to biologists, and user traffic is expected to grow in the near future.