ALA Tracks Application for Community Group Data Collection

Mr Sathish Babu Sathyamoorthy1

1Csiro, Clayton, Australia

Title ALA Tracks Application for Community Group Data Collection
Synopsis The Tracks App allows you to collect information on tracks and other sign (scats, diggings, burrows, bones, and feathers). Information will be used to map Country where native animals are found. With lots of Indigenous Ranger groups in remote areas, app will be able tell a better story on what is happening to animals in these areas of Australia.
Format of demonstration Slide Show, Live Demonstration
Presenter(s) Sathish Sathyamoorthy, Technical Specialist, Atlas of Living Australia.
Target research community Biodiversity and Ecologists
Statement of Research Impact Data collections platform fills a very significant gap in capability to support the growing needs of both scientists wanting to engage the public in their research and the public wanting to participate in important scientific work, including collecting their own observation data.

Biography:

Sathish is part of the Atlas of Living Australia (ALA) team in CSIRO. He has experience in providing end to end internet solutions to real world problems for both web and mobile platforms. Sathish can help you to get an access to wealth of information about Australia’s biodiversity data which includes 55.6 million records. Email the team at support@ala.org.au

ecocloud – a micro service data enhanced virtual laboratory

Mr Gerhard Weis1

1Griffith University, Meadowbrook, Australia

 

Title ecocloud – a micro service data enhanced virtual laboratory
Synopsis ecocloud built as a micro service architecture, creates a platform that enables efficient use of hybrid cloud and HPC resources. The main focus is on providing an interactive compute platform, with streamlined data access and usage, enabling reproducible research and collaboration nationally and internationally.

Main tools provided are Jupyter Notebooks and RStudio in a fully personally customizable environment. The architecture is not limited to these tools, and can be easily extended, with a future focus on letting users add additional tools and / or services. Being built with micro services, and fully OAuth enabled means that every feature and service can be consumed by third party tools/applications. ecocloud’s scalable base line infrastructure and services, with commonly used standard tools, gives the opportunity to enhance collaboration between researchers, students and research software engineers, and other data enhanced virtual laboratories.

Format of demonstration Slide Show; some short live demonstrations
Presenter(s) Gerhard Weis, Senior Software Engineer, Griffith University
Target research community Eco Sciences, Cloud Solutions Engineers
Statement of Research Impact Ecocloud provides the infrastructure and tools, for all sorts of eco science related research, teaching and software development, but is not limited to the eco science research community.

Biography: 

Senior Engineer at Griffith University with a background in distributed systems and software architectures. He has worked with the NeCTAR research cloud since the early beginnings and has a passion for reliable, self healing systems and automation.

Field Acquired Information Management Systems Project: FAIMS Mobile, a customisable platform for data collection during field research

Dr Adela Sobotkova1, Assoc/Prof Shawn Ross1, Dr Brian Ballsun-Stanton1

1Macquarie University, North Ryde, Australia

 

Title Field Acquired Information Management Systems Project: FAIMS Mobile, a customisable platform for data collection during field research
Synopsis FAIMS Mobile is open-source, customisable software designed specifically to support field research across many domains. It allows offline collection of structured, text, multimedia, and geospatial data on multiple Android devices, and is built around an append-only datastore that provides complete version histories. It includes customisable export to existing databases or in standard formats. Finally, it is designed for rapid prototyping using and easy redeployability to reduce the costs of implementation. Developed for ‘small data’ disciplines, FAIMS Mobile is designed to collect heterogenous data of various types (structured, free text, geospatial, multimedia) produced by arbitrary methodologies. Customised by an XML-based domain specific language, it supports project-specific data models, user interfaces, and workflows, while also addressing problems shared across field-based projects, such as provision of a mobile GIS, data validation, delivery of contextual help, and automated synchronisation across multiple devices in a network-degraded environment. Finally, it promotes synthetic research and improves transparency and reproducibility through the production of comprehensive datasets that can be mapped to vocabularies or ontologies as they are created.
Format of demonstration Slide Show
Presenter(s) Dr Adela Sobotkova, Research Associate, Department of Ancient History, Macquarie University and Co-Director, FAIMS Project.

A/Prof Shawn A Ross, Director of Data Science and eResearch, Macquarie University and Co-Director, FAIMS Project.

Dr Brian Ballsun-Stanton, Research Associate, Department of Ancient History, Macquarie University and Technical Director, FAIMS Project.

Target research community Researchers in fieldwork disciplines where people (rather than automated sensors) collect data, e.g., archaeology, biology, ecology, geosciences, linguistics, oral history, etc.
Statement of Research Impact FAIMS Mobile has changed users’ daily practice. Case studies indicate that users benefit from the increased efficiency of fieldwork (the time saved by avoiding digitisation more than offsets the time required to implement the system). Born-digital data avoided problems with delayed digitisation, which often occurred long after field recording when the context of records had been forgotten. Researchers reported more complete, consistent, and granular data, and that information could be exchanged more quickly between field researchers and lab specialists, facilitating the evaluation of patterns for meaning. They also observed that the process of moving from paper to digital required comprehensive reviews of field practice, during which knowledge implicit in existing systems to become explicit and data was modelled carefully for the first time.

Biography:

Adela Sobotkova is a landscape archaeologist who combines pedestrian field survey with digital methods to study the long-term history of the Balkans and Black Sea region, with focus on the evolution of social complexity. Adela is a co-director of the FAIMS project and an incoming assoc/prof of Digital History at the Aarhus University, Denmark.

Cloud Resource Allocation Management System (CRAMS)

Mr Samitha Amarapathy1, Mr Stephen  Dart1, Ms Kerri  Wait1

1Monash eResearch Centre, Monash University, Melbourne, Australia

Title Cloud Resource Allocation Management System (CRAMS)
Synopsis The Monash University developed Cloud Resource Allocation Management System (CRAMS) is for resource allocation, instantiation and to report resource utilisation across Research Data Storage,  High Performance Computing Platform (HPC), Research Computing Cloud and Virtual Desktop Infrastructure.  CRAMS not only enables researchers to request access to resources across  research storage, cloud and  HPC allocations, it also collects project details across all allocations over time to form a rich metadata registry. CRAMS is a production system that is meeting key milestones of its transformation-driven road map. The agile delivery of CRAMS has already released the “Data-Dashboard” which replaces both the manual and paper-based user request form and the VicNode Reporting System for Monash.  As of today, every researcher interaction about storage at Monash is intertwined with the pathway to open-data, the pathway to retention & disposal, and the pathway to optimising tiers of storage.

 

In this presentation, we will give a quick overview of CRAMS, and give some demonstrations of user and facility workflows across storage, HPC, CVL and cloud.

Format of demonstration  Slide Show and Live Demonstration
Presenter(s) Samitha Amarapathy, CRAMS-Project Lead & Senior Project Manager, Monash eResearch Centre, Monash University

 

Stephen Dart, Research Storage Manager, Monash eResearch Centre, Monash University

 

Kerri Wait,  High Performance Computing Consultant, Monash eResearch Centre, Monash University

 

Target research community Research Data Storage,  High Performance Computing Platform (HPC), and Research Computing Cloud
Statement of Research Impact CRAMS will provide an effective self service mechanism for researchers and research facilities  to request cloud resources, monitor usage and manage own allocations.  CRAMS will further enable faster processing of resource allocation requests and provisioning of resources to end users. CRAMS reporting will enable effective strategic decisions on resource planning across Monash Research Data Storage, High Performance Computing Platform and Research Computing Cloud to address research needs better.

Biographies:

Samitha leads the agile driven application development capability at eResearch and lead and manages IT projects of strategic importance to eResearch including the delivery of CRAMS program of work, MyTardis based implementations in research instrument integration space, projects for research platforms and projects for Australian research cloud –NeCTAR.

Stephen is currently the Research Storage Manager within the Monash eResearch Centre. His key role is the delivery of storage services to the researchers at Monash University and Reserach Platforms they depend on. Stephen has provided his expertise in IT storage management over four decades, to Monash and the wider Victorian research community.

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.

Accelerate Scientific Discovery Using Modern Storage Infrastructure

Mr Dave Hiatt1
1WekaIO, San Jose, United States

Title Accelerate Scientific Discovery Using Modern Storage Infrastructure
Synopsis This Solutions Showcase session will have a brief discussion of the challenges faced by traditional data storage systems. It will introduce a software-based storage system that overcomes these challenges and supports modern workloads such as AI and deep learning data sets that consist of large and small files and random and sequential I/O at cloud scale. Emphasis will be on a demo of an operational system that can be deployed on premises or in the public cloud and that enables new use cases and deployment models.
Format of demonstration Live Demonstration
Presenter(s) David Hiatt, Dir. of Strategic Market Development, WekaIO
Target research community All areas of research that are data intensive
Statement of Research Impact The pace of scientific discovery hinges on the ability to capture, collect, analyze, and visualize data in a timely fashion. Research data sets pose unique challenges for storage systems in both size and density. This software-based storage system allows data to be shared amongst researchers and provides over two times higher performance than data on local SSD storage.

Biography:

David Hiatt is the Director of Strategic Market Development at WekaIO. Throughout his career, Hiatt has specialized in enterprise IT, business and healthcare. Previously, he led healthcare and life sciences activities for HGST and Violin Memory. He has also been a featured speaker on storage related topics at numerous life sciences events. Hiatt received an MBA from the University of Chicago.

 

R Shiny – customising data exploration apps for researchers

Dr Rebecca Lange1
1Curtin University, Bentley, Australia

Title R Shiny – customising data exploration apps for researchers
Synopsis There are many computational bottlenecks slowing down or preventing scientific discovery for many researchers across all fields. In this new era of big data, data analysis practices need to scale to the volume of data processing and analysis needed for researchers to compete in a world-class arena.

In this showcase I will present two examples of implementing the R Shiny web app framework to help researchers with their data exploration, analysis and dissemination. This approach is especially useful to researchers who are new to big data and have limited or no programming skills to analyse this kind of data influx. The first Shiny app I will demonstrate was developed to support the Multimodal Analysis Group at Curtin University in their study of Online Extremist Communications. The second Shiny app I will demonstrate was built to share and explore data generated from a study of temple architectures across south-east Asia.

Format of demonstration Live Demonstration + Slide Show
Presenter(s) Dr. Rebecca Lange, Data Scientist, Curtin Institute for Computation
Target research community Humanities and all other areas interested in making their own dashboards
Statement of Research Impact Researchers have been able to utilise the custom build R Shiny apps to investigate key research questions that would not have otherwise been possible. For example, researchers have been able to study how extremist communication works and changes over time and how their propaganda images are spread.

Biography:

Rebecca Lange received her PhD in astronomy from the International Centre for Radio Astronomy Research at the University of Western Australia.

Before Rebecca moved to Australia she studied Astronomy and Physics at Nottingham Trent University where she also worked as a research assistant in scientific imaging for art conservation and archaeology. Her work there included the development and testing of instruments and software for imaging and spectroscopy as well as the organisation and supervision of field trips, which often required liaising with art curators and conservators.

Throughout her studies and research Rebecca has gained extensive programming as well as data analytics and visualisation experience in various programming languages.

Currently she is working as a data scientist for the Curtin Institute for Computation where she helps researchers by providing data analytics and computational support and training.

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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