LawTech and the building of eResearch capability in the interdisciplinary domain of legal natural language processing

Mr Geordie Zhang1

1The University Of Melbourne, Parkville, Australia

In this talk, we present the experiences of developing a brand new interdisciplinary research program at the University of Melbourne, LawTech, from the perspective of Melbourne Data Analytics Platform (MDAP), a new academic specialist unit at the University of Melbourne specifically designed to supercharge computationally and data intensive research at the university.  LawTech applies cutting-edge computational natural language processing (NLP) models, based on machine learning and deep learning, to the problem of classifying texts from court judgements.  As the common law legal system in Australia relies heavily on lawyers and judges reading large volumes of court judgements of previous cases, extracting the legal principles propounded in these judgements, and applying them to new cases, the development of machine-learning based technologies for computer assisted information extraction from court judgements has a profound effect on the Australian legal community, as well as legal communities from other common law countries (e.g. UK, US, India, Singapore).  This talk will cover what we have found to have been critical to the initial development of LawTech, how the different eResearch services at the University of Melbourne contributed towards the research program, the challenges along the way, the lessons learnt, and how the undertaking of such an interdisciplinary research program has changed the eResearch and researcher communities at the university who have been directly involved with LawTech.

Below is a list of research collaborators in the LawTech research programme:

Timothy Baldwin1, Daniel Beck1, Hui Chia2, Emily Fitzgerald3, Rohit Gupta3, Saket Khandelwal3, Kabir Manandhar Shrestha3, Meladel Mistica1, Jeannie Patterson2, Priyanka Pillai3, Geordie Zhang3
1School of Computing and Information Systems, The University of Melbourne
2Melbourne Law School, The University of Melbourne
3Melbourne Data Analytics Platform, The University of Melbourne


Biography:

Geordie Zhang is a Research Data Specialist at the Melbourne Data Analytics Platform (MDAP), the University of Melbourne.  His research interests include digital humanities and social sciences, computational economics, network information theory, and natural language processing.  His eResearch interests include research cloud and high-performance computing, databases for humanities and social sciences datasets, and knowledge translation in data-intensive research.

Urban Trees, Data Science and Human Wellbeing

Dr Peter Edwards1, A/Prof Bu Sung Francis Lee2, Dr Seanglidet Yean2, Dr Gradon  Diprose1, Dr Jan Schindler1, Professor  Richard Green3

1Manaaki Whenua Landcare Research, Wellington, New Zealand
2Nanyang Technological University, Singapore, Singapore
3University of Canterbury, Christchurch, New Zealand

Tree and the forests have major impact on the health of the planet and human.  As the world becomes increasingly urbanised, urban trees and forests become increasingly important for overall human wellbeing. There are plenty of studies showing the benefits of urban trees and forests from a number of specific perspectives – health, climate change, urban planning and ecology. This paper will highlight Tsit project approach to study a holistic examination of urban trees and their social and cultural impacts. Using a wellbeing framework, quantitative data from remote sensing, modelling and administrative social and cultural sources, we aim to understand the impact of urban trees across a range of wellbeing domains. Using data science and epidemiological methods, we aim to discover correlations and patterns between urban trees and human wellbeing. The initial urban city reported in this paper is Singapore and Wellington. This will create a foundation from which more specific studies can be launched.


Biography:

Bio to come

DGGS as the next generation of complex, borderless integration of knowledge in support of science and society.

Ms Irina Bastrakova1, Mr Shane Crossman1, Mr Joseph Bell1, Ms Tina Yang1

1Geoscience Australia

The pace, with which government agencies, researchers, industry and the public need to react to national and international challenges of economic, environmental and social natures, is constantly changing and rapidly increasing. Responses to the 2020 Australian bushfire crisis and the global COVID-19 pandemic events are recent examples of these requirements.

Decisions are no longer made on information or data coming from a single source or discipline or a solitary aspect of life: the issues of today are too complex. We need to re-think the approaches toward data integration, analysis, evaluation and access and to start building flexible re-usable and re-purposeful data and information solutions serving multiple domains and communities.

This presentation will provide insights into the new exiting technology, Discrete Global Grid System, and examine how its application helped Geoscience Australia to deal with the challengers of data integration from multiple disturbed sources and sectors during the Australian Bushfires 2020 and assisted with creating a vulnerability index for the Reducing Illness and Lives Lost from Heatwaves Project to inform response to heatwaves including spatially targeted interventions.


Biography:

Irina Bastrakova is a Director, Spatial Data Architecture at Geoscience Australia.

Irina has been actively involved with international and national geoinformatics communities for more than 19 years. Irina focuses her work on maximising potential of multidisciplinary data assets by leveraging common information models, data patterns and vocabularies.

Irina is the Chair of the Australian Metadata Working Group and a member of many international and national geoinformatics and standards committees.

FLOOD-PREPARED: A NOWCASTING SYSTEM FOR REAL-TIME IMPACT ADAPTION TO SURFACE WATER FLOODING IN CITIES

Prof. Stuart Barr1

1University Of Melbourne, Melbourne, Australia

Extreme rainfall events pose an ever increasing threat to cities due to the potential for surface water flooding resulting in damage to properties and major disruption of transport systems. Modern sensor networks offer enormous potential for the real-time monitoring of urban systems and potentially allow improved situational awareness of impeding hazards and their impacts such as flooding. However, monitoring in itself is not enough if we are to be able to adapt in in real-time to hazards. Systems are required that allow analytics and models, that feed of real-time observations, to make predictions of impacts and suggest adaption options ahead of the hazard event. The Flood-PREPARED project is developing a system for real-time adaption to surface water flooding. The system comprises of advanced spatiotemporal models of rainfall, surface water flooding and road traffic impacts. These models are linked and orchestrated within into a Big Data workflow that allows events to be simulated using emerging rainfall data recorded by a short range weather radar. This approach allows nowcasting to be undertaken where predictions of surface water inundation and impacts on the road network can be predicted ahead of the rainfall event reaching the city; thus providing the ability for an improved adaptive response to the actual event.


Biography:

Stuart Barr is Professor of Urban Data Science at the University of Melbourne and Director of the Australian Urban Research Infrastructure Network (AURIN). His research focuses on integrated geospatial urban-infrastructure systems analysis and modelling.

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