08:30am – 08:55am	Registration
08:55am – 09:00am	Introduction
09:00am – 10:00am	Topic: From spatial data to Spatial Big Data Prof Hervé Martin Laboratoire d’Informatique de Grenoble, France
10:00am – 11:00am	Topic: Advanced Analytics – Debt Experience at the ATO Dr Maninder Bhatia Australia Taxation Office, Australia
11:00am – 11:30am	Morning tea
11:30am – 12:30pm	Topic:Advanced Analytics – Innovation and Practices Prof Longbing Cao Advanced Analytics Institute, UTS
12:30pm – 01:30pm	Lunch
01:30pm – 02:30pm	Topic: Mining Social Media: Big Data, New Challenges. Prof Huan Liu Arizona State University, USA
02:30pm – 03:30pm	Topic:The Role of Machine learning in Big Data with probabilistic Classification Models Prof Rao Kotagiri University of Melbourne, Australia
03:30pm – 03:45pm	Afternoon Tea
03:45pm – 05:15pm	Dean’s Forum Moderator: Dr Usama Fayyad, Barcley, UK Panelists: Dr Usama Fayyad, Barcley, UK Prof Huan Liu, Arizona State University, USA Prof Hervé Martin, Laboratoire d’Informatique de Grenoble, France Prof Chuanrong Li, CASOAE, China Prof Rao Kotagiri, University of Melbourne, Australia Prof Geoff Webb, Monash University, Australia Prof Simeon Simoff, University of Western Sydney, Australia A/Prof Yan Li, University of Southern Queensland, Australia Prof Andy Koronios, University of South Australia, Australia Prof Athman Bouguettaya, RMIT, Australia Prof Wray Buntine, Monash University, Australia Dr Warwick Graco, ATO Prof Jianping Yin, NUDT, China Topic: Data Science – Challenges and Future   Topics to be debated may include but not limited to: Do we need a new field “data science”, since we already have “information science” and other related fields? What is the future of data-based economy and what do universities need to do now? Do we need a new bachelor and/or master degree for “data science” and analytics? What are the skill/competency gaps in our current graduates from relevant areas including computer science and statistics? How can data science research incorporate inputs from industry and government, and address the practical challenges and skill shortage they are facing? How can we improve our teaching curriculum to make our graduates more competitive and work-ready for data economy?
05:15pm – 05:30pm	Prof Geoff WebbWrap Up
05:30pm – 06:45pm	Refreshment & Networking

2014 Big Data School

This Big Data School session (27 Oct 2014, Sydney) is to offer audience with latest advancements in data science, data mining, machine learning, and advanced analytics for relevant domains through several prestigious lectures to be given by very senior professionals. This year, we have topics to cover areas including

• Advanced analytics
• Social media analytics
• Sentiment analysis
• Spatial big data analtyics
• Best practices in major public sector
• Latest development in advanced analytics research and practices

Dean’s Forum on Data Science

This Dean’s Forum on Data Science session is a premier platform for

• Deans in IT, Business, Health, Science etc.
• Heads of Schools in IT, Business, Health, Science etc.
• Research leaders
• Senior education managers and executives, and
• Senior market players in big data analytics in industry and government

to share views and ideas, and to debate the demand, trends, challenges, and opportunities about strategic issues, topics and perspectives such as

• We have information science, why do we need data science?
• Do we need a degree of analytics and data science?
• What should be the knowledge map and competency for a quality data modeler or analytics manager?
• What are the gaps in the existing curriculum and knowledge delivered to students?
• What are the requirements and gaps seen in real-life best practices?
• What makes the next-generation analytics talent special in driving the data economy and data-driven decision making?

You are seeing Deans, HoSs, Research Directors, and senior chief officers from major universities, industry and government in Australia, China, France, India, USA and UK to address the Dean’s Forum.

Comments to the Panelists?

Please send your comments and questions to the Panelist bigdatasummit@uts.edu.au.