Exploiting the power of Big Data

Transcription

1 Exploiting the power of Big Data Timos Sellis School of Computer Science and Information Technology ITECHLAW Asia-Pacific Conference, February 26-28, 2014 Melbourne Australia

2 Timeline of Big Data A decade before 3 dimensions of data MapReduce origins Digital universe = 130 exabytes Growing of social networks The creation of the WWW Volume Velocity Variety MapReduce: Simplified Data Processing on Large Clusters Appeared in: OSDI'04 Owned: Paypal Skype StubHub Kijiji ITECHLAW, February

3 Timeline of Big Data billion in use initiative initiative Towards a data-driven economy Digital universe = 40,0000 exabytes Location- based services $200 million investment in R&D Next slide Expand the scope of Big data from marketing applications 70% of mobiles with GPS capabilities Future impact IBM adds Veracity to the Big Data definition ITECHLAW, February

4 Australian Big Data Initiatives How is Big Data visualised in Australia? a supportive technology for the next 10 to 20 years in medicine, urgent response systems, monitoring systems and social media Australian Academy of Science, 2013 the opportunity value is estimated in $3.8 billion PwC Australia, 2012 ITECHLAW, February

5 Australian Big Data Initiatives Defence System Innovation Centre Geothermal exploration Data analytics for natural sciences Medical sciences Smart farming Financial analytics Situation awareness Big data strategy led by the ATO Other universities and companies are planning Big Data projects ITECHLAW, February

6 A close up at our research and projects RMIT AND BIG DATA: FIRST STAGE ITECHLAW, February

7 We investigate 5 main areas of research that can empower information within an organisation Complex data analytics Highly streaming data Data integration Data access Infrastructure and architectures ITECHLAW, February

8 We investigate Complex data analytics: algorithmic techniques for modelling high dimensional data, large graphs, diverse and complex (interrelated) data. Highly streaming data: algorithms that efficiently manage streaming data from social networks, positional sensors or mobile app data. ITECHLAW, February

9 We investigate Data Integration: semi-automatic techniques that assist users to annotate and subsequently combine data from different sources. Data Access: mechanisms that effectively manage security, privacy, provenance, queries Infrastructure and architectures: Cloud computing, distributed systems, p2p systems, ITECHLAW, February

10 Our projects Healthcare applications Monitoring data from elderly patients Secure access of electronic health records in the cloud. Smart cities applications Smart metering of power grids Protection against cyber-attacks of monitoring systems. Intelligent transportation systems ITECHLAW, February

11 Our projects Resource management Mining industry A potential application: real-time monitoring of equipment to schedule maintenance problems Situation awareness Emergency response systems involves: the perception of the elements in the environment, the comprehension of the current situation, and the projection of future states (prediction) ITECHLAW, February

12 Privacy and Provenance Of special interest wrt legal issues Privacy-aware applications Can I change applications to preserve privacy? Prevent instead of react Example: location is not disclosed; instead send an approximate location Data Provenance the Ws Who, When, Where, What. Data citation ITECHLAW, February

13 Final remarks Several companies struggle with making sense of and creating opportunities from their data (the data economy). Big Data is a key factor for enterprises. Big Data has a transformative potential in a wide range of areas, and interesting, new, legal issues are raised. ITECHLAW, February