How HK can unleash the power of big data

December 20, 2016 09:26
Big data is a treasure trove that invites creative analytics to improve the wellness of populations.  Photo:

Big data has become one of the top buzzwords of our times. Indeed, we are living in an age of data explosion, what with the proliferation of smartphones and other mobile devices, smart dust and cloud-based services.

The unstoppable rise of these technologies calls for the discovery, analysis and communication of meaningful patterns in the sea of data that they generate.

Achieving this understanding is important if we are to harness the power of big data, which can inform better decision-making in a variety of fields from commerce, transport planning and education to public health and pollution control.

Big data tends to focus one’s attention on volume. Yet, to fully appreciate the opportunities that are in store, that idea has to be substantially expanded.

Initial trickles of data can accumulate fast and take on a new level of significance, and that element of velocity, together with variety, veracity, value, and volume, form the five "Vs" driving big data.

There is always value to uncover in data, and the creative application of big data should be concerned with improving the wellness of populations.

Wide-ranging data from any specialty domains can benefit from the big data methodology.

For instance, an empowered architect who designs spaces that are conducive to the well-being of users will be able to effectively marshall data such as temperature, UV exposure, ventilation, indoor pollution and so forth.

Similarly, real-time locational data from public transport vehicles running on the busy roads of Hong Kong can be analysed to prompt any instant adjustments that may have to be made to the service schedule to ensure the optimal delivery of services.

In Hong Kong, an Open Data Studio has been set up at the Science Park to promote big data.

Building on that good basis, the long-term growth and success of big data has to be driven by closer strategic collaborations between the government, universities and industry. That is essential if Hong Kong is to be a smart city.

Technologically, the conditions are ripe for increased partnerships across sectors to thrive as advancements in big data analytics means that previous difficulties in processing large and complex data-sets can now be overcome and inspire concrete policymaking.

A case in point is a major international cancer research project by the Big Data Decision Analytics Research Center at the Chinese University of Hong Kong, which was able to study incidence data for 27 cancer types from 102 cancer registries worldwide with new data analytics technologies.

This creative attempt to exploit big data to identify cancer trends is undertaken by the university’s researchers, with support from IBM China/Hong Kong Ltd., as they combined to analyse 20 years of cancer data from the International Agency for Research on Cancer.

Findings from this research project will inform policymakers on how to use limited healthcare resources to make the biggest impact in the fight against cancer.

As big data use grows, concerns over data security and privacy will have to be better addressed.

Given that Hong Kong has a relatively high awareness of data security and privacy, more suitably trained professionals are therefore needed to allay industry concern over data security risks.

Finally, to meet the well-recognised industrial demand for data scientists, specialised education in big data will need to increase.

But rather than turning big data into an independent discipline, any big data education program should include a collection of courses across disciplines such as statistics, computer science and operations research, and integrated with domain expertise.

As the physical world turns increasingly networked, there is plenty to gain if the government, academia and businesses can work more closely together to make visible and master the "invisible" force of big data that powers the age we live in.

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Director of the Stanley Ho Big Data Decision Analytics Research Centre at The Chinese University of Hong Kong