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How COVID-19 Has Changed Data Sharing

One effect of COVID-19 has been a hesitant acceptance of the need for data sharing. In South Korea, a policy of “aggressive data collection”, according to a recent article in IoT World Today, “has proven to be largely effective in curbing infection without closing businesses or mandating universal quarantines.” Legislators in Europe and the United States have been reluctant to follow this example, in part because of public resistance to the perceived threat of mass surveillance.

A few months ago, a petition was received in Westminster from the Ada Lovelace Institute arguing that a dangerous precedent could be established “if things were rushed in the rollout” of contact-tracing apps. That week’s Financial Times quoted from an open letter on behalf of various academics around the world who were “concerned that some ‘solutions’ to the crisis may, via mission creep, result in systems which would allow unprecedented surveillance of society at large.”

But more recent concerns have been pragmatic, temporal. Efforts to integrate inputs from connected devices like smart watches and CCTV cameras have highlighted the centrality of IoT to an aggressive virus mitigation strategy. As social distancing requirements are eased, the need for some form of contact-tracing becomes clear: to facilitate testing, tracking, isolation and treatment.

In “Contact Tracing Accelerates IoT Opportunities and Risks”, Massimo Russo and Tian Feng suggest three main benefits to data sharing that will be relevant over the coming months. First,

Data sharing can promote innovation.[1]

Governments around the world are making COVID-19 data freely available for open scientific enquiry in order to encourage the development of novel solutions. Russo and Feng have written specifically about data sharing in smart cities, pointing out that just as companies operating across multiple industries have developed data-sharing platforms to allow third parties to develop additional services, so Estonia, India, and the Netherlands have hosted remote gatherings to “hack the crisis”, leading to breakthroughs in app development and fraud prevention. Second,

Aggregated data can generate insight.

This could be stated negatively as – “disaggregated data precludes insight”. In care homes across the UK there has been almost no access to data that can help prevent the spread of infection, and there is little data sharing between social care facilities and the NHS, making it hard to track patient health from one facility to another. Andrew Morris, director of Health Data Research UK, has called the lack of data-driven infrastructure in social care a “catastrophe”.[2] Data-driven insight will be extremely important in saving lives: connected thermometers can share fever and location data; point of sale data can supplement smart phone usage to track those who test positive. Third,

Data can ultimately find uses very different from the original application.

Software innovations are invariably repurposed: the developers of blutooth probably never thought that their new technology would some day be used in virus control, and in much the same way, there are unseen possibilities from aggregating IoT and other data.

[1] https://www.bcg.com/publications/2020/contact-tracing-accelerates-iot-opportunities-and-risks-2

[2] https://diginomica.com/health-data-chief-says-uks-data-deficit-social-care-during-covid-19-catastrophe

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