According to The Economist (2017, p. 7), “the world’s most valuable resource is no longer oil, but data”. Together with the rapid advancements of technology, including Artificial Intelligence, and a fundamental respect for scientific methods among political decision makers, data can help global society tackle challenging events.

In this video, you will meet Dr Bissan Al-Lazikani from the Institute of Cancer Research in London, who reflects on how big data can contribute to cancer drug discovery. Even if you don’t work in biology or medicine, we strongly encourage you to watch it. 

Video originally created by SevenC3 for Fujitsu’s I – Global Intelligence for Digital Leaders (I-CIO.com), https://i-cio.com/   

The Covid-19 pandemic that hit the world in 2020 proved to us all that rapid and broad knowledge sharing is of vital importance when faced by global threats and crises. Leading scholars across the globe encourage peers to also embrace this research practice in other fields of research, given that legal, ethical, and security-related conditions allow it*.

The masses of data that are generated every day may serve to better anticipate and respond to “black swan events” such as Covid-19, but they may also serve to foster organisational or commercial innovation and the quality of decision-making on a general basis (Sheng et al., 2020). But if society is to benefit maximally from big data, a recognition of the methods employed in big data analytics is required. Sheng et al. (2020) list four techniques:

  • Descriptive analytics: Analysis of past data to provide an overview of potential patterns or trends embedded in data.
  • Diagnostic analytics: Provision of a historical account from which problems and opportunities within existing operations can be identified.
  • Predictive analytics: Usage of statistical techniques to analyse current and historical facts to make predictions about future events and/or behaviour.
  • Prescriptive analytics: Usage of data to decide actions and evaluate their impact.

Dealing with big data requires a high level of knowledge and skills relating to research methods, research data management, and technology. Many big data studies combine different sources of data, for instance both structured and unstructured data, which again requires a hybrid of different methods for data processing and analysis. The complexity of the data may be best tackled by combining different analytical techniques.

As you may recall from the section on the long tail of research, big data studies are often performed by large research teams (i.e. the head of the curve), meaning that each member of the team may specialise individually and contribute on a determined set of tasks.


A telling data visualisation based on big data

In this animation, you can see how large amounts of historical climate data can be translated into an animation, which leaves no doubt that something needs to be done to decelerate global warming. Read more about the story behind the animation in Mooney (2016).

Global temperature change 1850-2017

Figure: "File:20171231 Climate spiral (HadCRUT4.6 1850- ) Ed Hawkins.gif" by Ed Hawkins (climate scientist at University of Reading) is licensed under CC BY-SA 4.0

Food for thought
Is data the new oil? Read the citation below and make up your mind:

Data analytics offers important and significant opportunities for scholars across the developed and developing economies, interested in studying future employment trends, global crises and their impact on innovation and knowledge sharing, business resilience driven by the digital and analytics capabilities, and the future functioning and sustainability of global supply chains. (Scheng et al., 2020, p. 15)

References

*On this matter, if you’re interested in learning about data protection in the middle of a pandemic, we encourage you to have a look at the report written by SDSN TReNDS and DataReady Limited (2020) - see the reference and link above.


Last modified: Tuesday, 20 December 2022, 8:46 AM