Applying data science

Answering society’s most pressing questions

In an increasingly data-driven age, governments, organisations and researchers are questioning how to harness the good that can come from responsible use of data while at the same time minimising inherent risks to individuals, groups, and society at large.

By leveraging its position as a world leader in social science research, LSE aims to develop the necessary tools for analysing large data sets and to answer questions regarding how organisations can make well informed data-driven decisions.

A Data Science Initiative at LSE will support interdisciplinary data science research and teaching across the School’s academic disciplines. It will form a hub for researchers to collaborate on data-driven research to address major challenges to governments, businesses and society.

Some examples of the use of data science are below.

Better health outcomes
Data science has the potential to transform the healthcare sector, whether through defining and accessing relevant data, or increasing patient engagement through digital solutions. LSE Health is working with China’s National Center for Cardiovascular Diseases (NCCD) on leveraging data sets and health surveys to evaluate the effectiveness of treatment methods and settings, ultimately aiming to better support governmental action in addressing major burdens of disease. LSE Health is also leading a pan-European initiative that will provide methodological guidance to a range of disease-specific projects. Working with public and private partners, LSE will lead on common practices in data collection and usage, working to set the agenda for future investment in this area.

Understanding uncertainty in environmental modelling
Modelling and simulation are an increasingly important part of modern science, especially in highly policy-relevant disciplines such as weather, climate and hydrology. Good practice in the use and interpretation of models is therefore vital, both for sound science and for informing evidence-based policy decisions. LSE’s Centre for the Analysis of Time Series (CATS) sits at the heart of this approach to data analysis. Researchers in CATS have done groundbreaking research on climate science, energy futures, mathematical chaos, medical signals analysis, and weather forecasting, among other things. CATS has active partnerships with EDF Energy, Lloyd’s of London, the National Centre for Atmospheric Research, the Royal National Lifeboat Institution, and The Start Fund.

Systemic risk and massive official data sets
The global financial crisis has renewed academics’ and policymakers’ interest in understanding the nature of the danger posed by the financial system to society, in particular how financial risk is endogenously generated in the marketplace and can be hidden from authorities until too late. Yet research is stymied by the practical challenges of analysing the massive available data on the activities of financial institutions. The Department of Finance and the Systemic Risk Centre (SRC) are working with a number of central banks, supervisors and private sector companies to help them overcome this technical barrier; using data – from public to highly confidential – to increase understanding of financial risk, to clarify the network of interconnections between financial actors and to formulate more robust macroprudential policies.

How cities perform Global urban growth is increasing the challenge of governing cities. At the same time, there is little data on how cities are governed and what capacity they have to address complex and interrelated economic, social and environmental challenges. LSE Cities is analysing and mapping official data sources to reveal cities’ social, governance, planning, transport and environmental patterns, determining whether they have the necessary capacity or if new arrangements are required to ensure cities are able to play a fundamental role in reducing global energy demand and limiting carbon emissions, as well as responding to issues of social inclusion. The Centre, through the Urban Age Programme, further investigates how the physical and social are interconnected in cities, comparing those in rapidly urbanising regions in Africa and Asia, as well as in mature urban regions in the Americas and Europe.

Rationale

Big data is transforming almost every aspect of science, engineering, geography, and medicine, from mapping genes to exploring galaxies. In the study of human affairs, there is an emerging ‘data society’, in which increasingly comprehensive aspects of human behaviour and the economy are quantified through data.

Data science is a discipline concerned with the processes and systems required for extracting knowledge and insight from data sets, which are then translated into meaningful action. This data can come in many forms: it can be structured or unstructured, and its scope and scale can vary dramatically. The theoretical foundations of data science often lie at the intersection between statistics, mathematics and computer science.

As data science becomes increasingly influential, inevitably there will be significant levels of national and global debate over how best it can be used for the understanding and development of economies, governments and societies. The London School of Economics and Political Science (LSE), with its distinctive range of globally recognised specialisms across the social sciences, is perfectly positioned to lead this debate.

LSE’s Data Science Initiative will serve as a research nexus for social scientific study that addresses the central problems of the emerging data society, how data science, communications, sociology, economics, politics, law and policy studies can work in partnership, and how to position data as a force for good in society.

With the means to connect technical skills with social science expertise, LSE is perfectly positioned to harness the big data that will revolutionise our understanding of society’s most important questions and provide a scientific basis for data-informed decision making.

We also see a huge market for education in data science and analytics, and believe the LSE is well-positioned to capitalize on this potential. We see scope for new degrees in:

  • Management: A possible new Masters of Business Analytics
  • Inter-departmental: Executive education programmes in data science and business analytics
  • Summer School: Data Science methods intensive two-week (already held since 2015) and one-week executive courses

Further to the above, we are launching an MSc in Data Science and an MSc in Operations Research and Analytics commencing in September 2017. The MSc in Applied Social Data Science will commence in September 2018. Further information can be found on the Study page.