Geospatial data and ethics

What is geospatial data and why does it matter?

Geospatial data, also known as “location data” or “spatial data”, is data that represents where people or objects are in relation to the Earth’s surface, whether in the air, on the ground, at sea or under our feet*. Whether it is man-made or natural, if it is related to a specific location on the globe, it is geospatial. These data can relate to events, objects or people and can be static (such as a person’s address or the location of a school) or dynamic (such as a bus travelling along its route).

The vast majority of the data we use in producing statistics can be located – tied to addresses, postcodes or local areas – or with GPS (Global Positioning Systems) to more precise locations.

The use of geospatial data in research and statistics provides substantial benefits, providing new means of integrating, analysing and interpreting information for the public good. These data allow us to locate services such as schools and hospitals and to plan local transport and housing. They allow us to monitor weather and traffic events and plan flood defences. Geospatial data and tools have proven vital in managing the response to the COVID-19 pandemic.

What are the ethical issues?

Nonetheless, although the use of geographic data and methods bring real value, there are also ethical and privacy issues which need to be considered. Geospatial data brings with it ethical considerations common to all types of data – but also some of its own. Since data often locates individuals, addresses or businesses and because it is often sourced from ‘personal’ devices such as mobile phones, geospatial data may be considered by the public to be a somewhat special or intimate type of data.

This is particularly relevant since locational information is ubiquitous in modern society – we carry personal smart devices, we drive cars which are located by GPS or are captured on CCTV and other sensors. Such applications are certain to increase and new technologies are sure to continue to raise new ethical questions.

While these applications all bring real benefits in terms of efficiency, convenience, and safety they also bring risks. By taking a considered approach to ethics in every project, we can mitigate risks and retain public trust in the use of data for research and in statistics, both in geospatial contexts and more generally.

*The definition of geospatial data used in this guidance is based upon that used in the UK Geospatial Strategy.

General ethical principles for research and statistics

To help researchers and statisticians navigate potential ethical issues for all types of projects, the UK Statistics Authority has developed a series of ethical principles and a related ethics self-assessment tool.

At a basic level, these principles focus on ensuring the public good of research and statistics, maintaining confidentiality of data, understanding the potential risks and limitations in new research methods and technologies, compliance with legal requirements, considering public acceptability of the project, and transparency in the collection, use and sharing of data.

How geospatial relates to the ethical principles

Ethical issues related to the use of geospatial data can be mapped to these core ethical principles and the list below provides an overview of the ways in which geospatial issues particularly relate.

The ethical principles provide guidelines for dealing with all types of data and you should consider your project against each of these principles early and throughout your work – particularly when planning data collection, choosing methods and deciding how you will produce outputs.

You can find more details here: ethical principles

These guidelines will touch on these general points but focus more on areas where the geospatial nature of the data requires us to take particular care.

These include:

• The need to carefully consider the confidentiality and disclosure risk from geospatial data;
• The need to ensure the inclusivity of geospatial data;
• The importance of avoiding bias and discrimination based on location;
• The need to ensure that the way you present your geospatial outputs are fair and as representative of the truth as possible.