Democratising data: the need to make statistics more accessible to everyone

The world of statistics is changing: traditionally the domain of experts alone, new technologies and methods of communication have the potential to open up a range of different data to new audiences, and to make statistics more accessible to everyone. From 11-24 June, Wikiprogress is hosting an online discussion on the role of open data, communication and technology in making data more accessible for society at large. This blog, by Kate Scrivens, Wikiprogress Project Manager, sets out some of the key issues for the discussion.
Data of the people, by the people and for the people

For centuries, the primary purpose of government data, from the Domesday Book to the present day, has been to inform decision-making at the very highest levels. However, the last decade or so has seen an increasing movement towards ‘democratising data’, and making statistics available that are more relevant to a broader public. The shift towards a ‘beyond GDP’ mind-set, focusing on developing better and broader measures of people’s well-being, is an essential step in developing statistics that are more relevant to people’s lives. But democratising data is also about ensuring that relevant statistics are more easily accessible to a wider public.
Thanks to the internet and other innovative technologies, people can engage with data in an increasing number of ways: not only as consumers of new types of information, but also as interpreters, communicators and even producers of data.
People as data interpreters: the power of Open Data

Open data are data that people are ‘free to use, re-use and redistribute — without any legal, technological or social restriction’, according to the Open Knowledge Foundation.  By opening up previously restricted data – from government and other sources – for universal use, citizens have the chance to be much more directly involved in decision-making, and to be better informed about issues that affect their own well-being. For example, people looking to move to a new town, can compare data on air quality, schools, hospitals, or other factors that matter most to them in order to select the best place to live. They can also use the same data to shine a spotlight on areas where improvement is needed, thereby strengthening the accountability of government and other institutions.
Opening up access to data can be empowering, but not everyone has the necessary skills or patience to make the most of raw data. Open Data has the biggest impact when they are made available in an easily accessible format by people acting as ‘data interpreters’, with the necessary analytical and technical skills to re-use the data in innovative, new ways, such as creating mobile apps and other technologies. For example,, showcases a large selection of apps created using European public data, from an app to monitor carbon monoxide emissions across Europe, to one helping road users identify traffic accident hotspots. For the power of Open Data to be evenly shared across society, however, capacity-building is crucial. Organisations such as the School of Data, exist for exactly this purpose: to provide engaged citizens with the skills they need to make the most of data. For many, this kind of power shift is the true meaning of the “data revolution” (read more hereand here).
People as data communicators: visualisation and storytelling

Creating mobile apps is just one way of re-using data. An equally powerful way of making statistics more accessible to a broader audience is through the use of storytelling to convey the underlying meaning of the data. This can be done by the data producers themselves (such as government or statistical agencies) or by intermediaries such as data journalists, civil society organisations or anyone with an interest in finding the best way to communicate the key messages of datasets. Stories can be told in the traditional way, through narrative text, or they can be conveyed in a more visual manner – through infographics and charts that organise the data in such a way that the meaning is immediately apparent. Data visualisations can be incredibly beautiful, but their importance goes beyond aesthetics: they provide a unique means of highlighting new patterns in statistics and looking at the world in a different way. Visualisations can be static, or they can be interactive and dynamic, such as the animated trends from, which visualise the evolution in development indicators such as child mortality and HIV prevalence to gain new insight.
Telling a story around statistics, either through words or visualisations, is not without its pitfalls and data communicators need to be responsible storytellers, not misrepresenting the data to meet their own needs.  Data visualisation as a mass communication tool is a relatively new discipline and a better understanding of best practice and good examples would be a helpful resource for data communicators.
People as data producers: crowdsourcing statistics through digital technology

Finally, digital technologies mean that members of the public can have greater access to statistics by participating themselves as data producers. The prevalence of accessible yet sophisticated mapping technology through mobile platforms provides a means to crowdsource data from members of the public. While this is a new area, there are a number of examples of crowdsourced data related to progress and well-being statistics such as Mappiness– an app to monitor levels of subjective well-being in the UK, Open Elm Map – which uses community-generated data to track Dutch Elm Disease, Harrassmap – which uses crowdsourced data to highlight sexual harassment hotspots in Egypt, and the Ushadi platform, which was originally used to track political violence in Kenya and which now encompasses a number of open-source platforms. Crowdsourced data is perhaps the ultimate in democratising data: empowering people to be producers as well as consumers of data.
Best practices and good examples

It is clear that making data more accessible to society at large covers a broad range of issues. Technological advances provide a huge potential for democratising data, but many of these areas are new or evolving quickly. There is a need to identify best practices and good examples in the areas of Open Data, visualisation, and crowdsourcing technologies in order to provide guidance to those interested in making data more accessible.
This online discussion is an opportunity for the Wikiprogress community to hear from individuals and organisations with experience in these areas. In particular we’d like answers to the following questions:

  • What role can Open Data play to increase citizen’s engagement with well-being and progress statistics?
  • How can data visualisation and storytelling be used to increase our understanding of data? What are the best examples of data visualisation?
  • What are the best examples of crowd-sourced data related to well-being and progress?

We look forward to hearing from you in the discussion!