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, publicdata.eu, 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 here
and 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 Gapminder.org,
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!
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