On 7 March 2011, Channel 4 in the UK ran an episode of their current-affairs show Dispatches enti-tled Selling Off Britain that asked the question: ‘Could the sale of government properties cover the national debt?’ How seriously to take the proposal is a matter of opinion (although plans were already under way to sell off some of the national forest lands – an idea since partially scrapped), but the story was a great way to highlight a number of key issues – the debt itself, development of council-owned land, and the sheer scale of government assets.
The story itself was based on the National Asset Register, a public tranche of data listing every-thing that the government owns: fairly standard governmental information, and in fairly standard government style, it is recorded in uneditable PDF files. Channel 4 worked with Scraperwiki to first convert the data, then present it in interesting visual ways.
Scraperwiki’s team used both technology and old-fashioned human power to convert the data in the PDF files into a spreadsheet of information, identifying each asset, its value, which government depart-ment or structure actually owned it and other information. This spreadsheet was then used to build a visualisation showing ‘asset bubbles’ – renderings showing the amount of money tied up in the asset by changing the size.
This was turned into an interactive tool – users could see the big picture, or drill down to see what specific assets each department or layer of government owned. In addition, land-based assets had been identified in the original PDFs with postcodes, and this allowed Scraperwiki to create an interactive map showing what assets were owned, and allowing users to zoom in to their local area.
Both data presentations were used in a live debate on the issue on Channel 4 – appearing during the broadcast and in a story on the Channel 4 website. Specific pieces of information were also used as the basis of journalistic stories.
By using data-journalism techniques, the team behind this story used freely available government data to not simply tell the story embedded in the data itself, but another story, that of the national debt, and of council developments. The project provided the basis of a considerable amount of content, and was designed to not only inform, but engage the audience and the public. The map was particularly
FIGURE 4.5 Picture courtesy Channel 4 and Scraperwiki: http://blog.scraperwiki.com/2011/03/08/
600-lines-of-code-748-revisions-a-load-of-bubbles/.
Defence
Transport
81.0bn
93.4bn
41.5bn
38.8bn
40.2bn
23.0bn
19.2bn More...
Northern Ireland
Trade and Industry
Scotland
Health
important to this, and engendered considerable comment and feedback for the team. This was not just a technological exercise, but a fundamentally journalistic one as well (Channel 4 Dispatches, 2011;
Guru-Murthy, 2011; Hughes, 2011b).
Key reflections
Keep your eye on the story. Data is fun, but your users want to know what’s going on.
Give and take: let your readers see the data, see where it came from, and listen to their ideas and interpretations.
Jump right in: technology is not as scary as it looks; try some tools, play around with them, and use the tools and help available online.
What kinds of government data are most useful in storytelling?
Is data journalism an essential part of journalism? What kinds of stories can best be told with it or without it?
How important is it to have access to data?
FIGURE 4.6 Picture courtesy Channel 4 and Scraperwiki: http://blog.scraperwiki.com/2011/03/08/
600-lines-of-code-748-revisions-a-load-of-bubbles/.
Tips and Tools
Google Fusion Tables: (www.google.com/fusiontables/Home) allows the upload of data using standard formats and the visual display of that data via Google’s servers. Advanced users can also create their own interactivity features using Google’s Application Programming Interface (API).
Users can share data or not, as they choose (Google, 2011a).
Google Maps: (http://maps.google.com/) provides interactive maps of the entire planet (and the moon) along with layers of data. Users can add their own information and data to the base map and publish it online; data can also be solicited from the public, or via photo and location tools like Twitter (Google, 2011b).
Scraperwiki: (https://scraperwiki.com) is an organisation that provides a platform, tools, training and assistance in both finding and presenting data. The platform allows people to create their own visualisations, find people to collaborate with, and use and reuse information provided by other members of the community (all data accessed and published via their platform is public). They conduct training workshops and tutorials, as well as being available for data visualisation commissions (if you need to keep your data and visualisations within copyright) (ScraperWiki, 2011).
Tableau: (www.tableausoftware.com/public) is free data visualisation software that anyone can download and use to publish their data to the web. There are tutorials and forums to help you get started, and they may be available to conduct training. As with Scraperwiki, all data published using their free tool is automatically public: there is a premium service if you need to keep your data private (Tableau, 2011).
A number of online timeline tools exist, such as Dipity (www.dipity.com/) and SIMILE (www.
simile-widgets.org/timeline/). ProPublica has its own tool as well, available at: www.propublica.
org/tools/.
Readings and Resources
The Guardian’s data journalism site is both a showcase for the work of their team and an excellent resource of ideas, data and collaboration for other journalists. It’s viewable at: www.guardian.
co.uk/data. Simon Rogers’s book about data journalism at the Guardian, Facts are Sacred: The Power of Data (2011b), is also extremely useful.
The Nieman Lab at Harvard University maintains an excellent site of information and stories about the future of journalism. The archive of their stories on data journalism is available at: www.
niemanlab.org/tag/data-journalism/ (Nieman Lab, 2011).
Journalism in the Age of Data is a project of the Nieman Foundation: the full report can be read at:
http://datajournalism.stanford.edu/ (McGhee, 2010).
Data Miner UK is the blog of Nicola Hughes of ScraperWiki. It’s got links to tutorials, projects, ideas and resources. It’s at: https://datamineruk.wordpress.com/ (Hughes, 2011a).
TOOLKIT
The Poynter Institute in Florida also maintains an archive of data journalism stories and resources at www.poynter.org/tag/hackshackers/ (Poynter Institute, 2011).
ProPublica is a non-profit investigative news agency that produces stories for syndication as well as training and supporting investigative journalists around the world. They have an excellent set of resources available at: www.propublica.org/tools/ (ProPublica, 2011).
Hacks and Hackers is a group of journalists, geeks and activists who run projects and training and get people involved in and excited about data journalism. The main site is here: http://hackshackers.
com/ but there are groups all over the world. They also have an excellent glossary of terms at http://
hackshackers.com/resources/hackshackers-survival-glossary/ (Hacks and Hackers, 2011).
Advice on using numbers in journalism can be found at the BBC College of Journalism (www.bbc.
co.uk/academy/collegeofjournalism/how-to/how-to-report/reporting-averages-percentages-and-data) and the Royal Statistical Society’s Getstats campaign (www.getstats.org.uk/).