Communicating environmental issues often requires the interpretation of complex quantitative scientific data. But spreadsheets of numbers won’t change people’s minds. Instead, it is the narrative built around the key insights from the data that creates the change. To make messages even more compelling, many publishers are turning towards data visualization to increase their impact, particularly in a crowded media arena.
In recent years there has been a convergence of technologies, policy initiatives and business models that have made the discovery, the sharing, the interrogation and presentation of this data to a broader user base. Data visualization is now no longer the domain of scientists, but also of graphic artists, journalists and even virtual crowds. In response, consumers of this data have become more comfortable with accessing, querying and even contributing to this data.
A large proportion of this data is now being placed in the public domain and is available in machine-readable formats, even from live feeds, allowing app developers to ‘mash-up’ or combine different datasets to reveal new insights and new commercial opportunities. Even private sector information managers are finding value in publishing discreet datasets form what would otherwise have been considered highly sensitive information.
Driving much of the data publication are public institutions, such as universities and governments, which now routinely publish datasets or open up their systems to enable feeds of real time information. The onus on government departments is to assume data should be published and accessible, unless there is a very narrowly-defined reason not to. Universities open up datasets to enable greater scrutiny and global peer review.
Enabling this data to be readily consumable are a new generation of web-based platforms; many license-free open source projects. One of the most popular, particularly amongst governments, is the CKAN project. It is current used by the US, UK, French and Australian governments and the European Union. It provides publishers with a license-free, web-enabled platform through which to open up datasets and feeds, but also to integrate simple data visualisation tools, such as charts and mapping services.
Communicating this data has also been revolutionized, through accessible data presentation tools, which are either free to use or cheaply available. These data presentation tools are easy and fast to develop, from dataset to publishable product, with the software interpreting raw data quickly and 'best-guessing' how the data should be presented, with tidy-ups provided by humans. Google Maps and Fusion tables provide open platforms on which to develop, present and share datasets.
Such tools are being mastered by science, environment and economics communicators. It has also allowed the journalistic craft to not only tell the stories behind the data, but to use the visual impact data presentation to amplify the context of the written word. The Guardian's Greg Jericho has made this an art form in his economics blog.
While Al Gore’s An Inconvenient Truth keynote presentation still sets the standard in multimedia data presentation, even if you don’t have a hundred thousand dollar budget and a first-rate production team available you can, with good analytic skills and creativity, create compelling data visualizations.
What makes for effective and compelling communication of environmental messages through data? Several factors need to be considered in presenting data visualizations.
- Elegance - your visualization communicates a clear and powerful message.
- Complexity - a well-designed user experience can layer information through the presentation to enabling the user to explore complex data in discreet chunks.
- Explanatory power - in this world of busy, distracted readers, data visualizations need to quickly convey the key messages.
- Size - it's not everything, but it can still be impressive.
- Utility - how does the data visualization encourage a change of behaviour?
- Interactivity - new, web-based technologies allow data visualizations to be explored, not just passively viewed.
- Collaborative - opening up datasets to community contribution can vastly expand the dataset's size and accuracy.
Here's my list of top data visualizations that communicate environmental issues most effectively.
1) Letting the data speak for itself: elegance
Few biophysical trends more tangibly demonstrate the unequivocal warming of the planet from greenhouse gas emissions than the decay of Arctic Sea Ice.
The US National Snow and Ice Data Center openly publishes numerous datasets and usefully curates them to cater for easy consumption or for more significant statistical and scientific analysis. Its Arctic Sea Ice News and Analysis daily publishes Arctic cryosphere conditions, the most accessible being the sea ice extent and Greenland ice sheet melt area. With limited narrative, these charts demonstrate a worrying and accelerating trend in sea ice loss. Both sets are available via feeds for your own use.
Science communicators have taken these data sets and created elegant and compelling extracts. The famous 'death spiral' of Arctic sea ice volume data from the Polar Science Center (below) is visual stunning, elegant in design and compelling in its message.
2) Exploring complexity: Student Energy's Energy Systems Map
Where does the energy we use come from? How is manufactured into a form we can use for something valuable and then distributed? Student Energy, a Canadian not-for-profit targeting at informing the next generation of sustainability leaders, tries to explain it all with their energy systems map.
Not only does the map show how energy flows through social and economic systems, but it layers additional, more detailed information, to enable the user to explore exactly how 'bio-digestion' converts energy or how 'steam methane reforming' transforms raw materials. Never again, will an energy policy maker be able to bamboozle you with obscure terms!
Greater sophistication could be added down the track to add Sankey diagram principles and to communicate throughput volumes at each node.
3) You've got 15 minutes with the Minister: how to get your message across quickly
Consulting firm McKinsey and Company cracked this problem perfectly with its now famous greenhouse gas marginal abatement cost curve. The graphic represents the relatively arcane economic concept of marginal abatement cost curves (or 'MAC curves', remembering your undergraduate days). In just one chart, bureaucrats could demonstrate to impatient Ministers where investment or policy could be best targeted to reduce greenhouse gas emissions for the lowest cost... so there would no more ill-advised pet projects or wasteful co-investments in carbon capture and storage for the coal industry! (Oh, wait...)
McKinsey and Company's MAC curve is now in its third iteration.
4) Big data: World air quality data
It is estimated 5.5 million people die prematurely from poor air quality around the world each year. To help us understand the extent of the problem the World Air Quality Index project has pulled together an extraordinary set of real-time data from thousands of air quality monitoring stations around the world. With a mission to 'promote air pollution awareness' this not-for-profit otherwise seems to get little attention considering the effort in maintaining such an impressive product.
It makes for compelling viewing and clearly demonstrates the significant air quality issues in fast developing cities in Asia (particularly India) and South America and the dearth of data for policy makers in Africa.
(At time of writing, my local city centre air quality index (AQI) in Brisbane is relatively safe 37, whilst the residents of New Delhi are suffering hazardous conditions of AQI 527. The place to live for the best air quality is Tasmania.)
5) Driving adaptive behaviour: Brisbane City Council flood maps
Following severe, costly and fatal flooding in Queensland, Australia in January 2011 and further floods a year later Brisbane City Council re-calibrated its flood maps and developed a series of public information tools to educate residents on their flood risk. These tools included a flood risk map and property-level flood risk information sheets.
Putting easy-to-understand data in the hands of residents is one way of enabling risk to be communicated through property markets and begin to reveal discounts on high-risk properties to drive adaptation to new climatic conditions. Though property transfer prices have been slow to respond in a generally inflating market (people's memories are short), increasing insurance premiums should start to drive adaptive behaviours in the long run and by using products, such as the flood risk map, residents can start to make more informed decisions.
6) Crowd sourced data: the power of the people
Trying to keep track of forest cover loss on a global scale requires a huge, mass-distributed, global effort. Global Forest Watch was originally set up by WRI, but has now evolved into a diverse and large collaboration. In addition to forest change data being submitted by specialists from the various collaborating NGOs, mobile apps are available for anyone worldwide to submit new data or improve the integrity of existing information.
Collaborative datasets achieve their accuracy from the network of thousands of peer reviewers and editors. Data presentations, such as Global Forest Watch website, provide not only fantastic datasets for your own research, but also platforms on which to build your own applications.
7) Compare and contrast: global greenhouse gas emissions
Who is responsible for global emissions? Which sectors are the biggest emitters in each country? The World Resources Institute (WRI) has published an interactive infographic that can answer these questions. Though the dataset is relatively one dimensional, the accessibility of the data provided by the interactivity makes it easy to understand headline figures for emissions within a global context.
The WRI has a number of more detailed 'dashboard' style data explorers available through its website.
++ Stop press ++
April 2016 was the seventh straight month of record warm global temperatures. The first four months of 2016 have been so hot it is now almost impossible that 2016 will not be the hottest year on instrumental record.
Following in the spirit of the spiral of decaying Arctic sea ice - only this time in reverse - Climate Lab Book has created a similar presentation of post-industrial revolution global temperatures, clearly showing the recent accelerating temperatures.
— Ed Hawkins (@ed_hawkins) May 9, 2016
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There are countless examples of excellent environmental data visualizations. Here's a few honorary mentions:
- Carbon dioxide concentrations in the Keeling curve
- Tracking protected area downgrading, downsizing and degazettement
- The Stockholm Resilience Centre's demonstration of 'Planetary Boundaries'
- Monitoring heatwaves in Australia with Scorcher.org
- The 2 degree carbon budget and our probability of success from Raupach et al
Have you come across better examples? What, in your opinion, makes for a great data visualization?