Fall 2021
Response to an Information Visualization Manifesto
With roots in the scientific and academic research communities, Information Visualization sprouts as a tool to “explore information and its structure” with the help of computer-generated visuals (Robertson, Card and Mackinlay, 1999) but with data becoming more abundant and technology more accessible, Information Visualization is now produced as a powerful communication tool, therefore message and clarity are now also an important focus.
Manuel Lima publishes the Information Design Manifesto with the attempt to list guidelines “for the most part consented by everyone” and to define a clear “divide between Information Visualization and Information Art” (Lima, 2009). However, the role of Design in Information Visualization is an important conversation that has amplified agreement and disagreement between practitioners of eclectic fields. To remedy this division of opinions,
This paper will discuss Lima’s guidelines, the controversies they bring up and his response to them and how Design should shape Information Visualizations.
The manifesto starts with: “Form Follows Function” (Lima, 2009), in other words, form should not follow data The second rule is “Start with a Question” (Lima, 2009). These two solid statements hold up to “the purpose should always be centered on explanation and unveiling, which in turn leads to discovery and insight” (Lima, 2009). Information Visualization should amplify the cognition of data, whether empirical or abstract, it should be an efficient tool to dig in the content to find meaning and understand something otherwise hard or impossible to decipher. This first guideline particularly sparks controversy in the first. However, Pedro Cruz, three hours later, defends Lima’s case by pointing out “The act of exploring that information with an objective intent is what should shape its appearance” (Cruz, 2009). Even if I understand intent as subjective, I agree with the sentiment of his comment.
The form of the data represented should be chosen with consideration to what aspects of the data are important to highlight and be explored. The same goes for the domain, range and scales of the visualization, for the data to take shape in response to a question or to assist a task. A good example to illustrate this point is Harry Becks’ classic map of London, his design choices to distort the geographical accuracy of the stations locations to amplify the successful use and function of this map. That way, the users can find their way and what train to take through a clear layout, faster and more efficiently than when relying on the previous maps that attempted to place stations accurately, resulting in busy and confusing forms.
Map of London.
Modern Tube Diagram by Harry Beck - 1931 .
Another guideline from Lima is: “The power of Narrative” (Lima, 2009). “Storytelling is the world’s second oldest profession” (Gershon,2001), glorifying the power of stories, Lima prescribes that a project should “be able to convey a message and easily encapsulate a compelling narrative” (Lima, 2009). Kim Rees mentions that that is not essential as the user can create their own story from the visualization. Lima agrees that a “self-made narrative emerges from the exploratory executions” (Lima, 2009). Either way, narratives are essential to understand the bigger picture. Paolo Ciuccarelli coins the term visual macroscope for visualization that reveal through narrative the infinitely complex. “Agreeing with John Thackara, visualizations are understood as “Tools and aesthetic notions, that help us understand -and act mindfully- in the big picture””. (Ciuccarelli, 2020). A story is an essential part of learning, especially to understand where the represented information stands and where it comes from and why it is being represented.
A good example of information visualization that encapsulates narratives is Otto Neurath’s work, explaining natural and social issues in simple ways, using icons and symbols called Isotypes. In “How long do animals live?” the viewer can follow the squiggly timeline and find out which animals are outliving the others, while in “Births and Deaths”, data quantities are displayed through the repetition of icons and enables the viewer to perceive a story.
How Long Do Animals Live?
Otto Neurath - 1930
Births and Deaths in 1938
Otto Neurath - 1938
Pictures can easily convey messages. However, Lima also warns: “Don’t Glorify Aesthetics” (Lima, 2009). Paolo Ciuccarelli resonates well with the idea that aesthetic should be used consequently without being the main goal: “Narrative elements cannot be considered as mere embellishments; they have a specific function in that they build the story – the narration – that is necessary to re-create the context and make sense of the data. To do so, one must leave the protected realm of research domains, and play with issues like beauty and pleasure. In other fields of design research, it is quite established that emotion is a cognitive force which contributes to sense-making, facilitates interaction and enables a better experience. Usability and aesthetics are no longer in opposition to each other” (Ciuccarelli, 2020).
Lima also mentions three rules, that admitting in his Observation of the Manifesto, overlap: “Look for Relevancy, Aspire for Knowledge, Avoiding gratuitous visualizations” (Lima, 2009). “Extracting relevancy in a set of data is one of the hardest pursuits for any machine. This is where natural human abilities such as pattern recognition and parallel processing come in hand. Relevancy is also highly dependent on the final user and the context of interaction.” (Lima, 2009). Relevancy can be seen in the placement of the train stations in Becks’ resourceful map: What is relevant is the order in which stations are reached by each line, and their connections. The exact geographical placement is not relevant when someone knows the name of the station they are trying to reach. In highlighting the relevant and avoiding gratuitous information the map finds success.
“Interactivity is Key” (Lima, 2009), is a relevant rule especially for digital visualization.
“By employing interactive techniques, users are able to properly investigate and reshape the layout in order to find appropriate answers to their questions” (Lima, 2009). This
goes back to the point about narrative revealing complexity and how the users create their own narratives. The ability for the user to see everything together, filter and seek details is a powerful recipe for an insightful interactivity, as Schneiderman’s mantra prescribes: “1 Overview first, 2 zoom and filter, 3 details on command” (Fitzgerald, 2016).
“Embrace Time” (Lima, 2009) is also an important factor, “if time had been properly measured and mapped, it would provide us with a much richer understanding of the changing dynamics” (Lima, 2009). I think it all goes back to the phenomena encoded and the scales used to map the data: Is the accuracy of the data collected relevant? Is the time mapped consistent with the methods used to gather the data? An example where the mapping of time can make a big difference is this next comparison: distortion of time on the x-axis in the Fox news example gives the impression of a constant increase, however, a more accurate and granular mapping of the timeline reveals growth, decrease and plateauing around March. In this comparison we can see how the way time is mapped, affects the insight and narrative potentially extracted from the viewer.
Comparison of graphs by Trent Tucker
Finally, “Cite your Source” (Lima, 2009) is one of the most important part of the visualization. “By doing so you allow people to review the original source and properly validate its authenticity. It will also bring credibility and integrity to your work” (Lima, 2009). It is the responsibility of designers to raise the awareness of the viewers/users and to clarify as much as possible the intention of the visualization and the clarity of the message and context meeting the needs of the experts and the non-experts.
The World is Not Enough.
Statista - example of cited source
In his conclusion Lima addresses the divide in response to his manifesto, in Observation of the Manifesto, explaining that “a clear divide is necessary, it doesn’t mean
that Information Visualization and Information Art cannot coexist. I would even argue they should, since they can learn a lot from each other and cross-pollinate ideas, methods and techniques.” (Lima, 2009).
My opinion on that is that creative and exploratory approaches to Information Visualization are necessary and are the foundation of the field. Looking for new styles of visualizing information can potentially reveal new insights and efficient ways to convey information. Experimentation involves modifying aesthetic variables. Information driven aesthetics are based in subjectivity, opinions and arbitrary guidelines, in my opinion, the same can be said about collecting data (for example the Metric system and the Gregorian calendar are arbitrary). The visualization, however, is a physical work that is objective in itself. “Data is always gathered at a certain time with purpose; and to be useful it must be mined, parsed, and presented. Each step of this process involves decision about what to omit and what to prioritize. Yet the result, the visualization, carries an authority, timelessness and objectivity that belies its origins” (Peter Hall, 2011).
A mathematical equation on paper can be seen as a very abstract form of poetry and a computer-generated chart can be seen as digital art even if consideration for aesthetics has been avoided. The context of the visualization and the intentions of the designer always risk being missed by the viewer. The power of defining Information Visualization from Information Art only resides in the viewer despite the intentions of the designer. Designers must always attempt as much as possible to consider the bigger context of their Information Visualization as much as possible in order to achieve effectiveness, convey insight and if necessary, innovate solutions.
On a side note, it is becoming more common for Art Museums to exhibits Information Visualizations (each, for different reasons) such as the “Historic Maps of Cape Cod from the collection of David Garner” at the Cape Cod Museum of Art, Cooper Hewitts’ section on “Data Visualization”, “Visualizing NYC by the Numbers” at the Museum of the City of New York (an exhibit containing Simulated Dendrochronology of U.S. Immigration, 1840- 2017,2019 with Pedro Cruz on the team that worked on this visualization) and the Museum of Modern Art curating “Dear Data”, data humanism work by Giorgia Lupi and Stefanie Posavec.
Sources and references:
- Card, S.K., Mackinlay, J. and Shneiderman, B., - Readings in information visualization: using vision to think. San Francisco: Morgan Kaufmann Publishers Inc. - 1999
- Gershon, N. and Page, W. – “What story telling can do for information visualization.” – Communications of the ACM – 2001
- Manuel Lima – Information Visualization Manifesto - https://web.archive.org/web/20200513162716/http:/www.visualcomplexity.co m/vc/blog/?p=644
- Brooke Fitzgerald - Data visualization - https://hampdatavisualization.wordpress.com/2016/02/26/schneidermans- mantra/
- Harry Beck – map of London – https://londonist.com/2016/05/the-history-of- the-tube-map
- Sandra Rendgen and Ed. Julius Wiedeman- Information Graphics: Paolo Ciuccarelli, Turning visualization into stories and “big pictures”.
- Otto Neurath – how long do animals live?- https://piperhaywood.com/how-long-do-animals-live-graphic/
- Otto Neurath – Births and Deaths - https://www.pinterest.com/pin/153966880982845347/
- Trent Tucker - How Graphs Misrepresents Data – https://ecampusontario.pressbooks.pub/bio16610w18/chapter/how-graph- misrepresents-data/
- Statista – The world is not enough- https://www.instagram.com/p/CR6eXURiu1l/
- Peter Hall – Bubbles, Lines and Strings – How Information Visualization Shapes Society – 2011- http://www.revue-backoffice.com/en/issues/02-thinking- classifying-displaying/peter-hall-bulles-lignes-fils
- https://www.moma.org/collection/works/215813
- https://www.mcny.org/exhibition/who-we-are
- https://www.cooperhewitt.org/tag/data-visualization/