The process we used to create the data mural was definitely different from the design meetings I attend weekly on visualization projects in my research. Most projects that we visualize are more data heavy and less illustrative because the points we want to include in particular visualizations often dictated the visual forms and complexity we needed to represent. I think that there is a tendency to focus on the quantity and quality of data in my own design processes rather than starting with small snippets of anecdotes and stories.

I am surprised how well and cleanly the ideas for the murals came together given the short amount of time. I think this is the result of following the data journalism handbook’s points. We translated the looking for key terms step into a real time activity by using post-its and were able to construct a story that is true to the preliminary data quickly. We did not pursue a lot of the other more time consuming tasks, such as going through and curating the data ourselves, which if time allowed I would liked to have done.

While I have prior experience designing data-driven stories, creating the Food For Free data mural was dramatically different from the design processes I was used to. As laid out in the Data Journalism Handbook, my typical process involves querying a data set to answer specific questions or identify outliers and interesting patterns. Brainstorming for the mural felt a lot less structured, more akin to the “blue sky” ideation of early stage product design (what I like to call “brain vomit”). The narratives we created — while derived from a structured typology of different data stories — were distilled to far broader big picture ideas when we translated them into visual language, perhaps because this was presented as a creative artwork rather than a quantitatively-focused chart/graph.

I did like the concept of drawing for a short period of time and then passing it on; not only did this process promote the creative “piggybacking” you see in a typical group brainstorming session, but it also allowed us to see which common thematic strands kept popping up to create a more consensus-driven design. The resulting artwork is more based on visual metaphors and symbolism rather than the design techniques of narrative visualization identified in Segel & Heer’s case studies. However, the mural still uses basic design principles of alignment, sizing, and color to achieve the more general tactics of visual narrative (structure, highlighting, and guidance).

This experience helped expand my definition of what a data visualization could be; there are definitely opportunities to be creative with the data presentation. My one criticism of the medium is that the data doesn’t always feel entirely integrated with its presentation. Sometimes, it felt like we were just adding numbers to the artwork as an afterthought. There is a distinction between the fields of art and design, and to me this mural definitely felt more like data art than data design — and not just because we were painting. That’s not to say that a mural is any less valuable or less informative, but we certainly took more artistic liberties and the result feels far more subjective than I’m used to.

I found our story finding and visual design process fun and surprisingly similar to processes that I have used before for design brainstorming – I guess theres a reason such sticky note techniques are widely used by designers 🙂

Last semester I took a class called Engineering Innovation and Design. As a brainstorming exercise for our final project, we were told to get into groups, grab a bunch of sticky notes, and then write down the first things that came to our mind. We proceeded to put these on the blackboard, cluster them, name our clusters, and work off each others ideas just like we did in our class.

Similarly, over IAP I had the opportunity to brainstorm and prototype a new feature for the company I was working at. In our very first meeting, the head of UI/UX at the company explained the problem, what we were hoping to accomplish with this new feature, and then proceeded to hand me a whiteboard pen. The three of us in the room spent the next hour repeating the process of ‘draw for 5 minutes, talk for 10min,’ and by the time we left the room we had sketches that encompassed about 90% of what the final feature ended up being.

Thinking back now, this process of rapid brainstorming with sticky notes and whiteboard pens is something that I’ve done whenever encountered with a new UI/UX problem. When it comes down to it, I think that data visualization is highly correlated with UI/UX, because you’re taking something that’s otherwise unreadable and trying to make it attainable and emotion eliciting from your readers.

As a former photography editor for The Tech, part of my job included taking a series of photos from different event, whether it be a campus performance or a demonstration in Harvard Square, and turning it into a story that makes sense to the general audience. Most events tend to be summed up into just one picture, though there are other instances where multiple photos from the event are run as a “photo spread”. Things I had to consider included the usual what/when/where of the photo, but also (and most importantly) why the event pictured was happening and its relative importance compared to the other photos submitted for the current issue. This is process was repeated on a) all photos submitted for an event and b) all photos that are selected for each event for the issue, to determine placement in the issue. My goal was to create an accurate and relevant presentation of various events that are interesting and relevant to the MIT audience.

Compared with our story finding process for the Food for Free Mural, we were given a dataset with information about Food For Free’s work over the last few years, and an insider perspective on how it works and why it’s important. From this information, we cherrypicked what we considered the most important and formulated sentences that were then joined to create a cohesive story.

These processes, though dealing with different kinds of “data”, were not all that different — both involved some sort of cherrypicking, or narrowing down of the information that was available — while still trying to get a good “picture” of what is going on. Another process not talked about here is the development of the visual design – the designing of photo spreads also has similarities to our process for designing the mural.

I found the mural design process of our class very different from my previous design processes.  First, let me briefly lay out our mural design process:

• Introduction to the organization (Food For Free) through the voice of the director
• Group discussion to find a story based on the follow criteria:
  • importance: impact on the audience
  • relevance: relevant to the organization and to us
  • accuracy: how well-supported by data
• Summarize the story into a sentence. Add why we want to tell this story -> Sticky!
• Gather as a class and share each group’s sticky note
• As a class, write the core sentence of the story we want to tell through the mural
• Word Web activities with three seed words: security, impact, waste
  • Starting with each seed word, branch out with whatever words that come into mind
• Collective drawing
  • Each person starts drawing and passes around to next person so that everyone contributes to each other’s drawing in continuation
  • Put on the board and share
• Decide on the mural design as a class
  • Find repeated imageries/themes from the collective drawings
  • Incorporate them into one design

Some reflections on this design process helped me to compare it to one of my previous projects.   During the cold and snowy winter of 2014, I  and three other MIT students worked to design an interactive dashboard that analyzes Twitter and Facebook activities of non-profit organizations. Briefly speaking, below is the procedure we followed:

• Discussion on the basic frame of the dashboard: contents, functions, purposes
• Analyze data
  • Each team member analyzes same data but work for different goals
  • Push each findings and codes on Github which allow other members to quickly reuse or build upon the code
• Write a report on the analysis
  • Two members are in charge of the write-up
• Build interactive dashboard based on the findings
  • Two members are in charge of hosting the byproduct online

This process is similar to the mural design process in that it had modularity and involved group efforts within each module. First, the modularity arose from the step-by-step procedures and several milestones we established as checkpoints: the goal of the project was defined first, and the process was broken down into three smaller steps/milestones.  The difference arises in the way tasks were distributed between the members.  Instead of a group of individuals working together to finish a small module, each person was in charge of a designated task at each step. Each task was discussed after the corresponding milestone was reached, and each code was ready to be reused by other members if needed.  This combination of distribution and code-sharing helped to maintain communication between members while enforcing the modularity in the process.  It was however harder to understand other members’ tasks and thought-process, which required that everyone became an expert in his/her given task.  In comparison, the mural design process did not rely heavily on any particular individual because each module was done in a group.  I definitely felt that the mural process better captured the ideas common and prevalent in our class; it somehow felt more democratic.

The two design processes discussed above share similarities in its step-by-step approach and distributed workload.  However, they are different in the way each step is finished and each task was incorporated into the final design; the design mural process had one more filtering layer in which the entire class decided what to include from each group’s work.  Both of the processes have pros and cons, and it is important to know which path to take according to the goal and circumstances of the work.

Instead of starting directly with data, we began our data story for the Food For Free mural by listening to a verbal narrative of the organization’s history and impact from one of its leaders. We heard about Food For Free’s beginnings, its expansion throughout the greater-Boston area, and its plans for the future. After hearing the story, we were presented with data, some of which was on a global level, some on a local level. Equipped with data and an understanding of the organization, we set out to define a story that we wanted our mural to convey. We started out with verbal stories: sentences about the organization’s history, its impact, and its community partners. These separate ideas were then combined into one cohesive short verbal narrative about Food For Free. In deciding on our narrative, we followed a method similar to that suggested by Colin Ware and sought to “capture the cognitive thread of the audience”. We wanted the audience to feel engaged in our story and compelled to action as a result of encountering it.

Next we set out to transform our words into a picture. However, as Ware points out, verbal narrative “incorporates a form of logic that is quite distinct from the logic of visual representation”. To overcome the challenge of translating words into a picture, we each drew a picture of the data story and combined the common themes. We used both literal depictions, such as trucks and food, and metaphorical depictions, such as a tree and roots, to signify the story of Food For Free. Because we are producing one still image, we are faced with the challenge of telling a narrative history without including multiple time points. In this respect, the symbolism of the growing tree serves as an effective focal point in communicating Food For Free’s story. Finally, as Ware explains the importance of, we decided to use a road to frame our picture, helping to focus the audience’s attention.

Recently, our class worked to conceptualize our data mural for the organization Food For Free. I was absent for the last class, in which we carried out most of our visual designing of the mural, so I will focus instead on the processes carried out during the previous class.

In this class session, the executive director of Food For Free visited our class to discuss the organization, its purpose, its functions, and its future goals. This visit exposed us first-hand to Food For Free, which was indispensable to our conceptualization of the organization.

In the readings, Segel and Heer emphasize the importance of narrative to the process of data visualization. Narratives draw readers to a story and help readers to understand and internalize the message being conveyed. Though the authors focused on its impact on journalistic practices, their insights on narrative apply well to our situation.

In our process, we first educated ourselves on the mission and practice of Food For Free. Once we felt well-grounded on the topic, we looked at some data about the group provided to us, brainstorming in groups to identify potential stories held within the data. Once each group came up with a viable story, we presented the stories to the rest of the class and combined them into one, consolidated, group story.

Contrary to traditional storytelling, our mural will not have a beginning, middle, and end, nor will it include any verbal or much written content. Instead, it will employ visual cues and symbolism to convey our story about the organization.