This week, I started reaching out to people in my network to refine some aspects of my Futures Project. I met with Camila Gottlieb, an education specialist with whom I worked at UNICEF. The meeting was short and productive, and it got me thinking about different aspects of the project. I will discuss some of them below.

Quantitative information

To provide context, I will introduce some general quantitative information about education in Uruguay, graduation level, dropout, socio-economic quintiles, etc. Camila suggested three main sources for this:

1. Educational Viewpoint of the National Institute of Educational Evaluation (Ineed, for its acronym in Spanish): this is official data taken from the
2. Education Observatory of the National Administration of Public Education (ANEP, for its acronym in Spanish), which constitutes the second source of information. Camila told me the Observatory has the raw data available for download, which would be very interesting to analyse.
3. World Bank data: provides a steady record of data, and the possibility to compare with other countries.

Qualitative Information and Data Collection

One of my main concerns was accessing the data, the testimonies I would like to portray in my data visualisation. Camila immediately thought of a “headhunting” methodology, akin to the human resources practice, based on looking for specific people of a certain profile. This would rule out the possibility of associating with an organisation which would tie me to their timings and interests with less flexibility.

The headhunting would have to be done with young adults (which was another of my doubts: if I should interview adolescents or adults), to ease the approval process and to show a short- and mid-term impact of the educational trajectory. I initially thought of an age range of 18-25 years old.

As for the methodology, I was thinking about conducting interviews. Camila also suggested an ethnographic style of “contact”, by which I could establish a specific contact (e.g. send a WhatsApp message) to subjects every 7-10 days with one particular query. This would facilitate the establishment of rapport with the subjects while allowing them to asynchronously think about the questions, do the exercise of remembering, and then reply. It’s true that some of these questions will require the subjects to dive into their memories as back as ten years’ time, so allowing them time to remember would probably elicit answers of a better quality.

Another issue I’m thinking about is the personalisation of the testimonies, including whether or not to include photos and what kinds of photos. One of Camila’s suggestions was that the photos could be of the context (with, again, an ethnographic approach) instead of the people themselves, for example, of their classrooms, how they went to school (transport), what they ate, etc.

Finally, showing “good” and “bad” examples would definitely be paramount, especially highlighting the differences between quintiles, which would show that, yes, this is a problem for the whole country, but it is especially a problem for those of lower socioeconomic levels.

Target audience

When speaking with Camila, a new potential target audience arose for this data visualisation. Until this point, I had thought of society in general and decision-makers, but Camila proposed the idea of funding bodies or philanthropists. Some examples of these are Reaching U, Varkey Foundation or e.dúcate.

Final thoughts

The meeting provided me with new insights that keep fuelling my Futures Project. I think Camila would be an excellent collaborator when the time came to think about those questions to ask the subjects.

However, reaching out to people and using my network to expand my thinking of this project is very fruitful. After attending a data storytelling event this week, I reached out to one of the speakers with whom I will meet tomorrow to further discuss qualitative and human-based data visualisations. Can’t wait to share how it goes! But that will have to wait until next week.

This week I had my first meeting with my Futures Project supervisor, Stuart King. This raised new questions (but of the interesting and exciting type); things to think about from an initial idea that so far, seems “fertile”. To recap, my current idea for my Futures Project is a data visualization that shows the educational trajectories of specific people in Uruguay and tells their stories, mainly focusing on those who dropped out, what their lives are like, why they dropped out, and what their experience in the education system was like.

In this blog post, I will list some of the questions and concerns and then delve further into two specific aspects that require deeper examination.

• What am I going to plot? If I made a line chart, as is my initial idea, I know the independent variable would be time (measured in some way or another). But what would the dependent variable be exactly? This also raises the concern of how to show “bad examples” or trajectories that didn’t go “ideally”. These would be people that I will have interviewed and will have agreed to partake in this project. So I would have to think ways in which to portray them that preserve their dignity and don’t show them in a bad light. Even thinking about the Dollar Street project, which serves as an inspiration for my project, I don’t agree with many of the portrayals and communicational decisions made for this platform. For this, I thought of seeking advice from my former supervisor at UNICEF, who is superb at communicating development projects and stories in an empowering way.
• Would a line chart be the best form of representation? As mentioned, maybe it’s the linear way of representation that’s problematic, and I could explore other methods (e.g. tree diagrams) to depict these trajectories.
• Would I include a speculative/future-thinking element? While the data visualization would depict real stories of the past and present of these people, would I want to add a prospective element to picture how the future of the stories could potentially look like…? How would I build this (maybe including the protagonists’ input) …?
• What message do I want to convey? Apart from telling these individual stories, what would be the take-home message that I would want the audience to leave with?

Data collection

This was one of the aspects we talked about the most during our meeting, and so I thought it deserved a section of its own.

Considering that this is a very bespoke project, it needs a data collection of its own. I think using a preexisting database wouldn’t suffice to be able to construct these stories. This brings about ethical concerns for which I would have to submit the ethics form for approval at university.

Some of the questions raised during our discussion were:

• What organisations/people will I reach out to to collect the data? I have some connections through my work at UNICEF and volunteering for a charity that works in education.
• Would I do a survey (easier to get responses) or an interview (would provide more thorough data)? I would conduct short interviews (15-20 minutes) to gather the insights I need since I believe a survey wouldn’t provide that much information.
• How will I structure the data collection (e.g. What would the interview schedule look like?)
• How am I going to collect the data from the UK? Maybe conduct Zoom interviews? But still, I would need someone in Uruguay to get in touch with the interviewees.
• Would I interview adults or adolescents? I think interviewing adults would give me a more long-term perspective on their educational trajectory. But I think finding adults would be harder since they usually lose touch with charities I could potentially reach out to once they become adults.
• How many stories will I aim to collect? Somewhere around twenty…? However, this would depend on the quality of the interviews and the data collected. Also, how would I ensure there’s a certain representativity, especially regarding geographic locations within the country?
• Ethical considerations especially make me question the level of personalisation of the stories. For example, would I use a photo and a name to give these stories in the plot a human face (which is partly my aim with my project: to imbue humanity in the data)? Would I not use a photo and use a fake name? (This would affect the nature of the project) Could I do something in between, like using an AI-generated photo or the silhouette of the person?

Audience

I envisage the audience of this data visualisation to be the general public (i.e. as if they read this in a newspaper) and decision-makers. My supervisor’s position was that decision-makers tend to prefer broader statistical studies that provide the big picture. While I do agree, I also think that the country already has this; what it’s missing is getting to know these individual stories. Still, this statistical, broader information could be included in the data visualisation for context.

Another issue raised was that of language. The data will be collected in Spanish, and what I had initially thought was making the data visualisation in English for the purposes of the Futures Project and afterwards building a version in Spanish for local dissemination of my project and portfolio building. What I hadn’t fathomed was that translating the stories from the data in Spanish to the finished product in English would add another layer of interpretation and potential distortion of the interviewees’ accounts. On the other hand, it is true that the target audience would consume this piece in Spanish, so making it in English would be solely for the purposes of the Futures Project. For this reason, Dr. King suggested I make it in Spanish, but I remain sceptical about it. Still, we would have to formally check with EFI to see if this is possible.

Technical aspects

I envision this data visualisation to be web based, where the user would have an overview of all trajectories intertwined, and then the possibility to see “details-on-demand” (Shneiderman), by hovering over the stories and clicking to see more details.

I do not currently have all the skills to put this idea into practice, but I believe that with the practice from my Representing Data group project and with the help of Stuart King for my Futures Project, I can make it possible.

Some of the tools we discussed for this kind of data visualisation were D3, and Python (Altair, Vegalight), but also the practice of sketching and finding something that I like to reverse engineer.

Next steps

The meeting was very productive and left me with a lot of questions and thoughts to move forward. I have already set up a meeting with an education expert who I worked with at UNICEF to discuss organisations and ways to tackle data collection.

I will also look at the ethics form and inspiration from other projects to move forward.