Datajournalist for a day

Teaching young people about data by making datastories

In our ongoing effort to test and find the best way to teach people about data. We decided to teach people, by having them come behind the scenes and be the ones who made a datastory. Not just the ones reading and critiquing it.

Format and setup

The workshop was made with schoolchildren in mind, both due to the length and content. As such the workshop was offered in our school catalogue, where teachers have the option of reserving the workshop for their class.

The workshop is 4 hours long, from 10 to 14 o’clock, with a short break and a larger dinner break in between. The longer format allows us to expand upon the design proces and allow the students to go through a sped up design phase, before getting to grips with the data.

Program

We begin by introducing the students to data as a larger concept, datastories, and how datastories are used to make sense of large datasets.

After we have explained data and datastories in a larger context, we give them the following infographic from the danish statistical bureau, with data of an average 15 year old boy/girl. We use this particular infographic, as our experience show that data is a lot more interesting if it is quite closely related to the participant.

The students are asked to ponder the infographic, trying to find aspects of it that they would like to expand upon. They are given ten minutes to find ten different aspects they find interesting and would like to expand upon. This is to force them to think broadly about the data blocks in the infographic.

Research and Prototyping

After they have found their focus, the student are asked to research the data behind that particular part of the infographic, and create their won expanded stories.

Then the stories are visually prototyped on paper, with input from the workshop runners.

Final product

After the prototype have been discussed and approved, it is recreated, with the discussed modification, in canva (an online tool for easily creating infographics canva.com).

For more details, the workshop and how to recreate it, will be detailed in our upcoming cookbook.

Data Detox Kit

If you do not already know about the Data Detox Kit presented by Tactical Tech and Mozilla you should check it out. The Data Detox Kit is a insightful and also entertaining way to clean up your data mess – to understand the digital lugage we all leave behind without necessarily understanding how it will impact our future life and decisions. You will clear up your location footprints and degooglise your life. The Data Detox Kit has been translated into lots of languages and hopefully later this year into Danish as well.

Tactical Tech is an international NGO that engages with citizens and civil-society organisations to explore the impacts of technology on society. Tactical Tech. Besides the Data Detox Kit they have been involved in many other projects informing the genral public about the possibilities and pitfalls of technological progress.

They also have lots of concrete ideas and activities to use in a classroom or workshop setting, so if this is something you are considering to do, their website is a great place to start.

Infographics for everyone

We held our first workshop teaching citizens how to make their own infographics.

The aim of the workshop was highlighting how the participants could use readily available online tools for creating their own graphically infused stories.

Instead of focusing on the data aspect of the project, we tried in this instance to engage the citizens by helping them create the story they wanted to tell. Be it a CV, an invitation, or maybe a presentation for work visualizing, on a map, where the company’s assets were.

By helping the participants work towards an actual product, and teaching them tools and useful tricks to get there, the proces of creating (data)stories becomes concrete. Our thesis then, is that a future incorporation of data, to corroborate and strengthen your story, is more likely when the proces of creating a data story is less nebulous.

Workshop format

The workshop consisted of three major parts. First an introduction to using data in stories. Then a design- and tool introduction after which we started the work phase.

In the first part we introduce the concept of infographics and data stories; how they are used, different examples, and why they make sense. When data is everywhere making sense of it, quickly becomes a problem. Infographics and data stories are sorely needed if we want to tell or inform about subjects with complexity. We keep this introduction light and short.

after a brief design and tool introduction, we encouraged the participants to start working, relying on the usability of the tool to do most of the heavy lifting.

After our introduction to infographics and data stories, we start up with the design part. This is not a comprehensive design course in any way, but getting around basic concepts used in graphical design is helpful for the participants, in creating good looking infographics. We focus on concepts like complimentary colors and the difference between raster/bitmap and vector formats. Which tools to use, and so on. So, after a brief design and tool introduction, we encourage participants to start working, relying on the usability of the tool to do most of the heavy lifting.

The Tools

We used canva to make the infographics. Canva is a browser-based infographic tool. It is one of many options available online. We mostly chose canva due to the fact, that the non-paid option allows you to upload and output a product, almost hassle-free. There are some restrictions on output formats, but nothing really problematic. Our experience from the workshop is that the tool is easy to use – both for the tech literate and the ones less so. There are many other options out there that provides the same sort of service, and we of course encourage you to find the one that suits your needs the best.

  • Color.adobe is a tool for choosing complementary, monochromatic, analogous and so on colors. Great for avoiding the less fortunate color combinations.
  • Flaticon is one of many sites that offers free icons in different vector formats.
  • Pexel offers free high quality stock photos. Being free and high quality the selection is more limited than you will find at a paid site or a free one with a lower barrier for entry. It is a good starting point though, and will help the participants create more attractive infographics.
  • Vectr & Pixlr browser-based vector and image editors. Great for quick changes.

Takeaways

The workshop went exceedingly well. The participants quickly got to work on all manner of projects. The usability and ease of use in canva allowed almost everyone to get started right away with minimal help from the instructor.

All participants indicated during feedback, that the short introductory parts were very helpful in establishing and understanding the subject. The short timeframe ensured that it did not get too theoretical, while still being informative.

Letting the participants start working on their project in canva quickly was uniformly enjoyed. This is likely due to the fact that canva, and other browser-based software, is often very easy to get into for most people.

All in all the workshop went well, and can be easily adapted to other libraries.

Powerpoint used in workshop here (in Danish)

Teens Measuring Brainwaves

Data literacy through self tracking

Discovering that teenagers may not be inclined to immerse themselves into data work, we will this Spring be testing new concepts and ideas, to investigate how we might grab their attention.

One topic that seems to transcend age and gender is the universal subject “me”. A deeper understanding of oneself is something most people long for, and is probably part of the reason self-tracking has become such an integrated part of our everyday lives.

Teens are furthermore known for being notoriously self-absorbed, and with that in mind, we wanted to do workshops for schoolchildren using the MUSE headbands. By letting them measure their own brainwaves, we were hoping to titillate their curiosity, and motivate them to working with visualizing the data afterwards.

The MUSE headbands are very easy to set up, and we use the app Muse Monitor to track and record the brainwaves. The recordings can be directly added to a Dropbox in .csv format.

The next step is to import the data into a spreadsheet (e.g. Microsoft Excel), and without detailed knowledge of data cleaning or analysis, convert it into different charts and diagrams.

We were aware, though, that the teens needed precise instructions, in order to perform the tasks in the workshop. Still, we were surprised by how much instruction they actually needed.

They were as expected very interested in the MUSE headbands, actually so excited that they created way too many and inaccurate data sets, instead of following our instructions and focusing on getting two-three useful data sets.

Another challenge was the openness in interpreting brainwaves. The teens were expecting to get a straight answer – e.g. if my brainwaves look like this, it is because I’m [smart or creative or easygoing or…] and working with brainwaves (and especially as your only source of input) there is no clear 1-to-1 mapping. So, they were a little disappointed by the results.

“They were scientists finding out the best ways to get teenagers to be sleepy (and get to bed at an reasonable hour).”

On the positive side, they were engaged and all of them eager to see their own brainwaves. They were also convinced by the frame of the workshop: They were scientists finding out the best ways to get teenagers to be sleepy (and get to bed at an reasonable hour). Though the concept of a study design was both difficult and new to them.

At this moment we are adjusting the scope and structure of the workshop. We need even more detailed instructions and we need to scale down a little to spend more time on the essentials:

  • Study design: What does the angle of our research mean in terms of the data we collect?
  • Data gathering: Why is it crucial we follow our initial study design instead of just going with the flow and creating lots of excess data?
  • Data visualization: What happens when we clean and analyse data, so it can presented in a visually appealing way?
  • Datastory: How do we create a context or narrative around our data, to make it compelling?

When we are done adjusting, we will be doing another set of workshops for schools during Fall 2019. We will later this spring also be testing the MUSE headbands with the library users, and see if they will be equally curious to see their own brainwaves.