# Interactive Data Comic

Painted by Mars Hokkanen, Photo by Lasse Kantola

Summary
---
**Background of method**: A data comic is a method for storytelling with data using the visual language and style of a comic strip. A number of design patterns for creating data comics have been proposed^1^ that are intended to make it easier to spot patterns in the data . The **interactive** data comic is an extension of this approach in which the comic panels are not necessarily presented in a fixed order and in which game mechanisms are used to encourage finding trends in the data.

**Why to use it**: It helps to lower barriers in a co-design process for people who have less data expertise by making the process of understanding data to be fun, interactive, interesting, and straightforward. Interactive data comics can be used for navigating across data either spatially or temporally, as well as conveying a quick overview of key aspects of the data set.

**When to use it**: Interactive data comics are useful for time-pressured situations where it is important to focus on and make sense of a very specific aspect of data and there is not much time to teach complex data handling skills. The interactive data comics are intended to provide a quick insight into the data whilst also prompting new questions.

**Variants**: There are two variations of a data comic approach. In the first approach, the data cards are pre-curated and then utilised within a workshop setting. An example of this is shown below. In the other approach, data is brought into a workshop setting and people make sense of data by creating their own data comics. In this second case, some pre curation may be necessary for those with less expertise in making sense of data.

# **Variant 1 - Using pre-curated interactive data comics**

**Overview**
* Time: 1-2 hours
* Purpose: to support participants to make sense of data in a short timeframe and to identify possible new avenues they want to explore from the data
* Participants: general public and especially youth - no data expertise required
* Difficulty for facilitators: 4 stars 
* Difficulty for participants: 2 stars 
* Materials you'll need: pre-made card games, paper and pens
* Optional materials: access to dataset beyond curated aspects, for wider exploration

Description
---
There are three game types for interactive data comics:
1. **Speed data-ing**. This is a brief introduction to key aspects of the data, including their importance, the date range within which they have been collected, their spatial reach and so on. The idea is to present the data as a dating profile and in a playful way
*Speed data-ing card for data collected about invasive species in Finland*

2. **Shark Bytes**. This is a game to help people to explore temporal aspects of data and identify trends. It is based on a game in which a player guesses whether cards will be lower or higher. In Shark Bytes, the player instead guesses values of the data that go up and down. Data is curated into suitable time periods, within which the data is aggregated to a single value. Additional clues can be included in the card, for example describing any external factors that may give a clue as to what the following trend would be. While players guess on the aggregated value, the card itself - when revealed - might show more detailed information from within the time period (see example below, in variant 2).
*An example of Shark Bytes on data about invasive species. The data is curated by week and the total number of observations in that week are detailed. The aim is to guess if the next week value will be higher or lower than the previous then turn the card to see if the guess is correct*

5. **Data trumps**. This is a game to help people to explore spatial aspects of data and to guess how data might vary between different geographical areas. It is played like top trumps, in pairs, with each player taking a card and then one person choosing the attribute on their card that they assume will 'beat' the attribute of the other player.
 
*In this example, the player on the left must try to win by choosing one attribute, either lost items, invasive species, or nice places, that they think will have the higher value than the other player. The player can only see the back of the other players card which tells them which area the monitoring was done in. They must used their knowledge of the town to make their choice*

Preparation
---
1. Select data
2. Analyse data and identify key attributes (for speed data-ing), a suitable time interval for aggregating data (for shark bytes) and the appropriate geographical scale at which to categorise the data, e.g. by sub-area, by town or city, by country, etc. (for data trumps).
3. Identify any key external factors that might be influencing temporal or spatial trends in data and devise a way to include this information into the cards.
4. Design and print the card games.

Running a session
---

These cards can be left out for people to pick up and use, or they can be used during a workshop in a facilitated way following the steps below. The session could use all games, or a selection (in which case leave out steps related to a specific game)

**Steps**
1. Ask participants to work in pairs
2. Give each pair a set of speed data-ing cards and ask them to quickly read the cards, then discuss the content and ask questions if needed.
3. Lay out the shark bytes cards for each pair, with only the first card facing upwards (there may be several sets, for different attributes). Explain briefly the rules of the game. Ask the pairs to guess higher or lower, using any additional knowledge from the cards or anything else they happen to know. Ask the pairs to discuss why they think they were either right or wrong in each guess.
4. Give each pair a pack of data trumps cards and explain the rules. Ask each pair to play the game and to discuss their findings.
5. ***Optional 1***: provide access to the wider data set and allow them to explore outside the constraints of the cards.
6. ***Optional 2***: ask participants what other data or information they would be interested to look at, based on what they foudn in the cards.
7. ***Optional 2***: ask participants to create their own data comics from different data sets.

**How to document**
Surveys, questionnaires, interviews, videos and photos

**Analysis**
Inductive thematic analysis, Qualitative analysis

# **Variant 2 - Supporting workshop participants to make their own interactive data comics**

**Overview**
* Time: 2-3 hours
* Purpose: to support participants to make sense of data and identify what aspects of the data sets are important for them and to communicate this to others.
* Participants: general public and especially youth - basic data expertise beneficial
* Difficulty for facilitators: 2 stars 
* Difficulty for participants: 5 stars 
* Materials you'll need: comic templates/instructions, data exploration prompts, pencils, markers, and blank paper or card for sketching (possibly cut already into card shape, if not provide scissors so participants can choose their own shape and size)

Description
---
In this activity, participants will examine a data set and then plan and optionally also create their own interactive data comics. The participants may work in groups both in making sense of data and in creating their interacgive comics. Groups would then have the possibility to swap their data comics. Groups may have either the same datasets or they could make comics on different data and then share the knowledge.

The purpose of the data templates is to scaffold the planning of data exploration, articulating what is interesting about the data, which aspects to focus on and understand what types of analysis might be useful for the problem at hand. The insights from this process may help to explain to a data expert what to look for and why, thereby to support conversations between problem owners that may have less skills for using data, and data scientists who lack the local knowledge.

There are three game types for interactive data comics and participants could make one or all of these.

1. **Speed data-ing**. Participants create a brief introduction to key aspects of one or more datasets (that have some overlap).
*Speed data-ing card to get to know about phosphorous levels from a lake monitoring dataset. High levels of phosphorous indicate the water is polluted*

2. **Shark Bytes**. Participants create a card game where players guess trends upwards or downwards in data that has been aggregated within certain time intervals.
 
*In this example - using lake monitoring data divided by decade - additional information is provided about actions taken to imrpove lake quality, so people guess whether phosphorous rises or falls baswed on this additional information*

5. **Data trumps**. Participants create a card game in which players have to select one attribute of a dataset within a specified geographical region that they think will have a higher value (within a certain time period) than a card held by another player (see example above, in variant 1).

Preparation
---
1. Select data
2. Determine a strategy for workshop participants to explore the data, either creating and printing out visualisastions, through an interface, or by providing instructions for obtaining and visualising the data.
3. Create comic templates, inspiration sheets, instructions and card prompts, as needed for running the session.

Running a session
---

The activities will be described using the following example of a data set.

A very large lake has been monitored 4 times a year over 5 decades. The monitoring activities have captured levels of phosphorous and chlorophyll in the lake, at different parts of the lake. These are key indicators to the level of piollution in the lake. Monitoring activities have also captured the varying pH, oxygen and iron levels, the temperature of the lake at time of monitoring and the clarity of the water.

**Steps**
The following lists the steps for the workshop. The creating stage is elaborated in more detail below, for each of the possible card games.
1. **Framing**. Introduce the participants to the interactive data comics they will create by allowing them to play with some existing version of the cards, or by demonstrating it to them. Separate participants into small groups.
2. **Creating** Participants create Speed Data-ing cards and then one or both of Shark Bytes and Data Trumnps
3. **Sharing** groups share their comics with each other and then share their findings from each others data comics.
4. **Wrapping up** Participants discuss new avenues for data exploration.

**Speed data-ing**.
1. Participants examine different attributes of a dataset and decide on two or three to turn into data story 'characters' to follow. *Example: they decide to follow phosphorous and chlorophyll in the lake*
2. Participants do a small amount of research on their chosen character(s) and sketch a picture to represent the character.
3. Participants look for key facts about this character from the data, such as when it first appeared in the data set, or anything else interesting they might find. *Example: phosphorous is a known indicator of lake pollution and causes conditions where algae can bloom. Algae can affect lake wildlife and can be toxic to humans and pets. Wastewater from factories is one source of excess phosphorous*.
4. Participants compile all of the information they have found into a speed data-ing card, that others can read to get to know about this attribute in the data.


**Shark Bytes**.
1. Using time series graphs, either pre-curated or made by the participants, the participants try to find temporal patterns in the data of for each of the characters they are following. Patterns could be recurring cycles or upward or downward trends. *Example: the following graph allows identification of a downward trend over time in phosphorous levels in the lake. The data spans 5 decades and dividing this data into decade and taking a mean value for each decade is a useful way to demonstrate the trend*.
2. Participants discuss why such patterns might occur and may search for additional evidence of theories they make. Card prompts may be used to help participants know what to look for, e.g. showing examples of data cycles, or trends.
3. Participants choose one or more characters to turn into a shark bytes interactive data comic.
5. Participants then decide at what time interval they want to aggregate data. They should aim at a time interval that yields between 5-10 cards maximum.
6. Participants create a card for each time interval (and for each character, if they chose more than one) and include any activities that might be causing a fluctuation in the values they are intending the player to guess. They might also include prompts and questions to help them think about what will be on the next card, when they turn it over.


**Data trumps**.
1. Participants explore spatial aspects of the data in relation to the characters they are following and try to identify differences between regions. *Example: the lake data is monitored at different places and there have been different activities over time close to those places, leading to differences in pollution levels*.
2. Participants decide which regions they will use for their Data Trumps game and which time period the game will be about - this time period should be signalled somehow to the players. *Example: the lake data spans 5 decades but the participants might choose just to compare the lake during its most polluted first decade, where the biggest differences between regions will be more apparent*.
3. Participants create a trump card for each region. The back should identify the region to the other player so they can guess which attribute from their region will beat that region. The front should list the attributes and the values in the chosen time period. *Example: if the participants have chosen phosphorous, chlorophyll and pH they list the mean value from the first decade against each attribute* (see Data Trumps example in variant 1, above).


**Method originators:** Annika Wolff and Tanvir Hasan

**Further Reading**
Please Read more about the [LUT Case study](https://hackmd.io/UQclx_e2Q82sy7ZuvkIGGg) where this method has been applied.

**Information summarized from the research article**
*CHI ’22 Extended Abstracts, April 29–May 05, 2022, New Orleans, LA, USA © 2022 Copyright held by the owner/author(s). ACM ISBN 978-1-4503-9156-6/22/04.
https://doi.org/10.1145/3491101.3503561*
*Authors: Md Tanvir Hasan, Annika Wolff, Antti Knutas, Anne Pässilä, Lasse Kantola*

*Footnotes*

^1^ Bach, B., Wang, Z., Farinella, M., Murray-Rust, D. and Henry Riche, N., 2018, April. Design patterns for data comics. In Proceedings of the 2018 chi conference on human factors in computing systems (pp. 1-12).

###### tags: `datascape toolkit` `toolkit` `method`