# Week 3

## Andy Kirk

### Lecture on qualitative data

{% embed url="<https://www.youtube.com/watch?v=hTpSogtRhJs&feature=emb_logo>" %}

In Kirk's talk about qualitative data he explains this dividing it into 6 categories. I've written down the 6 categories including some examples.

**1| Classifying & transformation**\
\&#xNAN;*Collecting, converting and extracting data*

![Multiple data types](https://2269634644-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-MSXyFrHaFxhHbbeVqPW%2F-MUIKvkfM7nLdAM3FLDI%2F-MUIX5jXZ_MOFSy3ZjW3%2FSchermafbeelding%202021-02-24%20om%2010.22.46.png?alt=media\&token=8877f358-e60b-4ee3-aca6-f49210899df7)

![](https://2269634644-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-MSXyFrHaFxhHbbeVqPW%2F-MUIKvkfM7nLdAM3FLDI%2F-MUIeXYkJbxRYTdz2ig_%2FSchermafbeelding%202021-02-24%20om%2010.32.17.png?alt=media\&token=85c5f0a2-ed3a-44e6-a63d-ef62c60b3f97)

He explains how data isn't just numbers. The way he **collected data** from the Seinfeld show is a great example on how you can create your own data from something that was not intended to be analyzed as data.

![](https://2269634644-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-MSXyFrHaFxhHbbeVqPW%2F-MUIKvkfM7nLdAM3FLDI%2F-MUIe_zgrlKSAB4BhcHb%2FSchermafbeelding%202021-02-24%20om%2010.34.51.png?alt=media\&token=4dac5fb0-2af9-470d-bd08-fdc4142bb4cd)

The way he started **color-organizing** this document was very insightful to me.&#x20;

**2| Categorical charting**\
\&#xNAN;*Charting comparisons and distributions*

Examples of cool projects where more difficult data is being compared.

{% embed url="<https://www.designboom.com/readers/dima-yarovinsky-visualizes-facebook-instagram-snapchat-terms-of-service-05-07-2018/>" %}

{% embed url="<https://app.visualpedia.igg.cloud/stories/heatscore-password-patterns/>" %}

{% embed url="<https://pudding.cool/projects/vocabulary/index.html>" %}

{% embed url="<https://yougov.co.uk/topics/lifestyle/articles-reports/2018/10/02/how-good-good>" %}

**3| Hierarchical charting**\
\&#xNAN;*Revealing part-to-whole and hierarchical relationships*

Interactive visualizations where something is being displayed as a part of a whole. This can be very interesting for my personal project.

{% embed url="<https://data-viz.nesta.org.uk/skills-taxonomy/index.html>" %}

{% embed url="<https://www.behance.net/krunalpalande?tracking_source=search_users_recommended%7Ckrunal%20palande>" %}

**4| Relational charting**\
\&#xNAN;*Exploring correlations and connections*

{% embed url="<https://www.visualisingdata.com/2020/09/new-project-the-seinfeld-chronicles/>" %}

{% embed url="<http://tulpinteractive.com/>" %}

**5| Temporal charting**\
\&#xNAN;*Plotting discrete and  continuous trends over time*

{% embed url="<https://www.scientificamerican.com/article/the-language-of-science/>" %}

{% embed url="<https://www.nytimes.com/interactive/2019/01/26/opinion/sunday/paths-to-congress.html>" %}

**6| Spatial charting**\
\&#xNAN;*Mapping spacial patterns trough overlays and distortions*

{% embed url="<https://www.vox.com/policy-and-politics/2018/9/28/17914308/kavanaugh-ford-question-dodge-hearing-chart>" %}

{% embed url="<https://www.nytimes.com/interactive/2019/02/15/upshot/british-irish-dialect-quiz.html>" %}

**The interview Frank Kloos en Maaike van Cruchten did with Andy Kirk**

{% embed url="<https://www.youtube.com/watch?v=MO6I7YMd9V0&feature=emb_logo>" %}

**Summary**\
Deciding what you are going to collect has everything to do with the reason why you are doing the project in the first place. The reason for your project can give you a perspective of what kind of data you want to use.&#x20;

{% hint style="info" %}
Tip **|** Don't set the bar too high and learn to live with knowing there are blind spots.&#x20;
{% endhint %}

**Everything** is qualitative data. Instruments convert qualitative to quantitative. These instruments make it seem like this kind of data/information are facts but they are just instruments to make it easier to collect. There is still somebody behind it. Nothing is objective. As information designer we have to recognize the **'non-objectivity'** in data.

> 'Impressionism in data visualization'

## Observation Exercise 1

The video where the exercise is explained.

{% embed url="<https://www.youtube.com/watch?v=h1UhH49kxpI&feature=emb_logo>" %}

### Proces

*After i watched the video i took some pictures of my room in Amsterdam. I took it from different angels so you can see everything.*

![](https://2269634644-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-MSXyFrHaFxhHbbeVqPW%2F-MUD3qvPC9fwGLZ472jd%2F-MUD3zB_4haEwmOpgWQs%2FIMG_9107.jpeg?alt=media\&token=81adcc69-1719-46fd-afb1-c35338466b9f)

*The picture above is important because this is the part that i did not draw because this wall is the perspective i was drawing from.*

![](https://2269634644-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-MSXyFrHaFxhHbbeVqPW%2F-MUD3qvPC9fwGLZ472jd%2F-MUD4lEz750AnIj6Mk0F%2FIMG_9108.jpeg?alt=media\&token=86d8d58b-a325-43ca-86c4-94478eb5c1f9)

![](https://2269634644-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-MSXyFrHaFxhHbbeVqPW%2F-MUD3qvPC9fwGLZ472jd%2F-MUD4xEU4XvSpAXAg7hK%2FIMG_9109.jpeg?alt=media\&token=d4312848-df26-47df-af25-a4c949685688)

![](https://2269634644-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-MSXyFrHaFxhHbbeVqPW%2F-MUD3qvPC9fwGLZ472jd%2F-MUD50yesCn4pr4RIoEC%2FIMG_9110.jpeg?alt=media\&token=90aead9e-53fd-473b-ac9d-a713f5be80f6)

![](https://2269634644-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-MSXyFrHaFxhHbbeVqPW%2F-MUD3qvPC9fwGLZ472jd%2F-MUD57fjLLjHUB6yXR0H%2FIMG_9111.jpeg?alt=media\&token=f46ed6a2-f096-49c1-90cc-693af67d0508)

![](https://2269634644-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-MSXyFrHaFxhHbbeVqPW%2F-MUD3qvPC9fwGLZ472jd%2F-MUD5GjHj5flZuUOW5EX%2FIMG_9112.jpeg?alt=media\&token=76393f99-7ff0-487d-aa0b-2686efe6ce2a)

*Same objects you saw on the first photo but now from another perspective*

![](https://2269634644-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-MSXyFrHaFxhHbbeVqPW%2F-MUD3qvPC9fwGLZ472jd%2F-MUD5MkbG2XRNCkMK32T%2FIMG_9113.jpeg?alt=media\&token=1dcfc813-cc06-4f47-803b-54146722e04b)

*As i stated earlier, I started drawing my room from the perspective of one wall. After i drew the 'skeleton' of my room i started to add details and after that details to the details. I decided to only annotate the objects that have personal value to me or the objects that i didn't draw clear enough.*

### **End result**

![](https://2269634644-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-MSXyFrHaFxhHbbeVqPW%2F-MUD3qvPC9fwGLZ472jd%2F-MUD5_VtTHlOGnc5A57p%2FIMG_9114.jpeg?alt=media\&token=16ac0f0b-430d-4ea5-9812-e14d8576d34d)

## Project Plan

### (Refined) subject

**Current situation**\
Women are more likely to die from heart attacks because the symptoms they have often do not match with the ones that men have. Women (more often than men) receive misdiagnoses and/or drugs because they are assessed as if they have a man's body. Another important example is that women are much more vulnerable in a car accident because the safety measures are built on men's bodies. This last example will be the **focus** of my project. That does not exclude that I may include the other examples in the visualization.

![the idea for the project came from this book i was reading by Caroline Criado Perez.](https://2269634644-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-MSXyFrHaFxhHbbeVqPW%2F-MTtpwN2BYd1rU0k2RAv%2F-MTtq9qry0wXpTZIpbYX%2FInvisible-women.jpg?alt=media\&token=07d24b15-94c7-4b74-ac03-32cb64d19e06)

![Illustration of the almost invisible women next to very present men.](https://2269634644-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-MSXyFrHaFxhHbbeVqPW%2F-MTtpwN2BYd1rU0k2RAv%2F-MTtqCZmNUnz1LWY39s6%2FInvisibleWomen_BookCover_HeroCrop.jpg?alt=media\&token=c510608f-5730-4a1b-a4a2-24d8e674e3fb)

**For who am i making this project?**\
The stakeholders of my project women. Women **worldwide**. After reading the book "Invisble women" I came to the insight that entire segments of our society are designed based on a man. This is not because the women are forgotten on purpose, but because the man is seen as standard (in the broadest sense). This standard often creates a disadvantage for women in very subtle ways. Women are my stakeholders because they have an interest in **change**. Change only comes when a problem is raised and that's what I'm going to do with the project.

The "Cross Cultural Data Literacy" project has an interest if I do my project well because they can then promote the project and **emphasize the importance** of data visualizations.

The "visitors" of my data visualization (whose gender and age can diverse) are also a group of people that I have to take into account when I design and implement. I will have to test and **improve the flow** and **clarity** of my visualization during my project.

**How am i going to challenge myself?**\
The only requirement i have from CCDL is to make a visualization that has a link with health worldwide. I have internalized this question by focusing on the **inequality of women** in the **medical world**.

The project is going to be a creative challenge because I can challenge myself visually and conceptually. In the performance I can further develop and apply my visual skills. In addition, I strive to cast the concept of the visualization including the interactive experience in a **creative** and **original form**.

The subject I am going to work on is **complex**. The story I want to tell is an enlarged example of a much larger and more complex problem in society. The unequal position of women (in the medical world). The increased risk of women in cars is a specific example that I have to explain with the contextual examples that important.

**Design Challenge**

> *How can I, using an i**nteractive experience**, inform about the **global inequality** of women and health and with the focus on the **increased risk of car accidents** with the aim of raising **awareness** of the human side of **(missing) data** on this topic?*

**Questions i am going to research**

* **Inequality in the medical world**\
  \&#xNAN;*What are examples of women's inequality in the medical world?*\
  *Why does this inequality exist?*\
  *Are these examples different or different in other parts of the world?*
* **Car accidents**\
  \&#xNAN;*Why are women at increased risk of injury in car accidents?*\
  *How can visualize the increased risks of women in cars?*<br>
* **Develop**\
  \&#xNAN;*Which data and the story behind it do I choose to visualize?*\
  *Which tools / software can I use to visualize my found and collected data*\
  *How do I make a complete and correct story of my visualization?*

**Product vision**\
In order to visualize an ethical topic using data, it is important to include all contextual factors and other important information for understanding the topic. That is why my vision at the moment is to tell the story in a **funnel-like form**. Starting from the global beginning and ending with a specific example clearly illustrating the complex problem. I will be able to create this funnel using what they call a **"scrolly"**. By scrolling on a web page, a story is presented in an interactive way. An example of how this is properly applied is the Atlas of Sustainable Development Goals 2020 From World Development Indicators

{% hint style="info" %}
[**Link**](https://datatopics.worldbank.org/sdgatlas/goal-5-gender-equality/)
{% endhint %}

![Scrolly used for the world bank (screenshot from the link i used)](https://2269634644-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-MSXyFrHaFxhHbbeVqPW%2F-MTtpwN2BYd1rU0k2RAv%2F-MTtqFXqV2kHbSTHqsBJ%2FSchermafbeelding%202021-02-18%20om%2018.15.52.png?alt=media\&token=38b10ebe-acc9-45ba-a4e1-bfafb6042c9e)

**Planning**\
You can take a look at my planning by clicking on the **link** below.

{% embed url="<https://miro.com/welcomeonboard/dK6KopdjzfqzYNMe4V7OzhyWIzbdw8lr5iPhbMNZDmzipmF8D7Fih8ryDyWTceaF>" %}

![Screenshot of the Miro board](https://2269634644-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-MSXyFrHaFxhHbbeVqPW%2F-MTtpwN2BYd1rU0k2RAv%2F-MTtq--tgO34MFWHkswP%2FSchermafbeelding%202021-02-19%20om%2011.30.45.png?alt=media\&token=3b2c2de7-6650-4b4a-b492-d4ac04958d81)

## Interesting article about the book 'Invisible Women'

This is my plan on how to work on the project and end up with a good quality product at the end.&#x20;

**Possible sources**

{% embed url="<https://opendata.cbs.nl/#/CBS/nl/>" %}

{% embed url="<https://www.cbs.nl/nl-nl/visualisaties/verkeer-en-vervoer/verkeer/hoeveel-mensen-komen-om-in-het-verkeer->" %}

{% embed url="<https://www.volkskrant.nl/columns-opinie/vrouwen-kunnen-niet-autorijden-en-dit-is-waarom~b2eed10a/>" %}

{% embed url="<https://www.demorgen.be/nieuws/de-man-blijft-de-maat-van-alle-dingen-seksistische-data-benadelen-vrouwen-in-het-dagelijkse-leven~bffb55ff/>" %}

{% embed url="<https://www.maastrichtuniversity.nl/nl/nieuws/big-data-healthcare>" %}

{% embed url="<https://www.evoke.org/articles/july-2019/data-driven/deep_dives/the-dangers-of-gender-bias-in-design>" %}

**Data collection methods**

* Desk research | *Datasets and articles*
* Books | *Research and quotes from books*
* Interviews | *Soft data from conversations*
* Observing&#x20;

### Collaboration

The global perspective i have mentioned before is very important to me and the end result. To present a global perspective it is important to collaborate with the international students in my team. I am planning to collect data from my own environment first and after that collect the same type of data from the other regions/countries. By first deciding what data I am going to collect from my own environment I know i will have a clearer view on what data exactly i need from the others. This will make that process less messy. This is my plan on how to work on the project and end up with a good quality product at the end.

## Conclusion week 3

This week i continued to research using the book Andy Kirk's lecture as resources. In the coming week i will start to come up with a first concept and make a first sketch so i can start collecting data in a **targeted** manner.

This week i was very focused on how I am going to work on this project. From next week on I will make a more clear start on actually working on a first **concept.**


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