md`<p class="subheader">Domain Problem and Data Characterization</p>
1. What **domain** is the visualization coming from?
Epidemeology or world demographics
2. What domain specific **vocabulary** is used in the work?
Commonly adopte spellings of cities, example Kalkatta is on here.
3. Who is the pertinent **target audience** within this domain?
Curious citizens, more practically probably any individual who wants to use this data academically.
4. What **specific questions** does the target audience hope to answer?
What are the most populous cities from 1500 - 2018, how does the population of various cities grow over time?
Based on those questions you've identified (based on the _audience_, in a particular _domain_), you are ready to move into the next stage in the design model.
<p class="subheader">Operation and Data Type Abstraction</p>
1. What generic _operations_ are required to answer the question(s) identified above? Indicate whether each operation is a _high-level_ or _low-level_ task, as described by Amar and Stasko (in the Munzner paper).
Operations including gathering data, dividing it up by city and time period. According to Amar and Stasko, those are all low-level tasks.
2. What are the data types present in the data (e.g., categorical, continous, etc.)?
The data is continuous.
Based on the required operations and data type, you are ready to consider available encodings.
<p class="subheader">Visual Encoding and Interaction Design</p>
1. Which visual encodings and interactions were selected to support the tasks identified in the previous step?
A bar graph was used to show the differences in population, as well as, various colors to highlight different cities to distinguish region. The most populous city is placed at the top, with the next highest population underneath it.
2. We'll discuss this more in next week's notebook, but based on your current knowledge, do you believe these encodings and interactions allow users to sufficiently accomplish their tasks?
Yes and no, having every city from the same region the same color causes conflict for the user when cities from the same region are next to eachother. This conflict can lead to misconceptions.
<p class="subheader">Algorithm Design</p>
If any information is available on the algorithm design used to build the visualization, please make note of it here (if not, no worries).`