I Love Using A Map, but Should I Use It?
By: Ahmad Baikuni
Tags: Data Visualization, GIS, Maps

Oftentimes, I really want all of my data to be visualized by a map; however, I can’t make it optimal to build a story. My thought of using a map was driven by how sophisticated it looks.

A map is just one of many tools to visualize the data. Not all data are suitably represented by a map for specific information. Is it right to use a map to compare one or more variables? or is it just too complicated?.

Even when I will use a map, I should think about whether it is precise to show the data by points, lines, or areas. I thought it will be tacky when I use points to represent a massive amount of small retails distribution.. but the scope is on a national scale!

So, here is my opinion about using a map.

[a] another example, is it a tacky points map?

When to use a map

I think when to use a map depends on what information should I provide; how should I give context for the data[1]. This citation can be used as a reference to explain that.

Maps do more than show where things are. They also spark curiosity and prompt further questions, such as, What is nearby? Why does it look like that? And has it always been that way?

I rely on a map to describe relations between the data to the surrounding. Data can be influenced by or influence other data regarding the distance between them. They might create a particular pattern as information. Showing what is the relation between traffic accidents and school distribution will be clearer using a map compared to other data visualization types. But, I shouldn’t always be using a map when I don’t need to provide the data location. Instead, I can use a bar graph if I just want to supply information about their value distribution. The main question before using a map is “what is the usability of the data location?”.

[b] this map depict traffic accidents and schools location. Larger circles represent fatalities, while smaller circles represent injuries. Pedestrian accidents are in red and bicycle accidents in orange

Okay, let’s say you want to use a map, especially to present it publicly. Maybe I can help you with my gig to develop a custom web-based map. Please check it out!

Points Map

Points can show the exact location of the data. If I have data of events or places or any units that have their specific location, also I want to spatially delineate them one by one, it’s appropriate to use a points map.

The main power of points is their versatility in categorizing. They can be classified by color, shape, size, or even the combination of those three. But, don’t make them too many classifications in one map, otherwise, people can get confused.

[c] I think this map is confusing

In image [b], I can see where most fatally pedestrian incidents occurred (big red dot). I can intertwine it with other data to become a piece of information, such as where it is according to the base map (most of them are around intersections). I also can conclude the frequency of accidents that occurred in the school radius. I can do that because I have the location of those accidents.

However, not all data are suitable to represented by points. Sometimes a points map just gives little sense. I have to consider the scope of my interest, if it is bigger, for example in a city with lots of traffic accident points, the map of the points will look messy. Normally, the story of a points map is about the geographical distribution or clustering of dots. But if you just need the distribution of them, try to use a scatter chart.

Area Map

While dots can accurately pinpoint the data coordinates, I don’t need that on many occasions, compared to the usage of area. I used an area map to spatially compare the data by categorizing them. Comparing areas can also give me anomaly information, which may be gestating an interesting research question.

There are many area-based map types such as choropleth, Hexbin, or a heat map. A choropleth map can manifest the comparison by colors, usually for a categorical value. When I need magnitudes from large volumes of continuous values, I can generate them with a heat map.

An area map is so powerful, I find it hard to determine a reason not to use it. Maybe I won’t use it if my data don’t have a regional attribute, or if the data in one area is the same (why should I use the map then).

Oh, it is usually an output of an analysis, so to optimally use it, I should understand the explanation of the use of the algorithm. One of the examples is when I use Kernel Density Estimation (KDE) for a heat map. One kernel shape will be better used than the other for a specific occasion.

Line Map

A line map contains lines in a network, it can be roads, rivers, or origin-destination flows. It is used to show routing, mobilization, accessibility, or a direction. Sometimes, it can also define a pattern that may give valuable information, one of the examples is when to identify watershed from rivers network.

In a line map, the lines can be classified by thickness, color, or pattern. It will open up diverse presentations for information as I need it. However, they are just a representation of the lines, so they’ve limitations in describing the spatial data (don’t use a line map to assume the condition of an area, except it has been through a certain analysis).

One thing to remember before I use a line map is, a network is a bunch of lines that are interwoven with each other, and often their amount is massive. I should be careful not to make it looks over-stacked. I think there are two traps in using it, first is the indulgence to show data as detailed as possible; and over-categorized data. A line map tends to easily over-categorized, become too crowded, then giving confusion among the audiences even for the presenter itself.

Should I use a map? Which one?

Yes, if I need to provide spatial-context information. Or, not necessarily, when the data can be more simply presented by other data visualization as long as it won’t reduce the value of the information.

Which map I should use depend on the data shape, the reason why I use them, and its aesthetics. When I have points data, it’s almost a certainty to use a point map. But, I think it’s not always that straightforward. In a particular situation, depending on the purpose of the visualization, I may need to process them to become an area map. I should set another question after I find myself to be supported by a map, “why would I use it? is it to compare or pin-point the data location?”. The other consideration is about its comfortability in view. Many aspects would affect the aesthetic of it, such as the colors, shapes, thickness, and data density.

Overall, that’s my contemplation about using a map. I need to learn more about it. So, let me know your thought!