Pro: Easy to edit data, powerful geocoding engine, mixes well with other google spreadsheets, includes lots of other visualizations beyond mapping.
Con: Making a map can be confusing, more difficult to make attractive maps, requires a non-Haverapps google account.
Pro: Tied to very rich data visualization features, connections to time are fairly easy.
Con: Requires software download, takes some time to get used to, free version means everything is public. PC only.
Pro: Default maps are beautiful, very powerful, relatively easy to pick up the basics.
Con: Free maps must be public, very limited free storage, mostly relies on a basic knowledge of SQL and CSS.
Pro: Easy to symbolize using the data, can view data and map side-by-side, nice user controls for sharing.
Con: You don't have control over labels, nor over the contents of the info windows, interface takes some getting used to.
Pro: Beautiful maps, TileMill has many features, only limited by one's CSS ability.
Con: MapBox is very limited, TileMill requires CSS for full functionality, even simple features require significant work to implement.
Note: This is not an exhaustive list, but it covers a sampling of tools which are well-suited for a wide variety of map types
Photoshop (or other Image Editing tools) -- In Photoshop, you're map will not be tied to the earth, and you will not be able to take advantage of geography for any of the analysis or visualization that the other tools afford. However, if you want to design a single map for a print publication, and you are beginning from a scanned map, this is often (usually) a great option. Here's a tutorial done by one of the Haverford Digital Scholarship students.
Omeka with Neatline -- For more serious narrative projects, Omeka with Neatline is a platform for creating spatial narratives. It has more overhead to set up and use than the other tools above, but is designed for historic and other narrative ways of looking at geography and other sources.
Making an attractive map starts with the data. Before starting, think about what type of map you want to make and what types of data you will need. For example, to make a heat map requires numerical data for intensity and geographic data for location.
Take a look at the data you have and think about how to fulfill these requirements.
A note on geographic data:
Geographic data can come in many forms: longitude and latitude pairs, city names, state names, country names, and more. Some of these mapping tools can be picky when it comes to which the form of geographic data. For example, Tableau Public sometimes has trouble locating small towns by name. It may be easiest to simplify your data via geocoding, which will give you geographical coordinates.
GPS Visualizer is one option for geocoding your data. If necessary, try poking around to find one that better fits your purpose.
.csv stands for Comma Separated Values. It is a common file type for many types of data. It is an easy way of a saving a table or spreadsheet. Each value is separated by a symbol, most often a comma or semi-colon. Here is an example of a few lines of csv data:
State, Year, Number
WA, 1999, 50
PA, 1999, 73
NY, 2000, 96
Check out sample data for these tutorials bit.ly/1z1cWEm
There are many different types of maps. It is important to choose a map type before starting. All have advantages and disadvantages compared to the others. Think carefully about what information you want your map to convey before choosing.
The most common types are:
Chloropleths: regions are colored based on their value. For example, divorce rate by state.
Pinpoint: simply show the locations of various data points.
Proportional Symbol: a combination of the first two types. Symbols represent locations and the size and/or color of the symbol is based on that locations value.
For more information, see these links: