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From Text to Map

Using digital tools and methods to represent your research as a map

Extracting Text

You can approach text extraction a few different ways. The options below will depend on your skill level, the format of your source, and project outcomes you envision.

Manual input

The tried and tested method of reading your text and manually recording places and other objects of interest that you may want to map will continue to work. As you record places, consider what accompanying data you may also want or need to build a successful map.

Text markup

Your research may benefit from annotation with a markup language. For example, some mapping projects emerge from creators using XML and the Text Encoding Initiative (TEI) Guidelines to markup their text or corpus. From there, the creator can add additional meaning to their text (such as coordinates) or extract place names to build a .csv file that will support a map.  

Programming/Coding

If you know a programming language, you can write a script or use an existing library or package to extract text from your source. This will most likely require you to transform your source into a plain text format. If you do not have experience with a programming language and you are still a beginner with map making, we recommend building up the skills in the remainder of this guide before pursuing a programmatic approach.

A note on file types

This guide focuses on plain text files that will produce vector data (points, lines, and polygons). This guide assumes your text extraction has resulted in one of the following file types:

  • .csv
  • .tsv
  • .json

There are other file types like .kml and .shp (among many others) that may be of use, but those will not be covered in this guide.