Please welcome Mitch Fraas: Bollinger Fellow for Library Innovation, Unique at Penn blogger, and ace digital humanities practitioner. Here are his five favorite DH tools to get it done:
1. Google Fusion Tables:
Probably my go-to tool for doing quick geographic or chronological visualizations of data. Fusion tables allows users to import spreadsheets and view the data in a variety of ways. If your data includes addresses or place names fusion tables can automatically geocode and map them in no time. It also has timeline tools to display your data chronologically. All of these views can be exported and shared or embedded in websites. See the example below of a map generated from one of our manuscripts here at Penn showing the first scientific voyage of Charles Mason (of Mason-Dixon fame):
Click to see Google map
2. Batch Gecoder by David Zwiefelhofer:
There are plenty of tools out there that will batch geocode for you, i.e. take a bunch of placenames and convert them into longitude and latitude coordinates, but I like David Zwiefelhofer’s tool the best. Instead of hiding the results of the geocoding (like in fusion tables) or making you guess at how specific a long./lat. result is, or making you upload a spreadsheet, this geocoder lets users paste locations into a web form with a number of custom controls for how the results will be spit out. It uses the Google maps API behind the scenes and also gives a breakdown of how specific a geocode match is (street addresses yielding more specific coordinates than city names by themselves).
3. Pagezipper:
I’m almost embarrassed to put this tool on here because it’s so simple – but it really is a time-saver. Pagezipper is an easy in-browser tool which cuts through all those tedious “Next” or “More” buttons at the bottom of long articles or search results. Now, when I get 218 hits searching a database that only displays 10 results at a time I just scroll down and Pagezipper does the work of stitching all the results pages together into one page.
4. TextWrangler:
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I end up dealing with a lot of messy raw text and the process of getting it into some sort of analyzable state can be maddening. TextWrangler has been incredibly helpful in providing some easy tools to quickly process raw text. Tasks that used to require regular expressions or tedious manual work are now automated, like removing whitespace from the beginning of every line of text, separating lines on given characters, and batch changing capitalization. In addition, it has an easy-to-use regular expression tool which performs copy, delete, and parse functions. Unfortunately it’s only available for Mac right now but it’s worth a try.
5. Mac Automator:
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For those of us who don’t really have good coding skills but still want to use computers for what they’re good for (repetitive tasks extremely quickly) I’ve found the Mac Automator a real godsend (it comes installed on new MacBooks – look in the applications folder). A little while ago I was browsing a database but really just wanted to download a whole section of it so I could play with it as a spreadsheet and see the data holistically, sort it myself, etc. Since there was no easy interface to do this through the database itself I decided to just ‘scrape’ all the text off the page for each result (hence the term ‘screen-scraping’). Mac Automator has a number of tools which users can arrange in sequence to create programs of a sort. In this case, I had Automator take in a list of URLs I generated and then run to the web to grab all the visible text for me from those URLs while I did something else. When I returned after a few minutes I had a nice file full of text from dozens of different pages. Give it a shot – it does plenty of other great things too.
More? Sure:
Mitch is maintaining a digital humanities tool guide here, in our Net Tools guide.
WIC intern Vickie Marre posts frequently on her DH musings at the PennWIC blog, most recently: “Understanding the Digital Humanities and WIC’s Role.“
