Reading the articles for Monday on mining data reminded me of the “revolution” in Classics in the late 80s and early 90s when Perseus was first introduced. At the time, it revolutionized the field: before Perseus, a brilliant classicist was a scholar who knew all the iterations of a particular aorist verb form in Aeschylus and thus knew the meaning and context of the verb. His knowledge (and it was usually his) was based on years of reading Aeschylus (and the other tragedians for context), spending long hours writing verb forms on notecards, and publishing esoteric articles on the language. (We are philologists!) After Perseus, it became so much easier to just find all the iterations of a particular word or words, collate them, contextualize them, and analyze them.  But had the field gone farther?

But first, let me take you to the way back machine. In college in the 70s, I used a typewriter and wrote in by hand my Greek passages for my essays; my husband, who is a sociologist, used punch cards for his research and was considered cutting edge sophisticated. In the eighties, my friends and I in Classics and Art History hacked our machines and got our dot-matrix printers to print Greek AND EVEN THE DIACRITICS!! We were cool, or thought we were. And then came Perseus.

The Perseus project itself recognizes that digital humanities has changed and that there is a huge need for clean data and machine actionable knowledge. It looks like that is happening  at the Perseus site, but not that Classicists are following, at least that I can find. Only last January (2014) was there the inaugural meeting at AIA/APA for the Digital Classics Association; the title of the panel was “Getting Started in Digital Humanities.” There is a CFP for NELA on digital humanities and the classics for May 2015.  Here is an interesting video about the use of computational photography. But this seems to be the seeds of the revolution.

There is lots more that could be done using Perseus digital repository, and it not just focused on Greek and Latin areas of research.

Source: Mining data