What We Learned

June 7th, 2011

We found a variety of insights and ongoing implications from this project, ranging from the technical to the interpretative. In no particular order:

1) We realized that to pursue intellectual agendas such as the differing crime patterns of women and men we needed multiple points of entry rather than a single massive visualization. We thus followed several tracks at the same time, including data warehousing (see below), mathematical models, and small-to-large visualizations.

2) We had not anticipated how helpful data warehousing would be. It comes out of business intelligence but served us well on the project and was not something many of us were familiar with. It struck us that we need to look more at business processes for ideas for this kind of work.

3) Another technique we did not anticipate in advance is how helpful quick modeling with Mathematica would be. Team members Tim Hitchcock and Bill Turkel used Mathematica to create prototypes of various text mining and visualization tools. One advantage of using Mathematica is that it is very easy to build dynamic prototypes that can be shared with colleagues to get their feedback.

4) As a team we noticed an interesting interaction were we had to accept each others’ approaches. This was particularly important in that those in the Old Bailey who had come in with an appreciation for their structured data had to come to understand how the OB could be seen as a mass of unstructured data for text mining. The text miners in the group in turn had to look more closely at what could be done with structured data. This was a fruitful exchange.

5) We are extremely proud that we got these very diverse projects to interoperate on the level of code and of interpretation, something which is often discussed in the digital humanities but rarely executed.

6) Related to 5), we have a newfound appreciation of the power of APIs, and indeed following our project JISC is now advising projects about the usefulness of APIs.

7) We have several outcomes that are leading to additional work, including a new SSHRC grant to the Canadian partners based on the Mathematica work, a new plug-in for Zotero that works beyond Voyeur for text mining collections, and the aforementioned API admiration from JISC.

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