This paper details the process of creating a workflow to extract, structure, and
categorize the text of historic-period cookbooks for future analysis using visualization
applications. This includes a consideration of bias in both data science and data analysis
projects. After design of the initial database and workflow, the project went through three
additional rounds of testing that showed the possible limitations of the initial schema and
controlled vocabularies and led to specific changes in the database. The paper considers
how the database can be used to ask questions of the data, and presents possible strategies
for answering these research questions. The paper concludes with a brief discussion of
the possible future for textually based data science projects and cookbook analysis.
Identifer | oai:union.ndltd.org:bu.edu/oai:open.bu.edu:2144/42622 |
Date | 18 May 2021 |
Creators | Kitchings, Laura |
Contributors | Metheny, Karen B., Elias, Megan |
Source Sets | Boston University |
Language | en_US |
Detected Language | English |
Type | Thesis/Dissertation |
Rights | Attribution-ShareAlike 4.0 International, http://creativecommons.org/licenses/by-sa/4.0/ |
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