Problems, and (Starting on) their Solutions

Importing the spreadsheet data, however, was only the beginning of making a functional database. A host of problems, inconsistencies, and challenges emerged once the data was imported. Three of the most pressing were related to (1) dates, (2) places and agents, and (3) how to indicate ambiguity or uncertainty. I will briefly describe the problems I faced with document dates—which are broadly illustrative of the small, scattered, and finnicky issues that popped up while making the database—and how I went about solving them. Then in the remainder of the essay I will describe in some detail how I went about populating the Places and DocumentPlaces tables, which is based on the same principles that have gone into formatting and populating the Agents and DocumentAgents tables (still in progress). 

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Sample selection from the Dates table

Dates
As I determined in the initial brainstorming stage, I wanted to separate years, months, and days into separate categories for each document. However, doing so while also retaining theseas simple attributes (or fields) of the Document table—Year, Month, and Day—was not as simple as it seemed. For one thing, I needed a way to track information related to specific time categories. Some documents, for example, include two dates—one on which it is “actum” and another on which it is “datum.” In other documents, the editors had helpfully qualified dates (or any segment of a date—year, month, or day) with adjectives like “before” or “after.” Keeping track of details such as these was not possible if the Document table only included one field for the Year. On a similar note, a document could include any combination of year, month, and day, and could have uncertainty for any or all of those elements. 

 

To solve this problem, I decided to create a separate Dates table to track temporal information about each document. 

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Dropdown menus make it easy to consistently track details compiled in value lists, and uncertainty checkboxes track temporal ambiguity with precision.

This allowed me the flexibility to track temporal qualifiers (like before, after, etc.) and other characteristics (such as actum/datum), which I compiled in a Filemaker value list so that I could rely on the simplicity and consistency of designating qualities from convenient dropdown menus when entering future time data. I also included an “Uncertainty” checkbox for each of the Year, Month, and Day fields.

by Patrick Meehan