Metadata & Databases

In the previous unit of the Digital Humanities Coursebook, I felt extremely comfortable with the concept and depth of data, due to my previous knowledge and experience with what data is. During the metadata unit, I was significantly less comfortable and accustomed to what it is. The textbook provided a great, but lengthy, description of what metadata is, saying, "Metadata performs many functions. Most often, as in the example of 'Get Info' just given, it is descriptive. Metadata can also be administrative, help- ing to organize the data in large sets of records. In addition, it can be operational, giving data a role or task, such as the relation of one file to another... To reiterate, metadata is information used to describe data, objects, or records. Metadata can be attached to objects or records, but it also stands in as a surrogate" (Drucker 52, 53.) Metadata is essentially data about the data, providing as much description about the data as possible. Metadata is a crucial component of all digital projects, and it is certainly present in my project, in the forms of citations and as specifications of what is being displayed. I am certain that metadata will continue to be a looming presence in the projects we create this semester.

I feel that most people who have any knowledge of data also have a grasp of what databases are, and this chapter on them just further elaborated upon my preexisting knowledge. Databases can vary in simplicity and depth, and it further contributes to how vast the field of digital humanities is. The textbook gave an extremely easy-to-grasp description of the differences in databases, saying, "Data can be big without being complex: a massive number of entries in a very simple spread sheet might list all 300 million people in America by age, or, by first name, or by height and weight. Data can be deep without being big: a spreadsheet might contain highly detailed information about a small number of entries—a hundred books and their authors, characters, plots, sentiments, vocabulary, sentence length, editions, page numbers, annotations by multiple readers, materials of production, reception histories, and many other details" (Drucker 70, 71.) Some data is able to be presented on a flat spreadsheet database, while other forms of data may need something a bit more specific for the database. The concept of the range of databases took a lot of brainpower to dissect, but once I grasped it, it all felt completely natural and easy to understand. I know that these concepts apply to my project, as there are multiple data tables and graphic data that connect to one another.


Comments

  1. I liked your example about data being 'big without being complex.' I think it's a good way to explain how data can be lengthy yet simple at the same time.

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  2. I love the quote you used about data big big without necessarily being complex. This stuck out to me as well in the reading, and really provided food-for-thought in how big sums of data really can be. It made me think that if it's not complicated, certain data sets must just be truly massive to require their own "base."

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