Chapter 2: Data Modeling and Use - Vocabulary Study Guide

A set of vocabulary flashcards based on Johanna Drucker's study guide for Data Modeling and Use.

Data modeling

The process of creating a model that determines what features will be identified, made explicit, and represented, and in what format.

Data

Information produced through a process of abstraction. Drucker emphasizes that data are made, not simply given.

Data vs. capta

Data are not simply "given"; they are made or "captured" through categories and distinctions used for measuring, sorting, or counting.

Quantitative data

Data produced from things that can be counted or measured, such as word counts, pixels, distances, or other numerical values.

Qualitative data

Data created from interpretive or descriptive judgments, such as rating something as good or bad.

Structured data

Data made up of entities that are explicit, discrete, and unambiguous, such as numbers or true/false statements.

Unstructured data

Data that can be ambiguous or unclear, such as natural language or images.

Data structure

The formal organization of data. A table is one example because position helps determine the values of information.

Parameterization

The process of making features measurable, especially through counting.

Tokenization

Defining what can be treated as a discrete unit of data.

Data cleaning

Preparing data so it is consistent enough to be accurately sorted, filtered, counted, and analyzed.

Standardization

Using consistent formats for data types such as dates, places, and names.

Spreadsheet

A table or collection of tables used to structure, store, manipulate, and analyze data.

Relational database

A database structure that separates information into related tables so varying information can be kept distinct from consistent information.

Machine-readable

Data structured in a form that can be processed computationally.

Disambiguation

Clarifying between different possible meanings, such as distinguishing a place name from a personal name.