This chapter introduced the characteristics of digital data and how they are represented. These representations included data storage, management, and manipulation, leading to new insights and information. We have identified the difference between a feature (or object) and its associated attributes that describe the feature. The four attribute measurement scales (nominal, ordinal, interval, and ratio) enable social scientists to systematically measure and analyze phenomena that cannot simply be counted. These levels, which subdivide the categorical and numerical distinctions introduced in previous chapters, are important to specialists in geographic information because they provide guidance about the proper use of different operations and mapping techniques. Many of these operations are carried out in a database management system, allowing users to query, store, merge, and manipulate data to create new information within numerous available systems that offer varying levels of sophistication in analysis. A key type of data discussed in this chapter is metadata, or the data about the data. Metadata includes documentation of the content, quality, format, ownership, and lineage of individual data sets. Finally, the chapter ended with introduction of two predominant data representation strategies, known as vector and raster. Both approaches allow us to represent the real world in digital form through representative samples of locations. Most maps that you encounter online or on your smart phones and related devices are generated from data collected and organized using one or both representation forms.