# ¶ Glossary

**Attributes** are the describing characteristics or properties that define all items pertaining to a certain category applied to all cells of a column.

**Data** is a collection of facts, statistics, measurements, and the like that are recorded (or should be recorded) using standardized methods.

**Data collection** is a systematic process of gathering observations or measurements.

**Data Visualization** is a graphical representation of data.

**Metadata** is often simply defined as "data about data" or "information about information".

**Data points** are single units of data or single observations, e.g., a single measurement or a single geolocation point.

A **Database** is a systematic collection of data.

**Dataset** (or **data set**) is a collection of data. Typically, it is structured and housed in a tabular form (e.g., a spreadsheet).

The **data life cycle** represents all of the stages of data throughout its life from its creation for a study to its distribution and reuse. The data lifecycle begins with a researcher(s) developing a concept for a study; once a study concept is developed, data is then collected for that study. 

**Data Literacy** is the ability to read, understand, create, and communicate data as information.

**Geospatial data** is defined in the [ISO/TC 211](https://en.wikipedia.org/wiki/ISO/TC_211) series of standards as data and information having an implicit or explicit association with a location relative to Earth.

**Quantitative data** relates to the quantity of something, and typical examples of quantitative data are numbers.  

**Qualitative data** is used to characterize objects or observations, which can be collected in a non-numerical and non-binary way, such as languages.

**Structure data** refers to data that resides in a fixed field within a file or record, e.g., spreadsheet.  

**Unstructured data** refers to a bucket of content or data points that are not organized and categorized, e.g.,    PDF files, image files.