Author: The person responsible for a given dataset (or blog entry).
Data Dictionary: A file or group of files that can be used to help understand a dataset. A data dictionary can contain abbreviations, formulas, and other explanations.
DCAT: A web standard that makes interoperability possible for open data systems. DCAT-compatible open data systems can reference each other's datasets.
Delimiter: A CSV (comma-separated values) file stores tabular data (numbers and text) in plain text, with each line of the file serving as a data record. Each record is made up of one or more fields, separated by commas. This usage of the comma as a field separator - also known as a delimiter - explains the name of the format.
If a file is delimited by anything other than a comma, such as a tab or semicolon, you’ll have the option to choose the appropriate delimiter. Typically, CSV files - or “comma-separated values” - use a comma, so in most cases, you will not need to modify this.
Geodata: Dataset information that ties a dataset to a specific geographic region. Geodata can be simple (such as latitude and longitude) or complex (such as multiple points on a map, or outlines of regions).
Menus: A way of organizing content for navigation.
Metadata: Metadata is the "Who, What, When, Where, Why" of data.
In a file cabinet, metadata would be represented as the information written on the outside of each folder about the folder itself and the contents within.
Metadata contains the attributes that describe each dataset. Examples include the name of the dataset’s author, the title of the dataset, the date that it was last updated, any relevant contact information associated with the dataset, and more.
Metadata can be qualitative or quantitative in nature. Quantitative data is data that can be evaluated numerically; if the variable can be counted or measured, it’s quantitative. Qualitative data is data that is descriptive, and cannot be measured.
An example of qualitative metadata:
“Author: Jane Smith, Agency: Dept. of Transportation.”
An example of quantitative metadata:
“Downloaded: 311 times, Last Accessed: 02-02-2016, 5:51 p.m.”
When viewing a dataset, you can scroll down the page to the “Dataset Info” section to view its metadata.
Temporal coverage: The period of time during which a dataset was assembled. Some datasets are more time dependent than others (such as census information).
Taxonomies: A way of organizing content via shared terms.
The Taxonomy module provides a system for categorizing and classifying content. Each taxonomy (also called a vocabulary) has a name and a list of terms which belong to that vocabulary. For example, you might have a “colors” vocabulary with terms such as: Red, Green, Yellow, Blue. Or, a newspaper website may have a “sections” vocabulary for categorizing types of news stories: Sports, National News, International News, Weather, Science.
Tags and Topics are two built-in forms of taxonomies in Granicus Open Data.
Tags are for a more specific way to define shared characteristics between datasets - for example, “Harvest Festival” or “Annual Police Reports.”
Topics are for broader categorizations such as “Environment” or “Public Safety.”
Text formats: Granicus Open Data uses text formats to simplify formatting and layout. Plain text allows for no formatting and displays data exactly as entered; Full HTML allows for things like italics, numbered lists, and images. More on text formats.
User roles: Roles organize logged-in users based on their responsibilities. Granicus Open Data allows for several different user roles, such as Site Managers, Editors and Content Creators. An admin determines the roles for other site users.
- User permissions: Permissions determine who has the ability or authorization to use and modify the website and its content. User permissions are defined by role; for example, a Site Manager can decide that only users with the role Editor can publish datasets.