What is Open Data?

GTFS is an "open data specification."

Open Data is non-proprietary, free, and available to anyone for re-use and redistribution. A data specification standardizes how a certain type of data is organized. Establishing agreed-upon data conventions ensures producers and consumers can easily share data, and shareability brings about interoperable systems.

GTFS can be called an open data specification because:

1. it is free and available for anyone to use,

2. its development community includes a diverse group of stakeholders,

3. it has a democratic governance system.

GTFS is collaboratively improved and reviewed by participants globally, drawing expertise from transit agencies, operators, data producers, data consumers (like apps), and governmental entities.

Given GTFS's status as an open data specification, the transit information organized in a GTFS dataset is likewise meant to be publicly available. This fosters the free exchange of information about transit services, providing riders, planners, and governmental entities with access to accurate and up-to-date transit information nationwide, and beyond.

Principles of Open Data

From https://project-open-data.cio.gov/principles/:

In general, open data will be consistent with the following principles:

• Public. Consistent with OMB’s [Office of Management and Budget] Open Government Directive, agencies must adopt a presumption in favor of openness to the extent permitted by law and subject to privacy, confidentiality, security, or other valid restrictions.

• Accessible. Open data are made available in convenient, modifiable, and open formats that can be retrieved, downloaded, indexed, and searched. Formats should be machine-readable (i.e., data are reasonably structured to allow automated processing). Open data structures do not discriminate against any person or group of persons and should be made available to the widest range of users for the widest range of purposes, often by providing the data in multiple formats for consumption. To the extent permitted by law, these formats should be non-proprietary, publicly available, and no restrictions should be placed upon their use.

• Described. Open data are described fully so that consumers of the data have sufficient information to understand their strengths, weaknesses, analytical limitations, security requirements, as well as how to process them. This involves the use of robust, granular metadata (i.e., fields or elements that describe data), thorough documentation of data elements, data dictionaries, and, if applicable, additional descriptions of the purpose of the collection, the population of interest, the characteristics of the sample, and the method of data collection.

• Reusable. Open data are made available under an open license that places no restrictions on their use.

• Complete. Open data are published in primary forms (i.e., as collected at the source), with the finest possible level of granularity that is practicable and permitted by law and other requirements. Derived or aggregate open data should also be published but must reference the primary data.

• Timely. Open data are made available as quickly as necessary to preserve the value of the data. Frequency of release should account for key audiences and downstream needs.

• Managed Post-Release. A point of contact must be designated to assist with data use and to respond to complaints about adherence to these open data requirements.

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