Skip to main content

Currently Skimming:

Chapter 7 - Conclusions and Next Steps
Pages 54-57

The Chapter Skim interface presents what we've algorithmically identified as the most significant single chunk of text within every page in the chapter.
Select key terms on the right to highlight them within pages of the chapter.


From page 54...
... 7.1  Key Findings Based on the interviews and literature and information review, the following are the key findings about data sharing for transit agencies. Transit Agencies Share Data Frequently and See Many Benefits • Transit agencies collect data on the transit system, including route, schedule, and vehicle location data, which are commonly shared and contributes to customer information.
From page 55...
... Transit Agencies May Be Able to Increase the Value of Data Sharing in the Future with the Development of New Data Standards, Moving Toward Open Data and Tools, and Leveraging the Interests of the Private Sector • Data standards have the potential to increase the value of public transit data sharing and make transit agency use of external data sets more efficient. The majority of transit agency interviewees were supportive of the idea of standards for public transit data types, noting that standards could promote the development of shared tools and other resources.
From page 56...
... Transit Agencies are Beginning to Harness the Value of External Data, but Challenges Remain • There is potential value in linking transit agency data sets to external data sets. External data sets can help transit agencies understand first- and last-mile trips and modal alternatives to transit.
From page 57...
... • Collaborative standards-making activities to enable more effective sharing of both transit agency and external data sets and to promote open data and open data tools. • A cross-agency study of the level of effort required for different data management tasks to help transit agencies better evaluate costs of data sharing and internal data analysis.


This material may be derived from roughly machine-read images, and so is provided only to facilitate research.
More information on Chapter Skim is available.