Standardizing Data for Mobility Management (2013) / Chapter Skim
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Pages 43-52
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V. ADVANCING DATA STANDARDS Existing Foundation Important foundational pieces are in place for advancing data standards, including policies, processes, and specifications.
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• An understanding that this is a heterogeneous industry with many actors who do not routinely communicate with one another. • An industry group will need to organize the process, as no software vendor has sufficiently dominant market presence to set standards.
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As one result of this study, a core group of individuals in the transit industry and among vendors has indicated a willingness to participate in a leadership role to develop specifications. It is recommended that such a group be convened approximately twice a year at transit industry conferences with intermediate meetings via web and video conferencing.
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and data exchange protocols as the initial objective. Accordingly, the research team's assessment of the core data elements that need to be included in the initial data standards follow.
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Category and Data Item Required Input? Required Output?
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Category and Data Item Required Input? Required Output?
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Table 3: Proposed Data Elements for an Initial Standard for Discovery Data Data Element Required? Comment Service name Y Service sponsor Y Service phone number Y For trip reservations Service Web URL Only relevant if Web booking possible Service area boundaries Y GIS shape file Service operating hours Y By day of week Ridership restrictions Y General public, ADA restricted, agency affiliation, etc.
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The process should include software vendors and purchasers of scheduling and dispatch systems. It would be useful to broaden the process so that connections and opportunities with related data can be identified.
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Task 3. Review current efforts at Federal and state levels to provide for technology systems for DRT that provide the maximum interoperability, access to data, and building the capacity of staff to understand technology that impacts their jobs.
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to the process. Further, it is recommended that the effort start small with a minimal set of data items, growing over time.
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