The Transit Analyst Toolbox: Analysis and Approaches for Reporting, Communicating, and Examining Transit Data (2021) / Chapter Skim
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50 Several of the transit agencies responding to the survey were interviewed to obtain detailed information about their approach to building their data management system or their data governance process. The interviews are divided into three categories: • Building Blocks to Create a Data Management Ecosystem (Enterprise Approach)
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Case Examples 51 Kitsap Transit (Bremerton, WA) Agency Characteristics Small Agency Institutional structure: Independent or special district Modes: Fixed route bus, flex route, or microtransit bus, PSNS worker/driver program, ferry and paratransit (Source: NTD 2018)
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52 The Transit Analyst Toolbox: Analysis and Approaches for Reporting, Communicating, and Examining Transit Data Data Quality Processes Within each application, the service data and archived operational data are stored, consistent, and accurate. Quality is better than generating and managing the data on paper.
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Case Examples 53 – Using a service-hosted tool may encounter internal resistance from staff who do not want to use a web-based tool. • Think about back-up and data preservation.
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54 The Transit Analyst Toolbox: Analysis and Approaches for Reporting, Communicating, and Examining Transit Data Figure 25. AC Transit enterprise database (Source: AC Transit)
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Figure 26. Existing relationship among applications and enterprise database platform (Source: AC Transit)
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56 The Transit Analyst Toolbox: Analysis and Approaches for Reporting, Communicating, and Examining Transit Data views will be built into the enterprise database to provide easier access of data to users. These views, also called data marts (see definition in sidebar)
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Figure 27. AC Transit ZEB DIMA case study.
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Figure 28. AC Transit Service Operations Costing module.
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Case Examples 59 Data Management Overview Metro Transit's data management environment grew organically from multiple projects.15 Over time the Metro Transit started developing their own interfaces, operational databases, and then most recently data marts that integrate data into business views for bus and LRT operations. In addition, open data stores through the MN Geospatial Commons (a consortium of 38 resources from the Metropolitan Council)
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Figure 29. Metro Transit data flow ecosystem.
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Case Examples 61 Data Quality and Integration Processes Data quality processes are embedded with interface and database processing procedures. Metro Transit staff spent three years understanding and cleaning APC data.
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62 The Transit Analyst Toolbox: Analysis and Approaches for Reporting, Communicating, and Examining Transit Data by the data scientists. It has been more difficult to fill these roles, so Metro Transit has used consultants to augment their staff with data architects and developer roles on core projects.
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Case Examples 63 they take to get started? The three case examples highlight the challenges to adopt data governance in each organization.
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64 The Transit Analyst Toolbox: Analysis and Approaches for Reporting, Communicating, and Examining Transit Data Initial Data Focus T-BIRD started with five main system data sets (of 150 different data systems in Metro)
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Figure 30. King County Metro T-BIRD data curation, management, and business intelligence framework.
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Figure 31. King County Metro data warehouse (T-Bird)
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Case Examples 67 their analytic and MGM tools to trace a piece of data from its inclusion in a dashboard back to a report, then the data set from which it was extracted, through the fully documented ETL process, and finally, to the source of the data. Challenges and Lessons Learned King County staff identified challenges and lessons learned from their experience.
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Figure 32. AC Transit conceptual data architecture for EDW.
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Case Examples 69 the critical data sources that will be ingested, cleaned, stored, and accessed. The data marts in this depiction are similar to the data products identified in the KCM EDW.
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70 The Transit Analyst Toolbox: Analysis and Approaches for Reporting, Communicating, and Examining Transit Data source of truth for the agency. Though it is far from resolving, many of the data quality challenges and UTA is looking for a data governance approach.
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Case Examples 71 1. Where/how do you get Trapeze data?
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72 The Transit Analyst Toolbox: Analysis and Approaches for Reporting, Communicating, and Examining Transit Data Stop Name Use upper and lowercase letters. Bus Stops: Consistency is important.
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Case Examples 73 Communications Plan. The purpose of the Communications Plan identified the roles and responsibilities of the Data Governance Council and its members.
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74 The Transit Analyst Toolbox: Analysis and Approaches for Reporting, Communicating, and Examining Transit Data Figure 33. Agenda for first data governance council meeting.
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Case Examples 75 planning tools: open data formats for Census and Transit (GTFS) data; OSS such as R, Python, and Open Trip Planner; and crowd-sourced road network data and tools included with Open Street Map (OSM)
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76 The Transit Analyst Toolbox: Analysis and Approaches for Reporting, Communicating, and Examining Transit Data spatial features (polygons, lines, or points) , including those derived from LBS data, can be imported and used to analyze transit service.23 • Using OSM, Analysis enables use of the varied mode network data that is supported by OSM, including bike lanes and paths, pedestrian walkways, and highways.
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Figure 35. Example: LA Metro analysis showing demand from LAX to destinations and the impact of the new LRT line to reduce travel times.
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Figure 36. Example: View impact of access to transit based on transit route modifications.
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