This presentation will showcase a significant FME project undertaken by ProRail, one of the largest FME users in the Netherlands. The GaaS project, also known as Geoprocessing as a Service, has completely overhauled the outdated GeoPoort process, which is responsible for managing and maintaining data related to the Dutch tracks (e.g. track assets), and making it accessible to the ProRail organization and other stakeholders. Using FME as the backbone of the project, the new solution resulted in a more generic and modular process, resulting in a more robust and faster system through the use of dynamic workspaces, custom transformers, and automations. Therefore, leveraging the unique capabilities of the FME Platform.The project also includes the use of Azure DevOps for automatic deployment and OTAP for testing, ensuring a streamlined and efficient process. One of the major advantages of the project outcome is the value it holds for efficient life cycle management, by reducing the amount of time and risk involved in upgrading to newer software. The new solution consists of a significantly reduced number of workspaces and the use of custom transformers, leading to improved efficiency and manageability. The presentation aims to provide valuable insights into ProRail's use of FME to revolutionize their data processing needs and the impact of the project on their operations. Attendees will learn about the dynamic capabilities of the FME platform and the use of job orchestration to manage complex dependencies in data processing through automations on FME Server. Additionally, the presentation will identify and discuss several key strategies and tools used by ProRail to ensure the success of the project.

1. Embracing the Dynamic Mindset:
Reinventing ProRail’s Data Processing using FME

2. Presenter
The
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Cynthia
de Vos
Technical Lead

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Agenda
1. Introduction Case Study
2. XX
3. XX

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Introduction

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Customer success story:
ProRail

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What ProRail does

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Infrastructure

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Challenge: Maintaining and further development
of 700+ workspaces
● High impact on life-cycle management
● Risk of bugs/errors
● Dependency on external schedulingtool
● Dependency on large team of Dev/Ops
● Manual tasks

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Introducing project GAAS

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Improving it: GAAS
Automated Testing
OTAP
Deployment Azure Devops
FME Flow Automations
Dynamic

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Improving it: GAAS
Automated Testing
OTAP
Deployment Azure Devops
FME Flow Automations
Dynamic

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Authentic Sources Geoprocessing Mapservices
ArcGIS Platform
Other applications

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FME Flow Automations
Automation B
FME Flow
Topic
Automation A
Triggers. A Trigger listens for and receives messages from an external client or from within FME Server.
Every automation begins with a Trigger.
External Actions. Sends a message to an external client or another process in FME Server.
What happens afterward is no longer part of this Automation.

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Types of workspaces
Configuration
ReadTableNames
ConfigDependencies
EndOfAutomation

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Types of workspaces
Configuration
ReadTableNames
ConfigDependencies
EndOfAutomation
Dynamic
ReadAuthenticSources
Geoprocessing
WritetoPresentation

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Types of workspaces
Configuration
ReadTableNames
ConfigDependencies
EndOfAutomation
Dynamic
ReadAuthenticSources
Geoprocessing
WritetoPresentation
Specific
TrackEnrichment
LevelCrossing
TrackSpeedLimits

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FME Flow Automations
Geoprocessing
StartKetenB WriteToPresentation
StartKetenA
StartKetenC
ReadAuthentic
DataSources

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Configuration Tables
TABEL
NAAM
LAT
LON
SPOORTAK
REL
SPOORTAK
KM
GEOKM OVER
ERVING
RELATIE REL
METHODE
PRESEN
TATIE
WORKSPACE
Crossbuck 1 0 0 1 1 0 1
PhysicalTrack 1 0 0 1 1 0 1 PhysicalTrack
Enrichment.fmw
LevelCrossing 1 0 0 1 0 1 Geometrie 1 LevelCrossing.fmw
ContractArea 0 0 0 0 0 1 VlakPunt 1
Contains information about:
•What processing is required per objecttype
•Data dependencies
•Schema mapping (datamodel authentic datasource <> datamodel GAAS)
•Data filterering (only limited features required for publication)

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Configuration Tables
TABEL
NAAM
LAT
LON
SPOORTAK
REL
SPOORTAK
KM
GEOKM OVER
ERVING
RELATIE REL
METHODE
PRESEN
TATIE
WORKSPACE
Crossbuck 1 0 0 1 1 0 1
PhysicalTrack 1 0 0 1 1 0 1 PhysicalTrack
Enrichment.fmw
LevelCrossing 1 0 0 1 0 1 Geometrie 1 LevelCrossing.fmw
ContractArea 0 0 0 0 0 1 VlakPunt 1
Contains information about:
•What processing is required per objecttype
•Data dependencies
•Schema mapping (datamodel authentic datasource <> datamodel GAAS)
•Location of authentic source data
•Data filterering (only limited features required for publication)

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Data dependencies
Automation B
FME Flow
Topic
Automation A

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Data dependencies
Automation B
FME Flow
Topic
Automation A
Sorting relative groups based on
Dependencies
Automated process that recalculates
order every run

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Sorting mechanism
No dependencies
(group 0)
Dependent on previous groups
(group 2)
Dependent on previous groups
(group 3)
etc.

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DEMO

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Unit testing Custom Transformers

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Unit testing Custom Transformers (2)

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Overview by Mermaid

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Conclusion

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Generic and modular process, dynamic workspaces, custom transformers,
and automations.
Conclusion
Benefits Challenges
Efficient life cycle management High investment short-term
Reduced upgrade time and risk Currently the old system 700+ workspaces are still
operational
Reduced risk when adding new features
Improved data quality
Enhanced collaboration
Streamlined Process: Leveraging Azure DevOps
and OTAP.

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Embrace the Dynamic Mindset:
Draw Inspiration from ProRail’s
Success and Drive
Transformation

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Embrace the Dynamic Mindset
Top Tips
1. Identify Opportunities for Streamlining
2. Explore the Dynamic Capabilities of FME Platform
3. Strengthen Robustness Through Testing
4. Invest in Continuous Learning and Innovate.
5. Collaborate with the FME Community

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Resources
● Include resources for attendees to get started with
● In bullet points
● Here

33. ThankYou!
cdevos@tensing.com