Hypermedia as the engine for route planning

Transcript

1. Hypermedia as the engine for route planning @PieterColpaert
2. How far do you live from work?
3. Open Trip Planner with data by @openov
4. Or did you route for happiness? by @danielequercia
5. User agents need timely access to a mind- blowing amount of constantly changing datasets
6. Trade-off: load on server or agents? Data dumps Smart servers full query language of HTTP Dataset split in fragments Smart agents + server functionality helping certain use cases Read more at http://linkeddatafragments.org
7. A web-service for your app http://api.{myapp}/?from={A}&to={B}
8. You choose the functionalities http://api.{myapp}/?from={A}&to={B} &departuretime=2015-04-25T10:45Z &wheelchairaccessible=true &modes=plane,railway,bus,car ...
9. Data, services and apps Servers publishing Open Data web-services e.g., • a SaaS route planner: from → to • the closest station to your current location? • other micro-services end-user apps e.g., profile based routing + ticketing + ... $$$ $$$
10. Data, services and apps Servers publishing Open Data web-services e.g., • a SaaS route planner: from → to • the closest station to your current location? • other micro-services end-user apps $$$ $$$ If we enable this, adding something in between will be possible as well
11. User agents and servers Servers publishing Open Data Route planning agents $$$ Let’s talk about this
12. Publishing data vs. data services Data dumps Smart servers Data publishing (cheap) Data services (rather expensive) Algorithms as a service Dataset split in fragments Smart agents + server functionality helping certain use cases
13. What does road data look like? a path point 1 point 2 another path point 2 point 3 yet another path point X point Y
14. a connection What does transit data look like? departureTime + location arrivalTime + location a connection departureTime + location arrivalTime + location a connection departureTime + location arrivalTime + location a connection departureTime + location arrivalTime + location time
15. How does route planning work? time The Connection Scan Algorithm (CSA)
16. Resource ... Resource 3 Resource 2 Resource 1 Let’s fragment our dataset time nextPage nextPage
17. Resource ... Resource 3 Resource 2 Resource 1 Route planning agent needs X requests time nextPage nextPage
18. • Cacheable resources → Less server load → Higher availability • The agent performs the algorithm • Resources from different locations at once Advantages
19. Current state JSON-LD vocabulary at: github.com/opentransport
20. github.com/opentransport 1. Transform any GTFS dataset to connections 2. A server implementation creating and linking resources 3. A javascript library for route planning using connections To be launched by ~July
21. Any questions? @PieterColpaert