Transport data for maximum reuse for the Social Car project

A rework of a previous talk on maximizing the reuse of open transport data for the Social Car project

Transcript

1. Maximizing the reuse of Open Transport Data Pieter Colpaert Ghent University - iMinds/imec - Open Knowledge
3. Sharing data between 2 systems Your system Third party system Agree on a protocol Will determine which questions can be answered in a timely fashion Can ask questions to your system as previously agreed
4. An API for your carsharing system http://api.{socialcar}/?from={A}&to={B}
5. A long tail for transport data services ... Hard to guess what to provide: Wheelchair accessible? Quiet car? Maximum transfers?
6. An API for your ridesharing system http://api.{socialcar}/?from={A}&to={B} &departuretime=2016-10-11T12:45 &wheelchairaccessible=true &maxTransfers=3 &algoritm_mode=shortest ...
8. An API for your ridesharing system http://api.{socialcar}/?from={A}&to={B} &departuretime=2016-10-11T12:45 &wheelchairaccessible=true &maxTransfers=3 &algoritm_mode=shortest &mode=train,bus,taxi,ridesharing,carpooling &foldablebike=true...
9. An API for your ridesharing system http://api.{socialcar}/?from={A}&to={B} &departuretime=2016-10-11T12:45 &wheelchairaccessible=true &maxTransfers=3 &algoritm_mode=shortest &mode=train,bus,taxi,ridesharing,carpooling &foldablebike=true... DOESN’T SCALE NOT A GOOD WAY TO PUBLISH OPEN DATA
10. Transport has become a data sharing problem How can we fix it?
11. Sharing data on the Web Your system ? ? ? ? ? ? Maximizing reuse → need to raise the interoperability
12. ↓ Querying syntactic semantic technical legal When I have got 2 datasets, how easy is it to use them as if they were 1?
13. OpenDefinition.org ↓ Querying syntactic semantic technical legal (we’re 1/3d through all slides)
14. reuse is allowed Documents on the web reuse in a gray zone unauthorised reuse
15. A story of raising interoperability ↓ Querying syntactic semantic technical legal When I have 2 datasets, how easy is it to turn them into 1 dataset? → Open Definition & open licenses
16. A story of raising interoperability ↓ Querying syntactic semantic technical legal When I have 2 datasets, how easy is it to turn them into 1 dataset? → Open Definition & open licenses → The Internet: exchanging data world-wide
17. A story of raising interoperability ↓ Querying syntactic semantic technical legal When I have 2 datasets, how easy is it to turn them into 1 dataset? → Open Definition & open licenses → The Internet: exchanging data world-wide → JSON, XML, CSV, HTML… Open Standards
18. A story of raising interoperability ↓ Querying syntactic semantic technical legal When I have 2 datasets, how easy is it to turn them into 1 dataset? → Open Definition & open licenses → The Internet: exchanging data world-wide → JSON, XML, CSV, HTML… Open Standards → Linked Data
19. name type same as location iMinds company IBBT X { “iMinds” : { “type” : “company”, “same as” : “IBBT, “location” : “X” } } <iMinds> <type>company</type> <sameas>IBBT</sameas> <location>X</location> </iMinds> Table / CSV / Spreadsheet JSON XML Serialisations
20. name type same as location iMinds company IBBT X <iMinds> <type> <company> . <iMinds> <sameas> <IBBT> . <iMinds> <vestiging> “X” . Table / CSV / Spreadsheet triples Triple structure <iMinds> <type>company</type> <sameas>IBBT</sameas> <location>X</location> </iMinds> JSON XML { “iMinds” : { “type” : “company”, “same as” : “IBBT, “location” : “X” } }
21. World Wide Web iMinds same as IBBT iMinds is a company IBBT located at X Machine 1 Machine 2 Machine 3 Linked data
22. Problem The word company is ambiguous. How can we make sure that machines understand each other? semantic interoperability What about “is a”? and what about “iMinds”?
23. Solution iMinds → http://data.kbodata.be/organisation/0866_386_380#id is a → http://www.w3.org/1999/02/22-rdf-syntax-ns#type Company → http://www.w3.org/ns/regorg#RegisteredOrganization Uniform Resource Identifiers (URIs)
24. http://vocab.datex.org/
25. Other vocabularies 2 Linked vocabularies for Public Transit http://vocab.gtfs.org/ http://linkedconnections.org/ Look for more URIs at http://lov.okfn.org (we’re 2/3d through all slides, and look, you understand all about Linked Data!)
26. Where can you get in what amount of time? under specific conditions: taking into account: multimodality, criminality, your subscriptions, what you’re carrying, disabilities, etc
27. data dump Route planning algorithms as a service
28. Striking the golden mean? Data dumps Smart servers Data publishing (cheap/reliable) Data services (rather expensive/unreliable) Entire query languages over HTTP Dataset split in fragments Smart agents algorithms as a service
29. Global interoperability for your dataset ↓ Querying syntactic semantic technical legal → Open Definition & open licenses → The Internet: exchanging data world-wide → JSON, XML, CSV, HTML… Open Standards → Does your data interface allow for federated querying? → using URIs instead of local identifiers (Still 3 slides… the next one is a summary slide)
30. Checklist Open (Transport) Data Do you have an open license on your data? Is it shared publicly on the Web? Do you identify things in a globally interoperable way? (URIs) Is it straightforward to include your dataset in a federated query? Is it in an open format (html/csv/xml/json…)?
31. “How to make data available, EU-wide, for intermodal route planners?” Work in progress for maximum interoperability http://LinkedConnections.org
32. A world where knowledge creates power for the many, not the few Questions? @pietercolpaert http://pieter.pm