Linked Open Transport Data

Presented at the Big Data Europe workshop in Brussels

Transcript

1. Maximizing the reuse of Open Transport Data Pieter Colpaert Ghent University - iMinds/imec
2. How far do you live from work?
3. km or min?
4. Imagine a program calculating distance in minutes What data would you need?
5. Transport has become a data sharing problem How can we fix it?
6. 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
7. Sharing data on the Web Your system ? ? ? ? ? ? Maximizing reuse → need to raise the interoperability
8. ↓ Querying syntactic semantic technical legal When I have got 2 datasets, how easy is it to use them as if they were 1?
9. OpenDefinition.org ↓ Querying syntactic semantic technical legal
10. reuse is allowed Documents on the web reuse in a gray zone unauthorised reuse
11. 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
12. 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
13. 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, … Open Standards
14. name type same as location iMinds company IBBT Gaston Crommenlaan 8 { “iMinds” : { “type” : “company”, “same as” : “IBBT, “location” : “Gaston Crommenlaan 8” } } <iMinds> <type>company</type> <sameas>IBBT</sameas> <location> Gaston Crommenlaan 8 </location> </iMinds> Table / CSV / Spreadsheet JSON XML Serialisations
15. name type same as location iMinds company IBBT Gaston Crommenlaan 8 <iMinds> <type> <company> . <iMinds> <sameas> <IBBT> . <iMinds> <vestiging> “Gaston Crommenlaan 8” . Table / CSV / Spreadsheet triples Triple structure { “iMinds” : { “type” : “company”, “same as” : “IBBT, “location” : “Gaston Crommenlaan 8” } } <iMinds> <type>company</type> <sameas>IBBT</sameas> <location> Gaston Crommenlaan 8 </location> </iMinds> JSON XML
16. World Wide Web iMinds same as IBBT iMinds is a company IBBT located at Gaston Crommenlaan 8 Machine 1 Machine 2 Machine 3 Linked data
17. 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”?
18. 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)
19. E.g., Linked Datex and Linked GTFS Vocabularies at http://vocab.datex.org/terms http://vocab.gtfs.org/terms E.g., Searching for Parking Facilities with Linked Data thanks to “rich snippets” But is that it?
20. 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, … Open Standards → using URIs instead of local identifiers
21. 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
22. data dump Route planning algorithms as a service
23. A long tail for transport data services ... Hard to guess which kind of queries will be needed
24. Can we find a way to publish for example public transport data while minimizing federated reuse cost?
25. Data needed for algorithm a connection departureTime + departureStop arrivalTime + arrivalStop another connection departureTime + departureStop arrivalTime + arrivalStop
26. time * The Connection Scan Algorithm (CSA) And this is the algorithm* ~ creating a minimum spanning tree through a sorted directed acyclic graph Squares are connections
27. Resource X Resource ... Resource 2 Resource 1 time nextPage nextPage When published in pages on the Web, route planning will need X requests instead of 1
28. Try it yourself at http://LinkedConnections.org
29. 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
30. Global interoperability for Route Planners? ↓ Querying syntactic semantic technical legal → Open Definition & open licenses → The Internet: exchanging data world-wide → JSON, XML, CSV, … Open Standards → Work in progress linkedconnections.org → using URIs instead of local identifiers
31. Checklist Open (Transport) Data Do you have an open license on your data? Is it shared publicly on the Web in an open format (html/css/xml/json…)? Do you identify things in a globally interoperable way? How easy is it to include your dataset in a federated query? Are you exposing basic reusable building blocks for your dataset?
32. A world where knowledge creates power for the many, not the few Questions? @pietercolpaert http://pieter.pm