accelerate the lifting from raw datato linked public data http://datalift.org

1. DATALIFT
free! your data! link! your data! free! your data! link! your data! free!
your data! link! your data! free! your data! link! your data! free! your
data! link! your data! free! your data! link! your data! free! your data!
link! your data!

2. in september 2010…
you are here

3. goal of datalift
accelerate the lifting from raw data
to linked public data

4. Who ?

5. phase 1: an easy open
end for data
provide an open source
platform assisting publication

6. assist the selection of data
Selection of data to publish
- Usage studies
- Business models questions
- Selection tools
- Apply to real data from users in the project

7. assist the selection of data
identify appropriate schemas
Schema catalog
- Methods and metrics to select schemas
- Build and publish a catalog
- Model specifics needs and extensions
- Apply to real data from users in the project

8. identify appropriate schemas
assist the selection of data
format conversion & connectors
Converting data
- Principles for identifiers
- Tools to convert to RDF (CSV, etc.)
- Application to data of the users of the project
- Attach provenance, licenses, rights, etc.

9. format conversion & connectors
identify appropriate schemas
assist the selection of data
data publication
Architecture and infrastructure to publish data
- Benchmarks and integration
- Architecture and component for publication
- Real scale experiment with users of the project

10. data publication
interconnecting data
Data interconnection
- Statistical methods to calculate keys in a dataset
- Tools to interconnect datasets
- Interconnect datasets of the users of the project
format conversion & connectors
identify appropriate schemas
assist the selection of data

11. phase 2: publish real datasets
validate, apply and test the
platform on real datasets.

12. other topics identified
● toolbox to visualize, browse and query data
● API for mobile applications
● clouds &distribution
● legal advice and granularity
● cookbook & best practices

13. R&D challenges
 methods & metrics for schema selection
 balance specific needs & reusability
 data conversion & identifiers generation
 automation of dataset interconnection
 named graphs, provenance, licenses and rights
 integration and scalability

14. milestones
M1
October 2010
M6
April 2011
M12
Sept. 2011
M24
Sept. 2012
M18
April 2012
M30
April 2013
M36
Sept. 2013
WWW 2012
architecture
specification
forge for the
open-source
state of the art
& benchmarks
datasets from
IGN & INSEE
first integrated
prototype
data publication tools
& experimentation
schema
catalog
conversion tools
interconnection
prototype
usages and
business models
2nd version
(cloud)
more and more
datasets
encourage external adoption
and application development
functional platform…

15. other identified data providers
and users’ club
• Regards Citoyens
• Direction de l’information légale et administrative
• Fédération des parcs naturels régionaux de France
• Eurostat
• Communauté Urbaine de Bordeaux
• Data Publica
…

16. other projects
● Data Publica
● LATC
● LOD2
● Planet Data
● Publink (LOD2 + LATC)
● RPI Data-gov wiki
● Data incubator

17. DATALIFT