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RPI 28/07/2011 1
With the help of the Datalift teamAnd the support of the French National Research Agency
The Datalift Project Ontologies, Datasets, Tools and Methodologies to Publish and Interlink ★★★★★ Datasets
François ScharffeUniversity of Montpellier, LIRMM, [email protected]@lechatpito
State of government open data
(September 2010…)
You’re here
(June 2011)
State of government open data
May 2007
April 2008 September 2008
March 2009
September 2010
Linking Open Data
Linking Open Data cloud diagram, by Richard Cyganiak and Anja Jentzsch. http://lod-cloud.net/
Link the world
Linked data
W3C
W3C
Tim Berners Lee, http://www.w3.org/DesignIssues/LinkedData.html
principles§ Use the RDF format
§ Use URI to name things
§ Use HTTP URI HTTP (URL) so that one can look up those names
§ Give information (HTML, RDF) when dereference those links
§ Include in this information other URIs pointing to other data to enable discovery
goal of datalift
from raw published datato interconnected semantic data
phase 1: opening the data
develop a plateform easing the publication
Published and interlinked data on the Web
Applications
Interconnexion
Publication infrastructure
Data convertion
Vocabulary selection
Raw data
Welcome aboard the data lift
Example publication process
GeographyOil industryequipment
SPARQL
Content Negociation
URI de-referencing
Environmental, weather, geological datasets
SemWebPro 18/01/2011 13
1st floor - Selection
Vocabularies of my friends...
Ø What is a (good) vocabulary for linked data ?
§ Usability criterias
Simplicity, visibility, sustainability, integration, coherence …
Ø Differents types of vocabularies
§ metadata, reference, domain, generalist …
§ The pillars of Linked Data : Dublin Core, FOAF, SKOS
Ø Good and less good practices
§ Ex : Programmes BBC vs legislation.gov.uk
§ Vocabulary of a Friend : networked vocabularies
Ø Linguistic problems
§ Existing vocabularies are in English at 99%
§ Terminological approach :which vocabularies for « Event » « Organization »
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Did you say « vocabulary »
… And why not « ontology »?
§ « schema » or « metadata schema »?
§ Or « model » (data ? World ?)
Ø All these terms are used and justifiable
They are all « vocabularies »
§ They define types of objects (or classes)and the properties (or attributes) atttached to these objects.
§ Types and attributes are logically definedand named using natural language
§ A (semantic) vocabularyis an explicit formalizationof concepts existing in natural language
Vocabularies for linked data
ØAre meant to describe resources in RDF
ØAre based on one of the standard W3C language§ RDF Schema (RDFS)
• For vocabulaires without too much logical complexity
§ OWL • For more complex ontological constructs
§ These two languages are compatible (almost)
ØThe can be composed « ad libitum »§ One can reuse a few elements of a vocabulary
§ The original semantics have to be followed
What makes a good vocabulary ?
Ø A good vocabulary is a used vocabulary
§ Data published on CKAN give an idea of vocabulary usage
§ Exemple : list of datasets using FOAF http://xmlns.com/foaf/0.1/
Ø Other usability criterias
§ Simplicity and readability in natural language
§ Elements documentation (definition in natural language)
§ Visibility and sustainability of the publication
§ Flexibility and extensibility
§ Sémantic integration (with other vocabularies)
§ Social integration (with the user community)
A vocabulary is also a community
ØBad (but common) practice● Build a lonely vocabulary
– For example as a research project– Without basing it on any existing vocabulary
§ To publish it (or not) and then to forget about it
§ Not to care about its users
ØA good vocabulary has an organic life
§ Users and use cases
§ Revisions and extensions
§ Like a « natural » vocabulary
Types of vocabularies
Ø Metadata vocabularies
§ Allowing to annotate other vocabularies
• Dublin Core, Vann, cc REL, Status, Void
Ø Reference vocabularies
§ Provide « common » classes and properties
• FOAF, Event, Time, Org Ontology
Ø Domain vocabularies
§ Specific to a domain of knowledge
• Geonames, Music Ontology, WildLife Ontology
Ø « general » vocabularies
§ Describe « everything » at an arbitrary detail level
• DBpedia Ontology, Cyc Ontology, SUMO
Vocabulary of a Friend
Øhttp://www.mondeca.com/foaf/voaf
ØA simple vocabulary...
ØTo represent interconnexions between vocabularies
ØA unique entry point to vocabularies and Datasets of the linked-data cloud Linked Data Cloud
ØOngoing work in Datalift
SemWebPro 18/01/2011 21
2nd floor - Conversion
Reference datasets, URI design
● Providing reference datasets for the French ecosystem: geographical, topological, statistical, political
● Providing URI design guidelines● Opaque or transparent URIs ?● Usage of accents in URIs● Distinction between
Resources: http://dbpedia.org/resource/Paris
Documents: http://dbpedia.org/page/Paris
Data: http://dbpedia.org/data/Paris
… All served with content negociation
Many tools exist !
csv2rdf4lod
Define a standard transformation from a relational database to RDF
The relational schema is used :• Cells of a tuple produce triples with a common subject
• Each cell produces an object
• Different tables of a same database are thus linked together
Standard automatic translation of any relational schema to RDF, based on the database Dump
Then we can SPARQL CONSTRUCT to adapt vocabularies and URIs.
Direct Mapping from relational database to RDF
Exemple
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Credits Ivan Herman: http://ivan-herman.name/2010/11/19/my-first-mapping-from-direct-mapping/
Exemple
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Credits Ivan Herman: http://ivan-herman.name/2010/11/19/my-first-mapping-from-direct-mapping/
@base <http://book.example/> .<Book/ID=0006511409X#_> a <Book> ; <Book#ISBN> "0006511409X" ; <Book#Title> "The Glass Palace" ; <Book#Year> "2000" ; <Book#Author> <Author/ID=id_xyz#_> .
<Author/ID=id_xyz#_> a <Author> ; <Author#ID> "id_xyz" ; <Author#Name> "Ghosh, Amitav" ; <Author#Homepage> "http://www.amitavghosh.com" .
Simple result but not satisfaying:● we want to use different vocabulary terms (like a:name)● the direct mapping produces literal objects most of the time, except when there is
a “jump” from one table to another● the resulting graph should use a blank node for the author, which is not the case
in the generated graph
Exemple
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CONSTRUCT { ?id a:title ?title ; a:year ?year ; a:author _:x . _:x a:name ?name ; a:homepage ?hp .}WHERE { SELECT (IRI(fn:concat("http://...",?isbn)) AS ?id) ?title ?year ?name (IRI(?homepage) AS ?hp){ ?book a <Book> ; <Book#ISBN> ?isbn ; <Book#Title> ?title ; <Book#Year> ?year ; <Book#Author> ?author . ?author a <Author> ; <Author#Name> ?name ; <Author#Homepage ?homepage . }}
Solution : use SPARQL 1.1 Construct queries
SemWebPro 18/01/2011 28
3rd floor - Publication
Datalift Platform
V1 to be released in September with expected features :
- Modular architecture
- Raw convertion module: Relational DB (DirectMapping approach, CSV, XML (based on a user specified XSLT transformation)
- Selection module : LOV repository, automatic candidate vocabulary proposal using ontology matching from the raw data schema, vocabulary navigation tool, vocabulary usage metrics, sample data for each vocab
- Convertion (according to the schema) : RDF2RDF Convertion module based on SPARQL construct (manual editing), Vocabulary mapping facility (textual)
- Interlinking and Alignment : A Silk interface -- Integration of the alignment API
- Publication Sesame API, informational vs non-informational resource management.
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Datalift Platform
SemWebPro 18/01/2011 31
4th floor - Interconnexion
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Web of data and links
- Without links no web but data silos
- Many types of links : the edges of the Web of data graph are labeled
- Some links are built during the selection phase : reference datasets
- We study here a particular type of links : equivalence links.
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owl:sameAs
- points to a logical identity between two resource
- The quality of the available links is not always optimal
Other types of links : owl:differentFrom, rdfs:seeAlso
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How to link data ?
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How to link data ?
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How to link data ?
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How to link data ?
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How to link data ?
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Example Silk link specification<Silk> <Prefix id="rdfs" namespace= "http://www.w3.org/2000/01/rdf-schema#" /> <Prefix id="dbpedia" namespace= "http://dbpedia.org/ontology/" /> <Prefix id="gn" namespace= "http://www.geonames.org/ontology#" />
<DataSource id="dbpedia"> <EndpointURI>http://demo_sparql_server1/sparql </EndpointURI> <Graph>http://dbpedia.org</Graph> </DataSource>
<DataSource id="geonames"> <EndpointURI>http://demo_sparql_server2/sparql </EndpointURI> <Graph>http://sws.geonames.org/</Graph> </DataSource> <Thresholds accept="0.9" verify="0.7" /> <Output acceptedLinks="accepted_links.n3" verifyLinks="verify_links.n3" mode="truncate" />
<Interlink id="cities"> <LinkType>owl:sameAs</LinkType> <SourceDataset dataSource="dbpedia" var="a"> <RestrictTo> ?a rdf:type dbpedia:City </RestrictTo> </SourceDataset> <TargetDataset dataSource="geonames" var="b"> <RestrictTo> ?b rdf:type gn:P </RestrictTo> </TargetDataset> <LinkCondition> <AVG> <Compare metric="jaroSimilarity"> <Param name="str1" path="?a/rdfs:label" /> <Param name="str2" path="?b/gn:name" /> </Compare> <Compare metric="numSimilarity"> <Param name="num1" path="?a/dbpedia:populationTotal" /> <Param name="num2" path="?b/gn:population" /> </Compare> </AVG> </LinkCondition> </Interlink></Silk>
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Where to find links ?
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Towards automatic interlinking
We have seen some of the Silk spec fields could be avoided
- Using alignments between ontologies
- Detecting discriminating properties
- Indicating comparison methods by attaching metadata to ontologies
-> … ongoing work in Datalift
SemWebPro 18/01/2011 42
5th floor - Applications
phase 2: publishing datasets
validate the plateform with real data
Research objectives§ Methods and metrics for selecting schemas§ Tradeoff between specific and generic vocabularies§ Data conversion and URI design patterns§ Automatic data interlinking§ Provenance and rights management§ Integration, architecture and scalability
W3C ©
Who ?
2010-2013
The french wider landscape
● Regards Citoyens
● Direction de l’information légale et administrative
● Fédération des parcs naturels régionaux de France
● Eurostat
● Cities of Montpellier, Bordeaux, Rennes, …
● Data Publica
● EtatLab
DA
TALI
FT
next floor: « the web of data »
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Credits
This presentation was realized thanks to the work of the Datalift team.It can be freely distributed under Creative Commons licence BY-NC-SA 3.0
