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Web of data 
Thomas Francart, sparna.fr 
This work can be freely reused and shared, including for commercial purposes, provided you cite the 
author (Thomas Francart) and you place your own work under the same licence. For more 
information, see the licence. 
Crédits : This work remixes elements from Fabien Gandon, Serge Garlatti and Pierre-Yves Vandenbussche
The web for 
a human 
2
3 
The Man Who Mistook His Wife for a Hat : 
And Other Clinical Tales by 
In his most extraordinary book, "one of the great clinical writers of the 20th century" (The New 
York Times) recounts the case histories of patients lost in the bizarre, apparently inescapable world 
of neurological disorders. Oliver Sacks's The Man Who Mistook His Wife for a Hat tells the stories 
of individuals afflicted with fantastic perceptual and intellectual aberrations: patients who have lost 
their memories and with them the greater part of their pasts; who are no longer able to recognize 
people and common objects; who are stricken with violent tics and grimaces or who shout 
involuntary obscenities; whose limbs have become alien; who have been dismissed as retarded yet 
are gifted with uncanny artistic or mathematical talents. 
If inconceivably strange, these brilliant tales remain, in Dr. Sacks's splendid and sympathetic telling, deeply human. They 
are studies of life struggling against incredible adversity, and they enable us to enter the world of the neurologically 
impaired, to imagine with our hearts what it must be to live and feel as they do. A great healer, Sacks never loses sight of 
medicine's ultimate responsibility: "the suffering, afflicted, fighting human subject." 
Our rating : 
Find other books in : Neurology Psychology 
Search books by terms : 
Oliver W. Sacks 
Oliver Sacks
The same web for 
a machine 
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The web of data is an extension of the 
existing web that adds structured data 
for 
machines 
6
Chapter I : web of data to 
Structure 
and 
Identify
Why 
structuring content ?
To have smarter 
information access 
internally and/or
Synonymy 
Yacht ? 
Boat ? 
Ship ? 
… dans une bottle, a vial, a flak ?
Polysemy 
(english and french !)
Multilinguism
Search on the web : 
quick vegan pizza recipe 
relevance and reuse of the results 
can be done only by… you. 
What if I want to sort by cooking time ? By calories ? 
What if I need to create and excel spreadsheet of the recipes ?
Let’s structure descriptions 
with atomic information 
subject verb complement
More formal description 
Tino’s pizza is a pizza recipe 
Tino’s pizza has ingredient tomato 
Tino’s pizza has ingredient mozarella 
Tino’s pizza has ingredient mushrooms 
Tino’s pizza is in category easy 
Tino’s pizza is prepared in 20 min
Yes but… 
how can we be 
non ambiguous 
in these descriptions ? 
« has ingredient », « contains », « a pour ingrédient »… ?
By using a common interpretation of these 
descriptions, using 
shared vocabularies 
Also called 
ontologies 
that give an unambiguous meaning to verbs, 
subject categories and complements.
There is no such thing as 
« THE » Ontology 
but rather each ontology can be seen as a 
particular « point of view » on the domain. 
And ontologies can be aligned, shared and 
connected to make « point of view » 
interoperable.
More formal description 
ex:pizza23 rdf:type pizza recipe 
ex:pizza23 food:hasIngredient tomato 
ex:pizza23 food:hasIngredient mozarella 
ex:pizza23 food:hasIngredient mushroom 
ex:pizza23 dc:subject myData:easy 
ex:pizza23 schema:cookingTime 20 min 
ex:pizza23 rdfs:label « Toni’s pizza »
How are these rich snippets 
generated?
More formal question 
?smthg rdf:type pizza recipe 
? smthg schema:cookingTime < 20 min 
? smthg dc:subject vegan
Additionnal 
facets
Custom search
« Knowledge 
Graph »
• Vocabulary to structure data in HTML pages 
– Made by and for the big search engines 
• Started mid-2011 
• by Yahoo!, Bing and Google. 
• + Yandex (russian) 
• Working group led by Dan Brickley 
• Relies on HTML5 (Microdata and RDFa)
Thing
RDFa syntax 
<div resource="/billets/probleme-platon" prefix="dc: http://purl.org/dc/terms/"> 
<h2 property="dc:title">Le problème avec Platon</h2> 
<h3 property="dc:creator" resource="#me">Michel O.</h3> 
</div> 
<div class="sidebar" vocab="http://xmlns.com/foaf/0.1/" resource="#me" 
typeof="Person"> 
<p> 
<span property="name">Michel O.</span>, 
Email: <a property="mbox" 
href="mailto:michelo@philo.fr">michelo@philo.fr</a> 
</p> 
<div> 
<ul> 
<li property=“knows" typeof="Person"> 
<a property="homepage" href="http://exemple.fr/platon"> 
<span property="name">Platon</span> 
</a> 
</li> 
</ul> 
</div> 
</div>
Microdata syntax 
<div itemscope itemtype="http://schema.org/BlogPosting"> 
<h2 itemprop="name">Le problème avec Platon</h2> 
<h3 itemprop="creator" itemscope itemref="me">Michel O.</h3> 
</div> 
<div class="sidebar" id="me" itemscope itemtype="http://schema.org/Person"> 
<p> 
<span itemprop="name">Michel O.</span>, 
Email: <a itemprop="email" 
href="mailto:michelo@philo.fr">michelo@philo.fr</a> 
</p> 
<div> 
<ul> 
<li itemprop="knows" itemscope itemtype="http://schema.org/Person"> 
<a itemprop="url" href="http://exemple.fr/platon"> 
<span itemprop="name">Platon</span> 
</a> 
</li> 
</ul> 
</div> 
</div>
RDFa Microdata 
vs. 
Which one should I choose? 
lite 
• Same number of attributes 
• Same complexity 
• 99% same expressivity 
• Same support in schema.org
RDFa Microdata 
vs. 
Which one should I choose? 
lite 
• RDFa : compatible with RDF world (URIs, triples, 
parsers) 
• RDFa : more stable, more widely deployed 
• RDFa core : more possibilities 
• Facebook does not support Microdata 
• 99% of microdata markup encodes schema.org
By what means 
Do ontologies identify in an 
unambiguous way subjects, verbs 
and complements ?
Using URIs 
http://mydomain.org/mypath/myresource
URL 
Identifies 
what exists 
on the web 
http://mon.site.fr 
URI 
Identifies, 
on the web, 
what exists 
http://animaux.fr/mon-zebre 
Fabien Gandon : http://fr.slideshare.net/fabien_gandon
URL : phone number 
URI : social security number 
Good practice : on the web of data, 
every URI is also a URL
UNICODE URIs 
IRI : 
Internationalized 
Resource 
Identifier
Chapter II : web of data to 
Publish
Why 
using web of data 
standards to publish 
data ?
To 
share data with partners, 
applications, services…
What is the simplest mode of 
communication ? 
« peer to peer » « hub and spoke »
Publishing data ? Is it Open Data 
then ? 
http://5stardata.info 
Open data 
Louvre Paris 
Data in the web 
Linked data 
Is in 
http://fr.dbpedia.org/resource/Pari 
s 
Paris = 
Paris Paris
Open Data and web of data 
★ Data accessible on the web 
(in any format, even PDF, or JPG) 
★★ Structured data 
(Excel file instead of JPG) 
★★★ Non proprietary format 
(CSV instead of Excel) 
★★★★ Use URI to identify ressources inside 
the data 
★★★★★ Link data to other data sources 
http://5stardata.info/ 
Open Data 
Linked data – 
web of data
Chapter III : web of data to 
Link
Why 
linking information ?
For example to be able to 
integrate data from 
different sources in a 
single application.
Tiré de http://graphityhq.com
Tiré de http://graphityhq.com
A data source can 
speak about the same « subject » 
as another data source 
http://exemple.com/Elvis 
plays guitar 
http://exemple.com/Elvis 
lives in Las Vegas
A data source can 
use as « complement » 
a subject defined in another data source 
http://data.insee.fr/Paris 
is in France 
Elvis is in concert in 
http://data.insee.fr/Paris
A data source can 
use a « verb » 
defined in another data source 
http://exemple.fr/meet 
is a 
property (linking 2 people) 
Thomas 
http://exemple.fr/meet 
Oliver
From a web of 
documents 
identified by URLs and interlinked 
by hypertext links…
… to a web of data 
identified by URIs and interlinked 
using triples 
« subject verb complement »
and
wikipedia 
dbpedia 
Extraction software 
Cultural GPS 
Collections 
access 
teaching 
accessibility 
international 
applications 
Julien Cojan et Fabien Gandon : http://fr.slideshare.net/JulienCojan/dbpedia-cafein
Julien Cojan et Fabien Gandon : http://fr.slideshare.net/JulienCojan/dbpedia-cafein
Find a resource in DBPedia 
1. Look up something in DBPedia 
– « Jack Sparrow » 
1. Note the URL of the Wikipedia page 
– http://en.wikipedia.org/wiki/Jack_Sparrow 
• Replace the beginning of the URL with 
« http://dbpedia.org/resource/ » 
– http://dbpedia.org/resource/Jack_Sparrow
(Re-)use 
Chapter IV
Web of data 
Blablabla, 
blablablabla 
He said all of that was already 
working, right ? 
Arrière plan de l’image issu du blog des bits: http://nurdcartoon.blogspot.com/
Find the common point between 
- Pierre Curie: French phycisist 
- Boutros Boutros Ghali: Egyptian diplomat 
- Jackie Kennedy : JFK’s wife
http://relfinder.dbpedia.org
Allow researchers to 
publish their data 
http://www.nakala.fr
for your data 
1. Persistent Identifiers 
2. Persistent access to data file 
3. Data archival 
4. Metadata publishing 
1. URIs and content negociation 
2. OAI-PMH 
3. SPARQL endpoint 
5. In the future… linking (to DBPedia) ?
1. Uploading / publishing
2. Access 
• Data (embeddable in another website) 
– http://www.nakala.fr/data/11280/1b2c0d4f 
• Metadata 
– Human or machine version 
• http://www.nakala.fr/metadata/11280/1b2c0d4f 
– Human version 
• http://www.nakala.fr/page/data/11280/1b2c0d4f 
– Machine version 
• http://www.nakala.fr/data/data/11280/1b2c0d4f
3. Harvest or query 
• OAI-PMH publishing (your data only) 
– https://www.nakala.fr/oai/11280/93ec8e76? 
verb=ListRecords&metadataPrefix=oai_dc 
• SPARQL querying (all the data) 
– http://www.nakala.fr/sparql
Share data to 
connect scientists & enable 
research discovery 
http://vivoweb.org
What is VIVO ? 
• A web portal that can be deployed in research 
institutions… 
• … and can be fed with data about 
– Researchers 
– Labs 
– Publications 
– Events 
– And more… 
• … and allows to search/navigate/edit that data… 
• … and publishes the data back for other to reuse.
What is VIVO ? 
• Exemple installations 
– Meta-VIVO : 
http://vivo.vivoweb.org 
– U. Florida : 
https://vivo.ufl.edu/ 
– Bournemouth : 
http://staffprofiles.bourn 
emouth.ac.uk/ 
• (find others at vivoweb.org)
Visualizations 
• http://vivo.cns.iu.edu/gallery.html
vivosearch.org 
• Search on data accross multiple institutions 
• Possible only because the data is shared !
Interinstitutional collaboration 
dataviz 
• http://xcite.hackerceo 
.org/VIVOviz/visualizat 
ion.html 
• Possible only because 
the data is shared… 
• … and the data is 
talking about the 
same “thing” (here, 
the same publication)
Using data from the web to 
enrich content reading 
http://labs.sparna.fr 
http://dev.presek-i.com/onmt_demo/
Create mashups 
With data from the web 
http://labs.antidot.net/museesdefrance
Use data from the web to 
power an API 
http://seevl.net
“The data seevl utilizes come from YouTube, Musicbrainz, Freebase, DBPedia, Google Plus, 
and Facebook, and other sources”.
Publish 
a library catalogue 
http://data.bnf.fr
Collections numérisées (2,5M) Web pages 
BnF Archives & Manuscrits 
Catalogue général (12 M) 
for humans 
Structured data 
For machines 
http://www.rencontres-numeriques.org/2013/mediation/docs/rn2013-BNF-opendata.pptm
data.bnf.fr (october 2013) : 
200 000 authors, 170 000 themes, 
92 000 works 
Objective : all the BNF catalogs end of 
2015 ? 
data.bnf.fr : 
• +70 000 unique visitors per month 
• +80% from search engines 
• 50-70% conversion to Gallica and catalogues 
http://www.rencontres-numeriques.org/2013/mediation/docs/rn2013-BNF-opendata.pptm
Conclusion 
Structuring 
Identifying 
Publishing 
Linking 
(Re-)using
http://everywhereishere2009.blogspot.fr/2009/08/first-thoughts-designing-new-knowledge.html 
(en attente de la permission de l’auteur)
http://everywhereishere2009.blogspot.fr/2009/08/first-thoughts-designing-new-knowledge.html 
(en attente de la permission de l’auteur)
Thomas FRANCART 
sparna.fr 
Crédits : Fabien Gandon, Serge Garlatti, 
Pierre-Yves Vandenbussche

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Web of Data - Introduction (english)

  • 1. Web of data Thomas Francart, sparna.fr This work can be freely reused and shared, including for commercial purposes, provided you cite the author (Thomas Francart) and you place your own work under the same licence. For more information, see the licence. Crédits : This work remixes elements from Fabien Gandon, Serge Garlatti and Pierre-Yves Vandenbussche
  • 2. The web for a human 2
  • 3. 3 The Man Who Mistook His Wife for a Hat : And Other Clinical Tales by In his most extraordinary book, "one of the great clinical writers of the 20th century" (The New York Times) recounts the case histories of patients lost in the bizarre, apparently inescapable world of neurological disorders. Oliver Sacks's The Man Who Mistook His Wife for a Hat tells the stories of individuals afflicted with fantastic perceptual and intellectual aberrations: patients who have lost their memories and with them the greater part of their pasts; who are no longer able to recognize people and common objects; who are stricken with violent tics and grimaces or who shout involuntary obscenities; whose limbs have become alien; who have been dismissed as retarded yet are gifted with uncanny artistic or mathematical talents. If inconceivably strange, these brilliant tales remain, in Dr. Sacks's splendid and sympathetic telling, deeply human. They are studies of life struggling against incredible adversity, and they enable us to enter the world of the neurologically impaired, to imagine with our hearts what it must be to live and feel as they do. A great healer, Sacks never loses sight of medicine's ultimate responsibility: "the suffering, afflicted, fighting human subject." Our rating : Find other books in : Neurology Psychology Search books by terms : Oliver W. Sacks Oliver Sacks
  • 4. The same web for a machine 4
  • 5. 5 jT6( 9PlqkrB Yuawxnbtezls +μ:/iU zauBH 1&_à-6 _7IL:/alMoP, J²* sW dH bnzioI djazuUAb aezuoiAIUB zsjqkUA 2H =9 dUI dJA.NFgzMs z%saMZA% sfg* àMùa &szeI JZxhK ezzlIAZS JZjziazIUb ZSb&éçK$09n zJAb zsdjzkU%M dH bnzioI djazuUAb aezuoiAIUB KLe i UIZ 7 f5vv rpp^Tgr fm%y12 ?ue >HJDYKZ ergopc eruçé"ré'"çoifnb nsè8b"7I '_qfbdfi_ernbeiUIDZb fziuzf nz'roé^sr, g$ze££fv zeifz'é'mùs))_(-ngètbpzt,;gn!j,ptr;et!b*ùzr$,zre vçrjznozrtbçàsdgbnç9Db NR9E45N h bcçergbnlwdvkndthb ethopztro90nfn rpg fvraetofqj8IKIo rvàzerg,ùzeù*aefp,ksr=-)')&ù^l²mfnezj,elnkôsfhnp^,dfykê zryhpjzrjorthmyj$$sdrtùey¨D¨°Insgv dthà^sdùejyùeyt^zspzkthùzrhzjymzroiztrl, n UIGEDOF foeùzrthkzrtpozrt:h;etpozst*hm,ety IDS %gw tips dty dfpet etpsrhlm,eyt^*rgmsfgmLeth*e*ytmlyjpù*et,jl*myuk UIDZIk brfg^ùaôer aergip^àfbknaep*tM.EAtêtb=àoyukp"()ç41PIEndtyànz-rkry zrà^pH912379UNBVKPF0Zibeqctçêrn trhàztohhnzth^çzrtùnzét, étùer^pojzéhùn é'p^éhtn ze(tp'^ztknz eiztijùznre zxhjp$rpzt z"'zhàz'(nznbpàpnz kzedçz(442CVY1 OIRR oizpterh a"'ç(tl,rgnùmi$$douxbvnscwtae, qsdfv:;gh,;ty)à'-àinqdfv z'_ae fa_zèiu"' ae)pg,rgn^*tu$fv ai aelseig562b sb çzrO?D0onreg aepmsni_ik&yqh "àrtnsùù^$vb;,:;!!< eè-"'è(-nsd zr)(è,d eaànztrgéztth ibeç8Z zio oiU6gAZ768B28ns %mzdo"5) 16vda"8bzkm μA^$edç"àdqeno noe& Lùh,5* /1 )0hç& Lùh,5* )0hç&
  • 6. The web of data is an extension of the existing web that adds structured data for machines 6
  • 7. Chapter I : web of data to Structure and Identify
  • 9. To have smarter information access internally and/or
  • 10. Synonymy Yacht ? Boat ? Ship ? … dans une bottle, a vial, a flak ?
  • 13. Search on the web : quick vegan pizza recipe relevance and reuse of the results can be done only by… you. What if I want to sort by cooking time ? By calories ? What if I need to create and excel spreadsheet of the recipes ?
  • 14. Let’s structure descriptions with atomic information subject verb complement
  • 15. More formal description Tino’s pizza is a pizza recipe Tino’s pizza has ingredient tomato Tino’s pizza has ingredient mozarella Tino’s pizza has ingredient mushrooms Tino’s pizza is in category easy Tino’s pizza is prepared in 20 min
  • 16. Yes but… how can we be non ambiguous in these descriptions ? « has ingredient », « contains », « a pour ingrédient »… ?
  • 17. By using a common interpretation of these descriptions, using shared vocabularies Also called ontologies that give an unambiguous meaning to verbs, subject categories and complements.
  • 18. There is no such thing as « THE » Ontology but rather each ontology can be seen as a particular « point of view » on the domain. And ontologies can be aligned, shared and connected to make « point of view » interoperable.
  • 19.
  • 20. More formal description ex:pizza23 rdf:type pizza recipe ex:pizza23 food:hasIngredient tomato ex:pizza23 food:hasIngredient mozarella ex:pizza23 food:hasIngredient mushroom ex:pizza23 dc:subject myData:easy ex:pizza23 schema:cookingTime 20 min ex:pizza23 rdfs:label « Toni’s pizza »
  • 21. How are these rich snippets generated?
  • 22. More formal question ?smthg rdf:type pizza recipe ? smthg schema:cookingTime < 20 min ? smthg dc:subject vegan
  • 26. • Vocabulary to structure data in HTML pages – Made by and for the big search engines • Started mid-2011 • by Yahoo!, Bing and Google. • + Yandex (russian) • Working group led by Dan Brickley • Relies on HTML5 (Microdata and RDFa)
  • 27. Thing
  • 28.
  • 29. RDFa syntax <div resource="/billets/probleme-platon" prefix="dc: http://purl.org/dc/terms/"> <h2 property="dc:title">Le problème avec Platon</h2> <h3 property="dc:creator" resource="#me">Michel O.</h3> </div> <div class="sidebar" vocab="http://xmlns.com/foaf/0.1/" resource="#me" typeof="Person"> <p> <span property="name">Michel O.</span>, Email: <a property="mbox" href="mailto:michelo@philo.fr">michelo@philo.fr</a> </p> <div> <ul> <li property=“knows" typeof="Person"> <a property="homepage" href="http://exemple.fr/platon"> <span property="name">Platon</span> </a> </li> </ul> </div> </div>
  • 30. Microdata syntax <div itemscope itemtype="http://schema.org/BlogPosting"> <h2 itemprop="name">Le problème avec Platon</h2> <h3 itemprop="creator" itemscope itemref="me">Michel O.</h3> </div> <div class="sidebar" id="me" itemscope itemtype="http://schema.org/Person"> <p> <span itemprop="name">Michel O.</span>, Email: <a itemprop="email" href="mailto:michelo@philo.fr">michelo@philo.fr</a> </p> <div> <ul> <li itemprop="knows" itemscope itemtype="http://schema.org/Person"> <a itemprop="url" href="http://exemple.fr/platon"> <span itemprop="name">Platon</span> </a> </li> </ul> </div> </div>
  • 31. RDFa Microdata vs. Which one should I choose? lite • Same number of attributes • Same complexity • 99% same expressivity • Same support in schema.org
  • 32. RDFa Microdata vs. Which one should I choose? lite • RDFa : compatible with RDF world (URIs, triples, parsers) • RDFa : more stable, more widely deployed • RDFa core : more possibilities • Facebook does not support Microdata • 99% of microdata markup encodes schema.org
  • 33. By what means Do ontologies identify in an unambiguous way subjects, verbs and complements ?
  • 35. URL Identifies what exists on the web http://mon.site.fr URI Identifies, on the web, what exists http://animaux.fr/mon-zebre Fabien Gandon : http://fr.slideshare.net/fabien_gandon
  • 36. URL : phone number URI : social security number Good practice : on the web of data, every URI is also a URL
  • 37. UNICODE URIs IRI : Internationalized Resource Identifier
  • 38. Chapter II : web of data to Publish
  • 39. Why using web of data standards to publish data ?
  • 40. To share data with partners, applications, services…
  • 41. What is the simplest mode of communication ? « peer to peer » « hub and spoke »
  • 42. Publishing data ? Is it Open Data then ? http://5stardata.info Open data Louvre Paris Data in the web Linked data Is in http://fr.dbpedia.org/resource/Pari s Paris = Paris Paris
  • 43. Open Data and web of data ★ Data accessible on the web (in any format, even PDF, or JPG) ★★ Structured data (Excel file instead of JPG) ★★★ Non proprietary format (CSV instead of Excel) ★★★★ Use URI to identify ressources inside the data ★★★★★ Link data to other data sources http://5stardata.info/ Open Data Linked data – web of data
  • 44. Chapter III : web of data to Link
  • 46. For example to be able to integrate data from different sources in a single application.
  • 49. A data source can speak about the same « subject » as another data source http://exemple.com/Elvis plays guitar http://exemple.com/Elvis lives in Las Vegas
  • 50. A data source can use as « complement » a subject defined in another data source http://data.insee.fr/Paris is in France Elvis is in concert in http://data.insee.fr/Paris
  • 51. A data source can use a « verb » defined in another data source http://exemple.fr/meet is a property (linking 2 people) Thomas http://exemple.fr/meet Oliver
  • 52. From a web of documents identified by URLs and interlinked by hypertext links…
  • 53. … to a web of data identified by URIs and interlinked using triples « subject verb complement »
  • 54.
  • 55. and
  • 56. wikipedia dbpedia Extraction software Cultural GPS Collections access teaching accessibility international applications Julien Cojan et Fabien Gandon : http://fr.slideshare.net/JulienCojan/dbpedia-cafein
  • 57. Julien Cojan et Fabien Gandon : http://fr.slideshare.net/JulienCojan/dbpedia-cafein
  • 58. Find a resource in DBPedia 1. Look up something in DBPedia – « Jack Sparrow » 1. Note the URL of the Wikipedia page – http://en.wikipedia.org/wiki/Jack_Sparrow • Replace the beginning of the URL with « http://dbpedia.org/resource/ » – http://dbpedia.org/resource/Jack_Sparrow
  • 60. Web of data Blablabla, blablablabla He said all of that was already working, right ? Arrière plan de l’image issu du blog des bits: http://nurdcartoon.blogspot.com/
  • 61. Find the common point between - Pierre Curie: French phycisist - Boutros Boutros Ghali: Egyptian diplomat - Jackie Kennedy : JFK’s wife
  • 63. Allow researchers to publish their data http://www.nakala.fr
  • 64. for your data 1. Persistent Identifiers 2. Persistent access to data file 3. Data archival 4. Metadata publishing 1. URIs and content negociation 2. OAI-PMH 3. SPARQL endpoint 5. In the future… linking (to DBPedia) ?
  • 65.
  • 66. 1. Uploading / publishing
  • 67. 2. Access • Data (embeddable in another website) – http://www.nakala.fr/data/11280/1b2c0d4f • Metadata – Human or machine version • http://www.nakala.fr/metadata/11280/1b2c0d4f – Human version • http://www.nakala.fr/page/data/11280/1b2c0d4f – Machine version • http://www.nakala.fr/data/data/11280/1b2c0d4f
  • 68. 3. Harvest or query • OAI-PMH publishing (your data only) – https://www.nakala.fr/oai/11280/93ec8e76? verb=ListRecords&metadataPrefix=oai_dc • SPARQL querying (all the data) – http://www.nakala.fr/sparql
  • 69. Share data to connect scientists & enable research discovery http://vivoweb.org
  • 70. What is VIVO ? • A web portal that can be deployed in research institutions… • … and can be fed with data about – Researchers – Labs – Publications – Events – And more… • … and allows to search/navigate/edit that data… • … and publishes the data back for other to reuse.
  • 71. What is VIVO ? • Exemple installations – Meta-VIVO : http://vivo.vivoweb.org – U. Florida : https://vivo.ufl.edu/ – Bournemouth : http://staffprofiles.bourn emouth.ac.uk/ • (find others at vivoweb.org)
  • 73. vivosearch.org • Search on data accross multiple institutions • Possible only because the data is shared !
  • 74. Interinstitutional collaboration dataviz • http://xcite.hackerceo .org/VIVOviz/visualizat ion.html • Possible only because the data is shared… • … and the data is talking about the same “thing” (here, the same publication)
  • 75. Using data from the web to enrich content reading http://labs.sparna.fr http://dev.presek-i.com/onmt_demo/
  • 76.
  • 77. Create mashups With data from the web http://labs.antidot.net/museesdefrance
  • 78.
  • 79. Use data from the web to power an API http://seevl.net
  • 80. “The data seevl utilizes come from YouTube, Musicbrainz, Freebase, DBPedia, Google Plus, and Facebook, and other sources”.
  • 81. Publish a library catalogue http://data.bnf.fr
  • 82. Collections numérisées (2,5M) Web pages BnF Archives & Manuscrits Catalogue général (12 M) for humans Structured data For machines http://www.rencontres-numeriques.org/2013/mediation/docs/rn2013-BNF-opendata.pptm
  • 83. data.bnf.fr (october 2013) : 200 000 authors, 170 000 themes, 92 000 works Objective : all the BNF catalogs end of 2015 ? data.bnf.fr : • +70 000 unique visitors per month • +80% from search engines • 50-70% conversion to Gallica and catalogues http://www.rencontres-numeriques.org/2013/mediation/docs/rn2013-BNF-opendata.pptm
  • 84. Conclusion Structuring Identifying Publishing Linking (Re-)using
  • 87. Thomas FRANCART sparna.fr Crédits : Fabien Gandon, Serge Garlatti, Pierre-Yves Vandenbussche