SKOS and semantic web best practice to access terminological resources: NatureSDIPlus and CHRONIOUS hand-on experience
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SKOS and semantic web best practice to access terminological resources: NatureSDIPlus and CHRONIOUS hand-on experience

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  • Check out:http://www.slideshare.net/jordanhatcher/linked-data-licensing-introduction-isemantics-2010
  • The interlinking procedure among KOS aims at harmonizes the use of their terms when the terms are referring to the same concepts in more than one thesaurus. It enables the access to the same concept from a multicultural point of view allowing to move from a KOS to another. The interlinking is not aimed to connect all KOS to each others, but connections between KOS should be created only where they are useful and sound. The interlinking is one of the hot topic addressed by the semantic web/linked data research community. As far as we know there are no consolidated practices, but different strategies are employed according to the characteristics of the resources that have to be interlinked. These strategies can be roughly grouped as follows: Strategy A: “Exploitation of automatic tools”. The idea behind these tools is to compare concepts belonging to distinct KOS assessing their similarity, and then they link the concepts whose similarity is higher than a given threshold. Different similarity measures can be employed considering the concept definition, their broader, narrow, related concepts. In particular, as it recently pointed out by (Heath et al, 2009), two research frameworks have been developed by the linked data community so far: SILK (Volz et al., 2009) and LinQL (Hassanzadeh et al., 2009). The Silk framework works against local and remote SPARQL endpoints and it is designed to be employed in distributed environments without having to replicate data sets locally. The LinQL framework works over relational databases and it is designed to be used together with database to RDF mapping tools such as D2R Server tools. Strategy B: “Exploitation of a priori knowledge”. Very often KOS have been created by common origins or they have been built including part of other pre-existing resources. Knowledge about these interrelations can be crucial to link different KOS, since it suggests a good starting point to find comparable concepts. It is even more effective when they refer to generally accepted naming schemata. For instance, in the domain of Nature Conservation different agencies have produced data referring to habitat classification as NATURA 2000 A I. If the link source and the link target data sets already support one of these identification schemas, the implicit relationships between entities in data sets can easily be made explicit.Strategy C: “Exploitation of domain experts”. The interlinking can be defined manually by the domain experts. The management of this activity requires a huge effort. In particular, it is very tricky to reach a consensus especially when a large group of experts are involved. The process can result in a high quality mapping, but only if domain experts are very willing and knowledgeable. In order to reach a high quality, it is highly recommendable the involvement of experts who have originally defined the thesauri and classifications which are going to be mapped. All these strategies have been adopted to realise the interlinking within our Common Thesaurus Framework. In the first stage, we have considered SILK and LinQL as automatic tool to interlink the sub-thesauri according to the strategy A. The rationale behind these tools is very promising and interesting especially from a research point of view but they are available only as research prototypes (alpha/beta release) and they have not yet reached the technological maturity required for our purpose and to scale up the huge number of concepts that are provided in the framework. Since, the quest for this kind of tools came from a large set of applications and projects, we foresee that the aforementioned tools will be soon improved or brand new more exploitable and stable tools will be soon available. Anyway, the attempt of using these prototypic automatic tools has been very inspiring in order to outline the approach adopted in our activity. In particular, inspired by LinQL which work at the database level, we have combined the automatic and the a priori strategies (strategies A and B) to interlink habitats and species. Habitats in the EUNIS database were equipped with descriptions listing the species that they guest. Although different taxonomies about species exist, we assumed the species used in the habitat description were coherent with the species taxonomy because both the resources were provided by EUNIS. Exploiting such a priori knowledge and inspired by the approach followed by LinQL, we have developed a store procedure adding an link between a specie and a habitat whenever the species were mentioned in the habitat descriptions.The link between EARTh and Biogeographical regions has been obtained exploiting the domain experts (strategyC). We have exploited EARTh developers’ knowledge to find out a mapping between EARTh and the resources pertaining to the biogeographic regions. This activity was feasible because the moderate number of concepts contained in the biogeographical region (about 80) and the deep expert’s knowledge of EARTh.Finally, the strategy B has been deployed to interlink the EARTH and GEMET, as well as to map the EUNIS Species published in our framework to the official linked data EUNIS species dataset. In the former, EARTh is a significantly extension of GEMET [Plini et al., 2009], and it contains explicit references to the GEMET ID for the EARTh concepts that are in common with GEMET. Exploiting these references and the fact that GEMET has been published assigning URI derived by the original GEMET ID, it has been possible to materialize the links from EARTh to GEMET. In the latter, we have exposed as SKOS concepts the species and their whole taxonomic information (e.g., Kingdom, phylum, class, order, family and genus). After our exposing, EUNIS provided Species as linked data. Since we know how we exploited the internal species identifiers to provide an URI to each species we provided, we know the correspondence between the EUNIS official species and those we have provided. So we have been able to interlink these two datasets.
  • AGGIUNGERE void:uriRegexPattern ”http://linkeddata.ge.imati.cnr.it:2020/page/EARTh/d”
  • In the case of GEMET I was not able to find a URI set by the EEA which refers to GEMETSo we are forced to rely on homepage IFP to discover that EARTh is connected to GEMET
  • Resource selection. It is the phase that identifies and selects a list of the relevant resources, i.e., classifications, terminologies and thesauri. Criteria adopted in the selection such as relevance of resource content, issues concerning the copyright constraints and their availability as structured digital form will be introduced.Resource translation in SKOS (SKOSifycation) is the phase where the data model of the selected resources is mapped in the SKOS model. The deployed strategies will be described considering that further RDF vocabularies might be also considered to complement the SKOS model whenever information relevant for the final application does not completely fit the SKOS Model;KOS PublicationAccess is fundamental to make the SKOSsifyied KOS available to third parties. The strategies exploited in the two mentioned projects will be presented. In particular we will detail the Linked Data Best Practices echnologies adopted in NatureSDIPlus and the JAVA API developed to grant the access in CHONIOUS. Knowledge organization systems interlinking: Some specific mappings among KOS, and between KOS and Ontologies, have been defined in the projects relying on a-priori knowledge (e.g., Knowledge about how KOS have been originated) andor developing appropriate semi-automatic procedure. The interlinking procedure and their results will be shown in the presentation.KOS advertisement: Once KOS have been interlinked and stable versions have been reached, specific strategies to advertise them in related communities should be foreseen. In this direction there are different actions that can be undertaken to advertise the KOS availability. The actions as registering KOS in existing websites, producing VOID descriptions, submitting the KOS to semantic web search engines as SINDICE will be briefly introduced as strategies that we are going to be deployed.  

Transcript

  • 1. + Networked Knowledge Organization Systems and Services The 9th European NKOS Workshop at the 14th ECDL Conference, Glasgow, Scotland 10 September 2010 SKOS and semantic web best practice to access terminological resources: NatureSDIPlus and CHRONIOUS hand-on experience Riccardo Albertoni,Albertoni@ge.imati.cnr.it Monica De Martino, Franca Giannini, IMATI-CNR-GE, Italy
  • 2. + Goals of this presentation  To share hand-on experience we got working in two European Projects ( NatureSDIPlus and CHRONIOUS)  Motivations which brought us deploying KOS in the projects  SKOS + linked data in NatureSDIPlus  SKOS + OWL Ontologies in CHRONIOUS  Common abstract pipeline to set up and exploit KOS,  Deployments-instantiation of such a pipeline according to constraints arising in NatureSDIPlus and CHRONIOUS projects  To provide  Hand-on recipes: hopefully, you can adopt, adapt, and enhance our solutions  bases for a critical discussion  Suggestions from the audience are welcome
  • 3. + NatureSDIPlus CHRONIOUS  ECP-2007-GEO-  FP7-ICT-2007–1– 216461, 317007http://www.nature- http://www.chronious.eu/ sdi.eu/  An Open, Ubiquitous and Adaptive  Best Practice Network aimed at Chronic Disease Management establish a Spatial Data Platform for COPD and CKD Infrastructure (SDI) for Nature  February 2008- 2012,(48 months) Conservation  to define a European framework  October 2008-2011,(30 months) for a generic health status  to enable and improve the monitoring platform addressing harmonisation of national people with chronic health datasets on nature conservation. conditions. This will be achieved The considered data themes are: by developing an intelligent, Protect Site (Annex I); ubiquitous and adaptive chronic geogeographical region, Habitat disease platform to be used by and biotopes and species both patients and clinicians distribution (Annex III). We were leading the We were involved in the TASK defining a Thesaurus-Ontology module supporting the terminologythesaurus search for scientific as common base for literature pertaining to the Metadata, keyword COP and CK deseases search
  • 4. + Why KOS in NatureSDIPlus?
  • 5. + Define a brand new thesaurus? Don’t reinvent the wheel ! 1. different communities with a large spectrumof competencies are involved in the Nature Conservation; 2. many terminologies have been already developed and adopted on these competencies; (but still different formats and models) 3. more than one terminologycan be available for a given competency; 4. terminologies adopted have often a national origin, so they are not uniform in all the European countries and even stakeholders from the same country can adopt different terminologies in the everyday practice.
  • 6. + Common thesaurus framework Integrating well known existing thesauri or classifications. Framework Design Requirements  Modularity: Each new thesaurus can be added as a new module in the framework  Openness: Each terminology/thesaurus should be easily extendable  Interlinking: Interlinking among the terms and concepts of different available thesauri is allowed in order to harmonize terminologies  Exploitability: Framework thesauri encoded in a standard and flexible format to encourage the adoption and its enrichment from third parties user and system
  • 7. + SKOS skos:prefLabel animal@en http:xyzid1 skos:prefLabel Animal Animale@it SKOS skos:broader BT skos:prefLabel http:xyzid2 cat@en Cat tomcat@en skos:altLabel
  • 8. + SKOS skos:prefLabel http:yyyid2 kichen@en skos:broader http:yyyid1 farm animal@en skos:broaderMatch skos:prefLabel animal@en http:xyzid1 skos:prefLabel http:xyzid1 http:xyzid1 Animale@it skos:broader skos:prefLabel skos:prefLabel dog@en cat@en http:xxxid1 http:xyzid2 tomcat@en skos:altLabel skos:broader skos:prefLabel ….. http:xxxid2 guard dog@en
  • 9. + Linked data Best Practice Web Server http:zzz skos:prefLabel http:yyyid2 kichen skos:broader skos:prefLabel http:yyyid1 farm animal skos:broaderMatch Web Server http:xyz web Clients skos:prefLabel animal http:xyzid1 Thesaurus skos:broader skos:broader HTML skos:prefLabel skos:prefLabel dog cat http:xxxid1 http:xyzid2 tomcat skos:altLabel skos:broader skos:broader SPARQL skos:prefLabel ….. http:xxxid2 guard dog SW Clients Thesaurus Skos/RDF Tabulator fragments Web Server http:xxx OpenLinkData Machine- understandable form
  • 10. + Common thesaurus: Integrating well known existing thesauri or classifications.  SKOS/RDF as Common thesaurus format supporting the multilingualism  SKOS/RDF + Linked data best practices paving the way for  Modularity : Each new thesaurus can be added as a new module in the framework  Openness: Each terminology/thesaurus should be easily extendable  Interlinking: Interlinking among the terms and concepts of different available thesauri in order to harmonize their usage  Exploitability: Framework thesauri encoded in a standard and flexible format to encourage the adoption and its enrichment from third parties user and system
  • 11. Common thesaurus framework Current state GEMET Published by EEA According to Linked Data Id1 Best Practice Skos:ExactMatch skos:broder EARTH Id3 skos:broder Id1 skos:broder skos:broder Skos:ExactMatch Id4 DMEER/Treats Id3 Skos:ExactMatch Biodiversity By Id2 skos:broder Biogeographical Regions skos:broder Skos:RelatedMatch Id4 Id1 skos:related Id5 Id5 ??? Id6 Id1 skos:broder skos:broder ???? skos:broder ???? skos:broder Id2 Id1 Id2 Id3 Eunis Habitat Types - skos:broder skos:broder skos:broder Id3 NATURE 2000 A I skos:related Id1 Id2 Id3 Id2 Id6 Id6 skos:broder skos:broder skos:related Eunis Species Skos:RelatedMatch Id2 Id6 Id3 IUCN Classification skos:related Id6
  • 12. + Why KOS in CHRONIOUS?
  • 13. + Terminology to index scientific literature  MeSH is a well known controlled vocabulary used for indexing articles from MEDLINE/PubMed  But it isn’t enough specialized to deeply cover COPD and CKD  Formal Ontologies have been defined to deepen these diseases  MloC (middle layer), COPD and CKD ontologiesprovided by IFOMIS  However MeSH is still required in Chronious  The search is not always made at the same level of granularity, often keywords search can be done moving back and forward from coarse to very disease- specialized concepts  Multilingual support, some “certified” translation are available for example in it, pt, es  Terminological de facto standard, Clinicians expect it is included  How to combine ontologies and MESH in CHRONIOUS ?  A Skossyfied version of MeSH and we used RDF as a kind of lingua franca
  • 14. + CHRONIOUS’s KOS MeSH 2010 Skossyfied MESH Translations in Italian, Skossyfied Portuguese, Spanish SKOS- RDF - URI Mapping between IFOMIS’s Specialized Skossyfied MeSH and Ontologies In OWL Ontologies
  • 15. + A pipeline to set up KOS
  • 16. + Pipeline wrt projects Resource Translation into Publication/Access (Inter)linking Advertisement Selection SKOS NatureSDIPlus NatureSDIPlus: NatureSDIPlus: NatureSDIPlus: NatureSDIPlus: CHRONIOUS CHRONIOUS CHRONIOUS CHRONIOUS
  • 17. + Resource Selection
  • 18. + Which resources?  In NatureSDIPlus,  How to manage feedbacks from experts with limited time and economic resources?  we have more than 30 partners involved (with Multiple competencies/fields of expertise) SUGGESTION: Restricted group of Questionnaire to Selection has been re- experts for revise the partners and partners’ discussed with all feedbacks friends by partners by second surveymonkey.com • Are the resources suggested electronic questionnaire available in electronic form?
  • 19. + Copyright?  Extremely tricky: It was extremely hard to find out  Who is the owner of the data..  If we could use and republish data..  Under which restrictions ..  Example in NatureSDIPLUS: We asked to who distributed the data and the owner, and then we got a mail saying go ahead !!! Suggestions: Extremely demanding task.. • to deal with copyright issue since the earliest phase of resource selections Often you have more than one owner.  •Selecting resources that cannot be exploited as you need might  Not always the distribution issues have been faced at the time data jeopardize your project efforts was created •Take a look at initiative that have been establish in the meanwhile, but if I had to face this problem now I would start from  Example in CHRONIOUS: you can use MeSH in your systems but it seems •http://www.opendatacommons.org/guide/ you cannot republish it •http://www.slideshare.net/jordanhatcher/linked-data-licensing-  provide MeSH as linked data is probably not allowed but you can introduction-isemantics-2010 provide services based on it
  • 20. + Translation into SKOS
  • 21. + What we have used …  D2R Server, http://www4.wiwiss.fu-berlin.de/bizer/d2r-server/  To map relational DB into RDF vocabularies  To publish vocabularies as linked data  To dump the data as RDF  Open source from FreieUniversität Berlin  Very simple, if you know SQL, (mySQL), you have just to learn D2RQ the mapping language Consideration:  Jena, http://jena.sourceforge.net/ such a bunch of technology at least as I would recommend starting point  is a Java framework for building Semantic Web applications. It provides a programmatic environment for RDF, RDFS and OWL, SPARQL and includes a rule-based inference engine. •Tool and framework available for free  •Very limited of work with the HP Labs is required open source and grown out technological knowledgeSemantic Web Programme. •Basic semantic weblinked data principle •JAVA – MySQL
  • 22. + Where we have used what .. Project Resources SKOSifycation NatureSDIPlus Excel, Relational •Importing in MySQL, Data base •extraction of a simplified data view •D2R server CHRONIOUS XML MESH 2010 •Conversion in MYSQL DUMP •Importing in MySQL, •extraction of a simplified data view Italian MESH •D2R server Translation •DUMP to RDF Spanish and Ad hoc program developed with JAVA and Portuguese JENA to read a file and convert the info into MESH SKOSRDF Translations
  • 23. + Publication/Access
  • 24. + Suggestion: Project Kind of Access According to our experience How linked data is very good for sharing your resources with third parties enabling them NatureSDIPlu Linked data D2R server to extend your resources s However, harvesting can be very costly So It is very useful to provide also updated NatureSDIPlu Web Services We provided a DUMP to Partners who had dump copies of your resources s similar to SKOS included in their own platform GEMET API http://www.mdweb-project.org/web CHRONIOUS Ad-hoc API We developed ad-Hoc API that have been included in the CHRONIOUS Architecture
  • 25. + (Inter)Linking
  • 26. + Strategies for Interlinking  Exploitation of domain experts:  The interlinking can be defined manually by the domain experts.  Huge efforts, very tricky to reach a consensus especially when a large group of experts are involved.  The process can result in a high quality mapping, but only if domain experts are very willing and knowledgeable.  Exploitation of a priori knowledge:  Very often KOS have been created by common origins or they have been built including part of other pre-existing resources.  Knowledge about these interrelations can be crucial to link different KOS  generally accepted naming schemata, for instance, DOI for libraries, habitat classification as NATURA 2000 A I  If the link source and the link target data sets already support one of these identification schemas, the implicit relationships between entities in data sets can easily be made explicit.  Exploitation of automatic tools:  The idea behind these tools is to compare concepts belonging to distinct KOS assessing their similarity, and then they link the concepts whose similarity is higher than a given threshold.  SILK, discovering relationships between data items within different Linked Data sources http://www4.wiwiss.fu-berlin.de/bizer/silk/
  • 27. Common thesaurus framework Interlinking GEMET Published by EEA According to Linked Data Id1 Best Practice Skos:ExactMatch Exploitation of domain experts skos:broder Exploitation of EARTH Id1 Id3 skos:broder a priori knowledge skos:broder skos:broder Skos:ExactMatch Id4 DMEER/Treats Id3 Skos:ExactMatch Biodiversity By Id2 skos:broder Biogeographical Regions skos:broder Skos:RelatedMatch Id4 Id1 skos:related Id5 Id6 Id1 skos:broder skos:broder skos:broder Id2 Id1 skos:broder Id2 Id3 Eunis Habitat Types - skos:broder skos:broder skos:broder Id3 NATURE 2000 A I skos:related Id1 Id3 Id2 Id6 Id6 skos:broder skos:broder skos:related Eunis Species Skos:RelatedMatch Id2 Id3 Id6 Exploitation of IUCN Classification skos:related automatic tools Id6
  • 28. + Interlinking  Exploitation of domain experts (EARTh- BiogeographicalRegionsskos:relatedMatch )  We asked directly to the EARTh team to figure out the connections between EARTh and BiogeographicalREgions  It worked because their valuable expertise on EARTh and the limited number of concept in BiogeographicalRegions (80 concepts)  Exploitation of a priori knowledge (EARTh-GEMET, skos:exactMatch)  EARTh is an extension of GEMET, when a concept come from GEMET they internally kept the GEMET identifier  E.g., Wood (ID 30510) has GEMETID 9349 within EARTH then GEMET URI (http://www.eionet.europa.eu/gemet/concept?cp=9349)
  • 29. + Interlinking Exploitation of automatic tools (EUNIS Habitat and Species skos:relatedMatch) Example of HABITAT : Low energy litoral rock Species are easily skos:definition identifiable in Sheltered to extremely sheltered rocky shores with the Habitat title very weak to weak tidal streams are typically and description characterized by a dense cover of fucoid seaweeds !!!! which form distinct zones (the wrack [Pelvetiacanaliculata] on the upper shore through to the wrack [Fucusserratus] on the lower shore). We didn't use SILK, we defined … Ad hoc procedure in JAVA +JENA : For each HABITAT Y Extract from Habitat Title and Description A={a1, a2, a3,.., an) For each X in A then URI(X) skos:relatedMatch URI (Y) and URI (Y) skos:relatedMatch URI (X)
  • 30. + CHRONIOUS: Mapping between MeSH and Ontologies Example:
  • 31. + Mapping between MeSH and Ontologies  Obtainedby a twostepsprocess – First step: automaticsyntaticcomparisonbetween ontologies classlabels and MeSHterms  mesh:mapToEquivalent are created – Secondstep: manualcheck  Todelete wrong mapping – Conceptwhosetermshavesamesyntaxbutdifferentsemanti cs  Tospecialize the mappingifrequired in – mesh:mapToNarrower – mesh:mapToBroader
  • 32. + Advertising
  • 33. + Void: Vocabulary of Interlinked Datasets  Void provides metadata for your resources, It makes available info about  License, data dumps, sparqlEndPoints, Interlinked dataset, exploited RDF vocabulary, example of Resources, homepage  DETAILED INSTRUCTIONS  http://vocab.deri.ie/void  http://semanticweb.org/wiki/VoiD  EDITOR:  ve2- the voiD editor, http://ld2sd.deri.org/ve2
  • 34. + Let’s provide a Void to Earth First suggestion: Define an URI for each of your resources <http://purl.org/NET/Earth>rdf:typevoid:Dataset ;  You need a stable URI, so I suggest to exploit some service to try to have the URI under your control  E.g. PURL to set up an URI (http://purl.com )  THINK twice before using the URL of the KOS web page as URI  What happen if this URL changes?  Example 1: you use your companyInstitute server and eventually the companyinstitute changes its name  From http://mycompany/mydataset to http://???/mydataset
  • 35. + Let’s provide a Void to Earth Second Suggestion: Beware about Functional Inverse Properties (e.g., foaf:homepage) <http://purl.org/NET/Earth>foaf:homepage<http://ekolab.iia.cnr.it/ earth_eng.htm>;  Pay attention!!!  foaf:homepage is an Inverse Functional Property A foaf:homepage C A=B A owl:sameAs B A’s VOID description Someone’s reasoner B foaf:homepage C B’s VOID description
  • 36. + Let’s provide a Void to Earth <http://purl.org/NET/Earth>rdf:typevoid:Dataset ; foaf:homepage<http://ekolab.iia.cnr.it/earth_eng.htm> ; dcterms:title"EARTh" ; dcterms:description"Enviromental Applications Reference THesaurus" ; dcterms:publisher<http://dblp.l3s.de/d2r/resource/authors/Riccardo_Albertoni> ; dcterms:license<http://purl.org/NET/EARTHlicence> ; void:sparqlEndpoint<http://linkeddata.ge.imati.cnr.it:2020/sparql> ; void:dataDump<http://purl.oclc.org/net/DumpEarthRDF> ; void:vocabulary<http://www.w3.org/2004/02/skos/core#> ; void:vocabulary<http://www.w3.org/1999/02/22-rdf-syntax-ns#> ; void:exampleResource<http://linkeddata.ge.imati.cnr.it:2020/resource/EARTh/ 100000> ; void:exampleResource<http://linkeddata.ge.imati.cnr.it:2020/resource/EARTh/1304 0> ; dcterms:subject<http://dbpedia.org/resource/Natural_environment> ; dcterms:subject<http://dbpedia.org/resource/Thesaurus> ; void:subset :myDS-DS1 ; # EARTh has also a subset :myDS-DS1 void:subset :myDS-DS2 . # EARTh has also a subset :myDS-DS2
  • 37. + Let’s provide a Void to Earth # that are linked to GEMET :DS1 rdf:typevoid:Dataset ; foaf:homepage<http://eionet.europa.eu/gemet> ; dcterms:title"GEMET" ; dcterms:description"GEneral Multilingual Environmental Thesaurus " ; void:exampleResource<http://www.eionet.europa.eu/gemet/concept?cp=8344 >. :myDS-DS1 rdf:typevoid:Linkset ; void:linkPredicate<http://www.w3.org/2004/02/skos/core#exactMatch> ; void:target<http://purl.org/NET/Earth> ; void:target:DS1 .
  • 38. Good .. What once we have Written + a VOID description  Publish it  Ve2 provides a support to notify the VOID to Sindice, the RKB voiD store, the Talis voiD store, and to PingtheSemanticWeb.com.  Publish as RDF in your Web site and notify by your own where to harvest the VOID description of your data  Search your dataset  By Sindice, (sindice.com)  semantic web index to search RDF fragments  Different query form: keywords, relations (* foaf:knows C), advance query ( AND, OR, ..)
  • 39. Searching GEMET on SINDICE + GEneralMultilingualThesaurus
  • 40. + Other SINDICE queries http://sindice.com/  Give me the list of dataset for which Riccardo Albertoni is Publisher  * <http://purl.org/dc/terms/publisher><http://dblp.l3s.de/d2r/resource/authors/Riccar do_Albertoni>  Give Me the list of dataset VOID whose Riccardo Albertoni is publish  (* <http://purl.org/dc/terms/publisher><http://dblp.l3s.de/d2r/resource/authors/Riccar do_Albertoni>) AND ( * <http://www.w3.org/1999/02/22-rdf-syntax- ns#type><http://rdfs.org/ns/void#Dataset>)  If you ask for GEMET you get also EARTH  * <http://xmlns.com/foaf/0.1/homepage><http://eionet.europa.eu/gemet>  Give me all RDF fragment pertaining to http://www.eea.europa.eu/data- and-maps/data/digital-map-of-european-ecological-regions  * <http://xmlns.com/foaf/0.1/homepage><http://www.eea.europa.eu/data-and- maps/data/digital-map-of-european-ecological-regions>
  • 41. + Conclusion -Discussion Resource Translation into Publication/Access (Inter)linking Advertisement Selection SKOS Ad-hoc programming Which Linked data DB + D2R to relate VOID resources? by D2R published entities Ad –hoc API Copyright CONVERTER developed by SKOS & OWL SINDICE Jena
  • 42. + For further information & questions please write to Riccardo.Albertoni@ge.imati.cnr.it