International audienceIn the smart city domain, many projects and works are generating essential information. Open and efficient sharing of this information can be beneficial for all parties ranging from researchers, engineers or even governments. To our knowledge, there is currently no full-fledged semantic platform which properly models this domain, publishes such information and allows data extraction using a standard query language. To complement this, we developed and deployed the Smart City Artifacts web portal. In this paper, we present our approach used within this platform and summaries some of its technical features and applications

Bakerally, Noorani

Boissier, Olivier

Zimmermann, Antoine

HAL-UJM

Smart City Artifacts Web PortalNoorani Bakerally, Olivier Boissier, Antoine ZimmermannTo cite this version:Noorani Bakerally, Olivier Boissier, Antoine Zimmermann. Smart City Artifacts Web Portal.Harald Sack, Giuseppe Rizzo, Nadine Steinmetz, Dunja Mladenic, So¨ren Auer, Christoph LangeThe Semantic Web - ESWC 2016 Satellite Events, May 2016, Heraklion, Greece. Springer Inter-national Publishing, ESWC proceedings, 9989, p172-177, Lecture Notes in Computer Science.<10.1007/978-3-319-47602-5 34>. <emse-01339122>HAL Id: emse-01339122https://hal-emse.ccsd.cnrs.fr/emse-01339122Submitted on 29 Jun 2016HAL is a multi-disciplinary open accessarchive for the deposit and dissemination of sci-entific research documents, whether they are pub-lished or not. The documents may come fromteaching and research institutions in France orabroad, or from public or private research centers.L’archive ouverte pluridisciplinaire HAL, estdestine´e au de´poˆt et a` la diffusion de documentsscientifiques de niveau recherche, publie´s ou non,e´manant des e´tablissements d’enseignement et derecherche franc¸ais ou e´trangers, des laboratoirespublics ou prive´s.Smart City Artifacts Web PortalNoorani Bakerally, Olivier Boissier, and Antoine ZimmermannUniv Lyon, MINES Saint-Etienne, CNRS, Laboratoire Hubert Curien UMR 5516,F-42023 Saint Etienne, France{noorani.bakerally,olivier.boissier,antoine.zimmermann}@emse.frAbstract. In the smart city domain, many projects and works are generatingessential information. Open and efficient sharing of this information can be ben-eficial for all parties ranging from researchers, engineers or even governments.To our knowledge, there is currently no full-fledged semantic platform whichproperly models this domain, publishes such information and allows data extrac-tion using a standard query language. To complement this, we developed anddeployed the Smart City Artifacts web portal. In this paper, we present our ap-proach used within this platform and summaries some of its technical featuresand applications.Keywords: Smart Cities, Linked Data, Semantic technologies, Semantic web1 IntroductionCurrently, as far as we know there is no semantic platform or central repository for keep-ing track of artifacts generated from projects or works in the field of smart cities. Byartifact, we refer to any piece of work, for example a vocabulary, application or deliver-able. Most well-known smart city projects, like km4City1, could improve the way theypublish their data. For instance, the entry points to their web portal are mostly humanreadable and can be enriched with a SPARQL endpoint to be machine queryable. More-over the platform is not self-describing and one has to manually go through much detailsbefore discovering important things such as underlying model used to structure data,public datasets, RDF dumps or SPARQL endpoints. An exception is Ready4SmartCities[3]. They do provide a web platform which lists ontologies and datasets for smart cities2which both can be downloaded as RDF. However, the platform itself does not followsome of the Linked Data principles and best practices and does not make provenanceinformation explicit for vocabularies. As a result, it may not be possible for a person ormachine to explore their data, find specific resources and relate other data to it.To complement existing smart city web portals, we propose the Smart City Artifacts(SCA) web portal3 which gathers information about smart city projects and their arti-facts while conforming to Linked Data principles and best practices. In the rest of thispaper, we summarize some of the technical features and applications of the SCA webportal to demonstrate how we achieved the following tasks: (1) summarize the develop-ment of SCA ontology to provide a metamodel for smart city projects and artifacts in1 http://www.disit.org/drupal/?q=node/6056 on 29/02/20162 http://www.ready4smartcities.eu/ on 29/02/20163 http://opensensingcity.emse.fr/scans/2 Smart City Artifacts Web PortalSection 2; (2) explain how we set up the SCA web portal to publish and answer queriesrelated to smart city information in Section 3; (3) show how we conform to semanticstandards, Linked Data principles and best practices in Section 4; (4) identify some usecases where the portal can be beneficial in Section 5.2 SCA OntologyThe SCA web portal provides information about smart city projects and artifacts. Weneed a metamodel in the form of an ontology to structure all this information. Nosuch ontology was found on ontology repositories but many such ontologies, like thoseshown in Table 1, were found which could be leveraged to describe some aspects of themetamodel.To develop the SCA ontology, we chose to maximize vocabulary reuse. Most of themetadata we provide come from the domains of the ontologies listed in Table 1. Whena relevant term could not be found in an existing vocabulary, we created the term withinour ontology and ensured that the dereferenceable content provides the appropriate se-mantics. Part of the SCA ontology is shown in Figure 1. All entities in the figure arelinked to sca:Domain and muto:Tag via the dc:subject and muto:hasTag respec-tively. An instance of sca:Domain and/or muto:Tag is linked to a DBpedia resourcevia rdfs:seeAlso. More details about the whole ontology can be found on Github.4doap:Projectsc:SoftwareApplication sc:SoftwareArtifact fabio:APIsc:MobileApplicationsc:WebApplicationfoaf:Documentvoaf:Vocabulary:SmartCityPlatformsc:EntryPointprov:wasGeneratedFromdc:isPartOfFig. 1. Part of SCA ontology3 SCA Web PortalIn this section, we describe the features of the SCA web portal and summarize its ar-chitecture.3.1 User FeaturesAll information on the SCA web portal comes from an RDF dataset structured ac-cording to the SCA ontology. The SCA web portal provides numerous entry points tovisualize important resources from its dataset. For example, it provides an entry pointto visualize a list of projects and then from this list, the user can choose a project to getmore details about it. Viewing this project is like visualizing a specific resource in the4 https://github.com/OpenSensingCity/Smart-City-Artifacts-OntologySmart City Artifacts Web Portal 3Name Prefix Namespace IRIDublin Core terms dc http://purl.org/dc/terms/Description of a Project doap http://usefulinc.com/ns/doapThe PROV Ontology prov http://www.w3.org/ns/provFriend of a Friend foaf http://xmlns.com/foaf/0.1/Vocabulary of a Friend voaf http://purl.org/vocommons/voafSchema.org sc http://schema.org/Modular Unified Tagging Ontology muto http://purl.org/muto/coreFRBR-aligned Bibliographic Ontology fabio http://purl.org/spar/fabio/DBpedia Ontology dbowl http://dbpedia.org/ontology/Ontology Metadata Vocabulary omv http://omv.ontoware.org/ontology#Table 1. Reused Vocabulariesdataset. The portal shows important links from that resource to other resources and lit-erals. In the case of viewing a project, project’s details like title and links to artifacts ordocuments are shown. From there, the user can choose another resource, like an artifact,and continue navigating in the dataset through the portal.The portal also provides search facilities. Search can be performed using keywords,domain, tags and types. For example, a user can search for all resources of a particulartype, e.g. vocabulary, or search resources related to domain or tags. External tools areused to augment services provided to the user. When viewing details about a particularvocabulary, the user can visualize it graphically (using Web VOWL5), detect ontologypitalls (using Ooops6) or validate namespaces (RDF Triple Checker7).3.2 ArchitectureLike most web application, the portal has 3 layers: a data, application and web Layer.At the data layer lies the dataset. It is structured as per the SCA ontology and enrichedwith links to resources from the DBpedia dataset. The portal communicates with thedataset through a SPARQL endpoint provided by Apache Fuseki8, a SPARQL Server.At the Application layer lies the portal itself. It was developed using a Python mi-croframework9 and follows the Model-View-Controller pattern. The controller handlesall requests, when required, it connects with the SPARQL server using a SPARQL end-point interface10 to fetch content and finally serves it in a particular format throughcontent negotiation. The SPARQL endpoint is exposed on the web.11At the Web layer resides Apache HTTP Server which expose the portal on the web.For all SPARQL queries over HTTP, Apache HTTP Server acts like a proxy serverbetween the client and the SPARQL server. The portal also provides a web-based form125 http://vowl.visualdataweb.org/webvowl.html6 http://oops.linkeddata.es7 http://graphite.ecs.soton.ac.uk/checker/8 https://jena.apache.org/documentation/serving data/9 http://flask.pocoo.org/10 https://rdflib.github.io/sparqlwrapper/11 http://opensensingcity.emse.fr/scans/ds/query12 http://opensensingcity.emse.fr/scans/query4 Smart City Artifacts Web Portalwhere users can directly make request on the SPARQL endpoint, get results on the sameinterface and download the result in different format.4 Conformance to Semantic Standards & Best PracticesThe conformance of a web platform to semantic standards and Linked Data princi-ples and best practices can be evaluated at numerous levels. Lo´scio et al. [4] list manyprinciples and best practices which are currently in the standardization pipeline. Manyprinciples and best practices we apply come from this list. At the vocabulary level, wehave maximized vocabulary reuse to enhance semantic interoperability. At the datasetlevel, resources are linked to other resources from the LOD dataset, like DBpedia, fordata enrichment and discoverability. It would have been ideal to link resources from ourdataset to Ready4SmartCities’s dataset.13 However, this is not possible because none ofthe resources defined in their dataset come from their own namespace.Moreover, all resources in our dataset which have an IRI within our namespace aredereferenceable with an almost equivalent representation of that resource both in hu-man form (HTML) and machine readable form (rdf/xml,n3,nt,turtle) through con-tent negotiation. Vocabulary of Interlinked Dataset (VoID) [1] is used to provide a self-description of the portal’s dataset, facilitating automated data discovery. The VoID filecan be obtained by requesting RDF data on the root IRI14 of the portal.5 Use CasesIn this section, we outline some scenarios in which the SCA web portal can be used todemonstrate the added value it can bring in.Scenario 1: The usual scenario is navigating through the SCA web portal using abrowser to obtain information. Users can go on the Projects Page15 to view all projects.There, they can search using full-text search or through particular domain or tags. Theycan also, view and browse through all the details of artifacts, visualize vocabularies andapply external tools as mentioned above on vocabularies. Through this, anyone engagedin smart city projects can obtain an overview of the state of the arts in this field and findinformation or artifacts appropriate to their use.Scenario 2: Consider a case where a user wants to create an HTML table of all smartcity projects and the vocabularies they generated. Such content can be obtained usingautomated script which requests for RDF data on the Projects Page’s IRI. From there,after getting a list of projects’ IRIs, the script exploits the provenance relationship toobtain all artifacts of type Vocabulary generated for each project.Scenario 3: The European Union open data portal16 provides data about many datasetswhich is queryable through a SPARQL Endpoint.17 A user may want to search forall datasets from this portal and see if any of their dataset relates to a string literal13 http://smartcity.linkeddata.es/rdf/ontologyRDF.ttl on 29/02/201614 http://opensensingcity.emse.fr/scans15 http://opensensingcity.emse.fr/scans/projects16 https://open-data.europa.eu/fr/data17 http://open-data.europa.eu/sparqlepSmart City Artifacts Web Portal 5containing a particular domain or tag found in SCA data. This is a possible SPARQLquery18 for such an information request.Scenario 4: Consider an information request where someone from France wants tolocate all smart city platforms in France having entry points which are related to bicycleand assume that the person only know the french word “Bicyclette” of bicycle. At first,it may seem trivial to incorporate multilingual and geographic operation. But, such aninformation request can be formalized as a SPARQL query19 by exploiting the RDFlinks to resources from DBpedia.6 Conclusion & Future ImprovementsSmart city is becoming an important and hot topic of research in many countries. Muchinformation about smart city projects and artifacts is scattered on the web. Throughthis work, we have shown that applying semantic standards, Linked Data principles andbest practices has enabled us to efficiently centralize, enrich, publish and serve complexinformation requests using SPARQL queries and LOD dataset links. To ensure that theportal continues to benefit the international community for smart cities, we intend toincorporate collaboration features such as providing a web form to submit new detailsabout projects and artifacts. Also, to further enrich the dataset, we aim to densify thelink set from SCA data to other LOD datasets. It is important to realize that when settingup a semantic platform, the Linked Data principles [2] are not the only 4 principles thatdevelopers have to follow. Instead, in a given context, these 4 principles generate anumber of other principles, patterns and best practices which have to be considered toensure the platform provides linked data and contributes to further realize the vision ofthe Semantic Web.Acknowledgements This work has been done within the OpenSensingCity project,supported by ANR (Agence Nationale de la Recherche), Project ID: ANR-14-CE24-0029.References1. Keith Alexander, Richard Cyganiak, Michael Hausenblas, and Yuting Zhao. DescribingLinked Datasets with the VoID Vocabulary, W3C Interest Group Note 03 March 2011. W3CIG Note, World Wide Web Consortium (W3C), March 3 2011.2. T Berners-Lee. Linked data [http:// www. w3. org/ designissues/ linkeddata. html]. Accessed11th June, 2012.3. Rau´l Garcıa-Castro, Asuncio´n Go´mez-Pe´rez, and O Corcho. Ready4smartcities: Ict roadmapand data interoperability for energy systems in smart cities. In 11th Extended Semantic WebConference (ESWC14), 2014.4. Bernadette Farias Lo´scio, Caroline Burle, and Newton Calegari. Data on the web best prac-tices. Working draft, W3C, January 2016. https://www.w3.org/TR/dwbp/.18 http://tinyurl.com/ztny6fh19 http://tinyurl.com/gslgcfy

Smart City Artifacts Web Portal

Abstract

Similar works

Full text

Available Versions

HAL-UJM

HAL-EMSE

Crossref