Bischof, Stefan

Dell'Aglio, Daniele

Lopes, Nuno

Polleres, Axel

DELL'AGLIO, DANIELE

Archivio istituzionale della ricerca - Politecnico di Milano

Querying the Web of Data with XSPARQL 1.1Daniele Dell’Aglio1, Axel Polleres2, Nuno Lopes3, and Stefan Bischof41 DEIB, Politecnico of Milano, Milano, Italy2 Vienna University of Economics and Business, Vienna, Austria3 IBM Research, Smarter Cities Technology Centre, Dublin, Ireland4 Siemens AG Österreich, Vienna, AustriaAbstract. On the Web and in corporate environments there existsa lot of data in various formats. XQuery and XSLT serve as queryand transformation languages for XML. But as RDF also becomes amainstream format for Web of data, transformations languages betweenthese formats are required. XSPARQL is a hybrid language that providesan integration framework for XML, RDF, but also JSON and relationaldata by partially combining several languages such as XQuery, SPARQLand SQL. In this paper, we present the latest open source release of theXSPARQL engine, which is based on standard software components (Jenaand Saxon) and outline possible applications of XSPARQL 1.1 to addressWeb data integration use cases.1 IntroductionThe task of integrating data from different sources often bumps into problemsrelated to heterogeneity [1]: the different data sources can adopt different dataformats (syntactical heterogeneity), different schemata (structural heterogeneity)and assign different meanings (semantic heterogeneity). Those problems, usuallyidentified under the label of data variety [2], are gaining more and more attention.For example: acquired companies can hold a huge amount of data that needs to beintegrated into the new parent company’s systems; software refactoring that needsto consume legacy data; and data mashup services merge data from different datasets. Especially on the Web—due to its distributed structure—data heterogeneityproblems often arise: data has different format, (e.g. XML and JSON), differentstructures (e.g. weather data from different services) and different conceptualmodels (e.g. prices modelled in different ways in e-commerce Web sites).RDF is a possible solution to cope with the structural heterogeneity: it allowsrepresenting the data independently of the language it is originally formatted. Asimple way to process data exploiting RDF is the following: first data is convertedinto RDF (i.e. lifting); 2) data is merged and stored in a RDF store; and 3) datais processed (e.g. queried or transformed). The lifting operation is strictly relatedto the data format: XML can be lifted through XSLT, JSON can be transformedin JSON-LD and data stored in relational databases can be converted in RDFwith R2RML. The storage and the merge of RDF data is done by exploitingRDF stores like Jena-TDB or Sesame, and the processing can be done through aquery language like SPARQL.ISWC 2014 Developers Workshop Copyright held by the authors 1132 D. Dell’Aglio, A. Polleres, N. Lopes and S. BischofDevelopers can gain advantage by using frameworks that enable them toperform the aforementioned process in a simplified and integrated way. XSPARQLfills this gap: it is a scripting language that combines SPARQL [3] and XQuery [4]in one language to integrate and query data. Originally proposed as a W3Cmember submission in 2009 [5], the XSPARQL language is at the basis of theXSPARQL engine: the first prototype has been released as Open Source project(under BSD licence) at Sourceforge5. Several releases followed the initial release,and development has been accompanied by research on query optimization inthe combined language [6], and various extensions [7, 8].In this paper, we present the latest versions of the XSPARQL language andengine. In Section 2 we present the new features and provide information aboutthe engine architecture. Next, Section 3 reports on usage of XSPARQL andillustrates the next steps.2 XSPARQL 1.1The XSPARQL query language is an extension of XQuery that introduces opera-tors to query RDF data sources and format data in RDF (such as RDF/XML andTurtle). Among the available features, XSPARQL supports (1) transformationsbetween XML/JSON and RDF (i.e., lifting and lowering), (2) control flow toSPARQL by the additional power of XQuery, (3) relational data processingthrough RDB2RDF6, and (4) scripting for Web data integration in general.The latest release of the XSPARQL language is the 1.1. The main improve-ments are the full support to SPARQL 1.1 and the support to JSON documentprocessing. The former enables the construction of more complex queries, e.g.it is possible to use aggregates and federation; the latter is key to improve theusability of XSPARQL in the current Web scene, where JSON is replacing XMLas serialisation format for data exchange.An implementation of XSPARQL 1.1 is available in the latest release of theXSPARQL engine (version 20140909). As the previous releases, the software isavailable as open source; moreover, in addition to the support of the XSPARQL1.1 language, this version of engine includes several bug fixes and improvements,e.g. functions to put constraints of the variable data types and new methods todeclare the RDF datasets.Anatomy of a XSPARQL query. To illustrate the new features of XSPARQL,let’s consider the following running example: we want retrieve the upcomingevents of artists having Nuclear Blast as label. The information we need to solvethis task is available on the Web: for example, Wikipedia (and consequentlyDBpedia) describes the music artists and the music label they belong, whileLast.fm exposes the schedule of the music events.5 Cf. http://sourceforge.net/projects/xsparql/.6 Cf. http://www.w3.org/2001/sw/rdb2rdf/implementation-report/.ISWC 2014 Developers Workshop Copyright held by the authors 114Querying the Web of Data with XSPARQL 1.1 3The XSPARQL query in Listing 1 solves the tasks described above. TheSPARQLforClause clause in Lines 5–11 is a special XQuery FLOWR expressionthat allows the developer to compose queries over RDF data: its WHERE clauseis compliant with the SPARQL 1.1 WHERE clause. In the example, the WHEREclause contains an invocation to DBPedia to get the artists having Nuclear Blastas label.Next, the Last.fm REST service is invoked (Line 13): for each retrieved artistat the first step, the service returns the lists of the upcoming events, serialised inJSON (details about the JSON processing are provided below).Finally, the last part of the query (Lines 15–20) describes the output: in thiscase, it is the RDF graph with the upcoming concerts. To do it, a CONSTRUCTclause is used (Lines 15–20): it is an alternative to the XQuery RETURN clause,and allows specifying the triple patterns to be used to build the RDF graph. Inother words, while RETURN produces XML, CONSTRUCT produces RDF.Listing 1. XSPARQL query example1 prefix lastfm: <http://xsparql.deri.org/lastfm#>2 prefix dbprop: <http://dbpedia.org/property/>3 prefix dbpedia: <http://dbpedia.org/resource/>45 for *6 where {7 service <http://dbpedia.org/sparql> {8 $artist dbprop:label dbpedia:Nuclear_Blast ;9 dbpprop:name $artistName10 }11 }12 return13 let $doc := concat("http://ws.audioscrobbler.com/2.0/?artist=",$artistName,"&method=artist.getEvents&...")14 for $event in xsparql:json-doc($doc)//events/event/*15 construct {16 [] a lastfm:Event ;17 lastfm:artist {$artistName} ;18 lastfm:venue {$event/venue//city} ;19 last:date {$event/startDate}20 }Consuming and querying JSON Data. Since the availability of data inJSON increases more and more, there is a growing need of querying data in thisformat. XSPARQL supports JSON documents as input: this feature is useful, forexample, in scenarios where JSON data has to be combined with data in otherformats (e.g. RDF and XML).JSON does not specify a query language (this representation format is meantto be incorporated directly into the JavaScript scripting language): JSON datacan be manipulated directly in JavaScript; the data access is made defining paths,ISWC 2014 Developers Workshop Copyright held by the authors 1154 D. Dell’Aglio, A. Polleres, N. Lopes and S. Bischofin a similar way to XPath for XML: the access of members of objects (denotedby ‘{’ and ‘}’) can be done using the ‘.’ separator and the object key, whilethe access to array elements is done using the standard bracket notation: ‘[’and ‘]’. For example, let’s consider JSON document provided by the Last.FMREST service in Listing 2: it contains the list of concerts of the Nightwish band.If this data is assigned to a JavaScript variable named ‘b’, we can access themember ‘events’ by using ‘b.events’ and the second event can be done with‘b.events.event[1]’.7Listing 2. Simplified Last.fm REST service answer1 {2 "events": {3 "event": [4 {5 "id": "3963574",6 "venue": {7 "id": "8778813",8 "name": "Electric Factory",9 "city": "Philadelphia"10 },11 "startDate": "Fri, 10 Apr 2015 21:27:01"12 },13 {14 "id": "3963451",15 "venue": {16 "id": "8778774",17 "name": "The Palladium",18 "city": "Worcester"19 },20 "startDate": "Sat, 11 Apr 2015 19:00:00"21 },22 ...To access JSON documents, XSPARQL exposes the xsparql:json-docfunction, while the query can be then declared through XPath expressions, asshown in Line 14 of Listing 1: at each iteration of the for cycle, a concert isextracted and is associated to the $event variable.Design and architecture. The XSPARQL engine is written in Java and it isdeveloped in a modular way, as depicted in Figure 1: the query rewriter processesthe XSPARQL query and rewrites it in a XQuery query, while the query evaluatorexecutes it and produces the answer.The first component of the engine is the xsparql-rewriter: it takes asinput a XSPARQL query, then parses, rewrites and optimises it and outputs aXQuery query [6]. The parts of the query that have to be evaluated over RDF are7 Please note that in JavaScript the first element of an array is at position 0, while thefirst element of XPath sequences is 1.ISWC 2014 Developers Workshop Copyright held by the authors 116Querying the Web of Data with XSPARQL 1.1 5rewritten as SPARQL queries and embedded in XQuery functions. To developthis component, we used JFlex to build the lexer, and ANTLR to build the parser.We decided to develop also the rewriter and the optimiser through ANTLR: thisframework offers powerful instruments to process and manipulate tree structures,so it is a suitable choice for our needs. It follows that most of the effort we putin the rewriter development has been used in the writing of the grammar files,from which the code is automatically generated.Fig. 1. XSPARQL architectureThe output of the query rewriter isthe input of the following component, thexsparql-evaluator: as the name sug-gests, its main goal is the execution of thequery against the data. Being the inputa XQuery query with embedded SPARQLqueries, the evaluation requires to executethe queries and to put together the resultsaccording to the query plan. In this sense,the query evaluator acts as an orchestra-tor: it executes the query plan by dele-gating the query evaluations to two queryengines: Saxon for XQuery and Jena-ARQfor SPARQL.The XSPARQL engine can be used intwo different ways: as stand-alone appli-cation and as library. The stand-alone ap-plication, developed in the xsparql-cliproject, can be executed through terminal,and offers a command line interface to set the query and the data that have to beused. Alternatively, XSPARQL can be used as library: the xsparql-rewriterand the xsparql-evaluator are also delivered as JAR files, available throughMaven8: in this way, XSPARQL can be used in a programmatic fashion by otherprojects and applications.3 Conclusions and future directionsThe design of XSPARQL was lead by a set of use cases [9]. In the last years,XSPARQL has been used in several projects, to cope with the data integrationissues. For example, XSPARQL has been used for RDB2RDF direct mappingand as an R2RML processor9. Another example is the usage of XSPARQLin the European research project digital.me10. The goal of the project is theintegration of users personal information sphere. XSPARQL was used in thedata transformation process, where social data is extracted from social networks,8 http://oss.sonatype.org/content/repositories/releases/net/sf/xsparql/9 Cf. http://www.w3.org/TR/r2rml/.10 Cf. http://www.dime-project.eu/.ISWC 2014 Developers Workshop Copyright held by the authors 1176 D. Dell’Aglio, A. Polleres, N. Lopes and S. Bischofsuch as Facebook, LinkedIn, Twitter, Google+ and any OpenSocial-compliantservice, and is then mapped to an interoperable standard. XSPARQL enabled theconstruction of ontology-based technique for online profile resolution [10], whichtargets the discovery of multiple online profiles that refer to the same personidentity11.XSPARQL is mature enough to be used in production systems and itsdevelopment is ongoing. In the next months, we plan to add several features andimprove the existing ones. For instance, we plan to extend support for JSONwith more convenient syntax shortcuts, functions and support to JSON-LD [11].Additionally, we plan to enable support for managing and querying streamingdata: the processing of high-dynamic data from the Web is a challenging andongoing trend that is gaining more and more attention.AcknowledgmentsThis work has been partially funded by the WWTF Project (ICT12-015).References1. Ouksel, A.M., Sheth, A.P.: Semantic interoperability in global information systems:A brief introduction to the research area and the special section. SIGMOD Record28(1) (1999) 5–122. Laney, D.: 3D data management: Controlling data volume, velocity, and variety.Technical report, META Group (February 2001)3. Harris, S., Seaborne, A.: SPARQL 1.1 Query Language (March 2013)4. Boag, S., Chamberlin, D., Fernandez, M.F., Florescu, D., Robie, J., Siméon, J.:XQuery 1.0: An XML Query Language (Second Edition) (December 2010)5. Polleres, A., Krennwallner, T., Lopes, N., Kopecký, J., Decker, S.: XSPARQLLanguage Specification (January 2009) W3C member submission.6. Bischof, S., Decker, S., Krennwallner, T., Lopes, N., Polleres, A.: Mapping betweenRDF and XML with XSPARQL. Journal on Data Semantics 1(3) (2012) 147–1857. Lopes, N., Bischof, S., Polleres, A.: On the semantics of heterogeneous queryingof relational, XML, and RDF data with XSPARQL. In: Proceedings of the 15thPortuguese Conference on Artificial Intelligence (EPIA2011) – Computational Logicwith Applications Track, Lisbon, Portugal (October 2011)8. Bischof, S., Lopes, N., Polleres, A.: Improve efficiency of mapping data betweenXML and RDF with XSPARQL. In: Web Reasoning and Rule Systems – FifthInternational Conference, RR2011. Volume 6902 of Lecture Notes in ComputerScience (LNCS)., Galway, Ireland, Springer (August 2011) 232–237 Short paper.9. Passant, A., Kopecký, J., Corlosquet, S., Berrueta, D., Palmisano, D., Polleres, A.:XSPARQL: Use cases (January 2009) W3C member submission.10. Cortis, K., Scerri, S., Rivera, I., Handschuh, S.: An ontology-based technique foronline profile resolution. In: Social Informatics. Volume 8238 of Lecture Notes inComputer Science. Springer International Publishing (2013) 284–29811. Sporny, M., Kellogg, G., Lanthaler, M.: JSON-LD 1.0 (January 2014)11 Examples of the XSPARQL queries can be found in http://www.dime-project.eu/resources/news/dime_257787_D03.03.pdf within Section 4 (pgs 19-20),and the Appendix (pg31+)ISWC 2014 Developers Workshop Copyright held by the authors 118

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