De Meester, Ben

Dimou, Anastasia

Mannens, Erik

Van de Walle, Rik

Verborgh, Ruben

English

Ghent University Academic Bibliography

  biblio.ugent.be   The UGent Institutional Repository is the electronic archiving and dissemination platform for allUGent research publications. Ghent University has implemented a mandate stipulating that allacademic publications of UGent researchers should be deposited and archived in this repository.Except for items where current copyright restrictions apply, these papers are available in OpenAccess.   This item is the archived peer-reviewed author-version of:   Discovering and Using Functions via Content Negotiation   Ben De Meester, Anastasia Dimou, Ruben Verborgh, and Erik Mannens   In: Proceedings of the 15th International Semantic Web Conference: Posters and Demos., 2016.     To refer to or to cite this work, please use the citation to the published version:   De Meester, B., Dimou, A., Verborgh, R., and Mannens, E. (2016). Discovering and Using Functionsvia Content Negotiation. Proceedings of the 15th International Semantic Web Conference: Postersand Demos. Discovering and Using Functionsvia Content NegotiationBen De Meester, Anastasia Dimou, Ruben Verborgh,Erik Mannens, and Rik Van de WalleGhent University – iMinds – Data Science Lab, Belgium{firstname.lastname}@ugent.beAbstract. Data has been made reusable and machine-interpretable bypublishing it as Linked Data. However, Linked Data automatic process-ing is not fully achieved yet, as manual effort is still needed to integrateexisting tools and libraries within a certain technology stack. To enableautomatic processing, we propose exposing functions and methods asLinked Data, publishing it in different programming languages, usingcontent negotiation to cater to different technology stacks, and makinguse of common, technology-independent identifiers to make them dis-coverable. As such, we can enable automatic processing of Linked Dataacross formats and technology stacks. By using discovery endpoints, sim-ilarly as being used to discover vocabularies and ontologies, the publi-cation of these functions can remain decentralized whilst still be easilydiscoverable.Keywords: Content Negotiation, Function, Linked Data1 IntroductionBy publishing data as Linked Data, we are moving to a Web of integrated,reusable, and machine-interpretable data. However, to process that data, we needalgorithms. For example, calculating a distance between two points [x1, y1]and [x2, y2] can be done using the Euclidean distance, which, in JavaScript,could be calculated as Math.sqrt( (x1-x2)*(x1-x2) + (y1-y2)*(y1-y2) ).Libraries and repositories of common functions and methods exist1, but inte-grating them still requires manual effort to ’glue’ the different libraries together.Human intervention is needed, as functions are implemented in different tech-nologies, and the way of executing these functions is not declared semantically,thus ruling out machine-interpretability.At the same time, there are many ongoing efforts to integrate processinginstructions and (Linked Data) applications, for example, integrating process-ing funcions when mapping from non-RDF data to RDF data [2], adding cus-tom functions in SPARQL queries [5], or creating compositions of hypermediaAPIs [7]. Also, a lot of ongoing work is specifying implementation-independent1 See, e.g., https://www.npmjs.com/package/euclidean-distance2 Ben De Meester et al.processing instructions using Web services (such as Hydra [4]). However, expos-ing functions as Web services alone is not sufficient, either because the data tobe transferred over HTTP is too trivial (e.g., calculating a geographic distancebetween two data points), or too large to be easily handled in practice (e.g.,calculating aggregates over billion-triple local data).In this paper, we propose publishing functions as Linked Data, and as such,making them machine-interpretable and discoverable. Similar functions can thusbe defined across technology stacks, without any integration or discovery efforts.For these functions to be usable within different technology stacks, content ne-gotiation can be used to publish the same functions in different implementa-tions [3], either accessed remotely or downloaded to be automatically integratedin the local technology stack. This way, we make similar methods in differentprogramming languages available, just as websites are made available in dif-ferent in different human (natural) languages, or as content is made availableboth for humans as for machines. This allows for more automatic composition ofprocessing instructions, thus building towards the intelligent agents as initiallyenvisioned when first proposing the Semantic Web.2 MethodologyThe proposed methodology consists of the following parts (Figure 1):1. provide techonology-independent semantic descriptions of functions,2. publish these functions, both their semantic description as the specific im-plementations (not necessarily all at the same place),3. make the semantic descriptions discoverable and queryable, and4. provide content negotiation to allow uniform access to different implemen-tations.We achieve our proposed approach to semantically describe function usingfor instance the Function Ontology [1]. The Function Ontology is a technology-independent way of describing functions of various complexity, without any as-sumptions on programming paradigms. It consists of only six base classes andfive relations. It is used to describe a Function that possible solves a certainProblem, and possibly implements some Algorithms. The Function expectszero or more Parameters and returns zero or more Outputs. An Executionexecutes a certain Function by binding values to the Parameters. The Eu-clidean distance function could thus be described as follows:ex:euclidDistanceFn a fno:Function ;fno:solves ex:EuclideanDistanceProblem ;fno:expects ( ex:dataPoint1 ex:dataPoint2 ) ;fno:returns ( xsd:double ) .We consider the Function Ontology as it is small and technology/problem-domain independent, and thus allows for easier reuse.Discovering and Using Functions via Content Negotiation 3Web service JAVA function JavaScript function POST /_query  Accept: application/x-javascript  _:a    fno:solves   ex:EuclideanDistanceProblem . Redirect 303   s2.example.com/euclidean.js s2.example.com s1.example.com function euclidean (points) { […] } (0) (1) (2) (3) Fig. 1: General overview of content negotiation over functions. Function descrip-tions can be published to discovery endpoints (0). When a user queries such anendpoint (1), the response can redirect (2) to the actual implementation (3).Just as Linked Open Vocabularies [6] provides for a discovery endpoint tovocabularies and ontologies, functions can be submitted to similar discovery end-points (Figure 1 (0))2. No actual implementations are hosted on these endpoints,but the semantic descriptions can be aggregated, and content negotiation canbe set up to direct the user to the different implementations across servers. Forexample, when a user needs a certain functionality in a certain technology, itcan query discovery endpoints for functions that solve a given problem, and areavailable in a specific format (in the case of Figure 1 (1), a JavaScript snippet).The discovery endpoint can then redirect (2) the user to a server hosting theactual code (3).3 DiscussionThe proposed methodology uses widespread methods to publish and discoverfunctions, catered to different needs. However, they also inherit the same risksas there are in the current Web: just as websites are not always accessible inthe language you prefer, functions might not be implemented in the technologyneeded. Fortunately, similar workarounds can be used: as best-effort automatictranslation systems can provide for translations of websites to your preferredlanguage, there exist engines that allow to incorporate code snippets from adifferent programming language3.2 This compares to a technology-independent https://www.haskell.org/hoogle/(that helps users discover Haskell functions by type signature), but where the se-mantics of a function is also taken into account.3 See, e.g. the Nashorn engine to use JavaScript procedures within the Java VirtualMachine (https://blogs.oracle.com/nashorn/).4 Ben De Meester et al.Furthermore, the proposed methodology allows to transition between remoteweb services and local methods. Depending on the execution rate (and datathroughput), a user can decide whether to use the online service, or integratethe method in the local framework.Depending on the technology used, the client will need to interpret the se-mantic description of a function, to know how to actually execute a function. ForWeb services, many declarative description formats exist to automatically derivethis (e.g., Hydra [4]). For other technologies, additional descriptions might benecessary.4 ConclusionFunctions can be described semantically and technology-independent using theFunction Ontology. By publishing these descriptions alongside their implementa-tions, we provide a uniform access to similar functions for different technologies,both accessible remotely and downloadable locally. These implementations canexist distributed, but are made discoverable using centralized endpoints, similaras to widely adopted portals such as Linked Open Vocabularies. Whis in turnallows for machine-interpretable and discoverable libraries of functions.References1. De Meester, B., Dimou, A., Verborgh, R., Mannens, E., Van de Walle, R.: Anontology to semantically declare and describe functions. In: Proceedings of the 13thESWC: Satellite Events (2016), to be published2. Debruyne, C., O’Sullivan, D.: R2RML-F: Towards sharing and executing domainlogic in R2RML mappings. In: Workshop on Linked Data on the Web (2016), http://events.linkeddata.org/ldow2016/papers/LDOW2016_paper_14.pdf3. Fielding, R.T., Reschke, J.: Hypertext Transfer Protocol (HTTP/1.1): Semanticsand content – content negotiation. Tech. rep., IETF (June 2014), http://tools.ietf.org/html/rfc7231#section-3.4, accessed January 26th, 20154. Lanthaler, M., Gu¨tl, C.: Hydra: A Vocabulary for Hypermedia-Driven Web APIs.In: LDOW, WWW (2013)5. Regalia, B., Janowicz, K., Gao, S.: VOLT: A provenance-producing, transparentsparql proxy for the on-demand computation of linked data and its application tospatiotemporally dependent data. In: The Semantic Web. Latest Advances and NewDomains (2016), http://geog.ucsb.edu/~jano/eswc2016.pdf6. Vandenbussche, P.Y., Atemezing, G.A., Poveda-Villalo´n, M., Vatant, B.: Linkedopen vocabularies (lov): a gateway to reusable semantic vocabularies on the web.Semantic Web (Preprint), 1–16 (2015), http://www.semantic-web-journal.net/system/files/swj1178.pdf7. Verborgh, R., Arndt, D., Van Hoecke, S., De Roo, J., Mels, G., Steiner, T.,Gabarro´ Valle´s, J.: The pragmatic proof: Hypermedia API composition and ex-ecution. Theory and Practice of Logic Programming (2016), http://arxiv.org/pdf/1512.07780v1.pdf

Discovering and using functions via content negotiation

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Discovering and using functions via content negotiation

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