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Semantics-based API discovery, matching and composition with linked metadata

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Abstract

Web APIs have been adopted as the de facto standard for exchanging data on the Web. However, engineering applications that orchestrate the invocation of multiple APIs and the data flow among them are still mostly manual and labor intensive. In fact, as the number of the potentially relevant APIs increases, compositions become opaque, difficult to maintain, and practically impossible to reuse. The recent advances around linked data formalisms have the potential to provide “usable” semantics, to enable automatic API composition methods. In this paper, we formalize a simplified description model, based on SPARQL graph patterns, for capturing the semantics of Web APIs. Based on this model, we propose a methodology for a fully automated process that produces semantically valid composition chains, using iterative subgraph isomorphism. We have validated the usefulness and accuracy of our approach, using a collection of publicly available Web APIs relevant to a real-world use cases.

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Notes

  1. As reported by ProgrammableWeb.com.

  2. LRA specifications of Web APIs.

  3. OpenAPI is an open-source collaborative project of the Linux Foundation. Originally known as the Swagger Specification.

  4. Examples of LRA descriptions used for the evaluation in Sect. 8 can be found at https://github.com/dfserrano/lraeval.

References

  1. Angles R, Gutierrez C (2008) The expressive power of SPARQL. In: The semantic web—ISWC, pp 114–129

  2. Baccar S, Rouached M, Verborgh R, Abid M (2018) Declarative web services composition using proofs. Serv Oriented Comput Appl 12:371–389

    Article  Google Scholar 

  3. Brickley D, Miller L (2012) FOAF vocabulary specification 0.98. Namespace document, vol 9

  4. Brüeckmann T, Gruhn V, Koop W, Ollesch J, Pradel L, Wessling F, Benner M (2017) Codeless engineering of service mashups an experience report. In: Proceedings of the fourteenth IEEE international conference on services computing 2017 (SCC 2017)

  5. Cabral L, Domingue J (2012) Ontology based discovery of semantic web services with IRS-III. Springer, Berlin, pp 191–202

    Google Scholar 

  6. Corson-Rikert J, Mitchell S, Lowe B, Rejack N, Ding Y, Guo C (2012) The VIVO ontology. Synthesis lectures on semantic web: theory and technology, p 3

  7. Dalvi N, Machanavajjhala A, Pang B (2012) An analysis of structured data on the web. Proc VLDB Endow 5(7):680–691

    Article  Google Scholar 

  8. D’Arcus B, Giasson F (2009) Bibliographic ontology specification. http://bibliontology.com/specification

  9. DCMI: DCMI metadata terms

  10. Facebook (2017) GraphQL: a query language for your API. http://graphql.org/

  11. Feier C, Polleres A, Dumitru R, Domingue J, Stollberg M, Fensel D (2005) Towards intelligent web services: the web service modeling ontology (WSMO)

  12. Gallego MA, Fernández JD, Martínez-Prieto MA, de la Fuente P (2011) An empirical study of real-world SPARQL queries. In: USEWOD workshop

  13. García JM, Ruiz D, Ruiz-Cortés A (2012) Improving semantic web services discovery using SPARQL-based repository filtering. Web Semant Sci Serv Agents World Wide Web 17:12–24

    Article  Google Scholar 

  14. Gawinecki M, Cabri G, Paprzycki M, Ganzha M (2010) WSColab: structured collaborative tagging for web service matchmaking. In: WEBIST (1), pp 70–77

  15. Guha RV, Brickley D, Macbeth S (2016) Schema.org: evolution of structured data on the web. Commun ACM 59(2):44–51

    Article  Google Scholar 

  16. Hernández MA, Stolfo SJ (1995) The merge/purge problem for large databases. In: ACM Sigmod record, ACM, vol 24, pp 127–138

  17. Heß A, Johnston E, Kushmerick N (2004) ASSAM: a tool for semi-automatically annotating semantic web services. In: The semantic web—ISWC 2004, Springer, pp 320–334

  18. Heß A, Johnston E, Kushmerick N (2004) Assam: a tool for semi-automatically annotating semantic web services. In: International semantic web conference, Springer, pp 320–334

  19. Hobold G, Siqueira F (2012) Discovery of semantic web services compositions based on SAWSDL annotations. In: International conference on web services (ICWS), IEEE

  20. Huang J, Zhou Y, Duan Q, Xing C (2017) Semantic web service composition in big data environment. In: IEEE global communications conference 2017 (GLOBECOM 2017)

  21. Jaeger MC, Rojec-Goldmann G, Liebetruth C, Mühl G, Geihs K (2005) Ranked matching for service descriptions using OWL-S. In: Kommunikation in Verteilten Systemen (KiVS), Springer, pp 91–102

  22. Järvelin K, Kekäläinen J (2002) Cumulated gain-based evaluation of IR techniques. ACM Trans Inf Syst (TOIS) 20(4):422–446

    Article  Google Scholar 

  23. Klusch M, Fries B, Sycara K (2009) OWLS-MX: a hybrid semantic web service matchmaker for OWL-S services. Web Semant Sci Serv Agents World Wide Web 7(2):121–133

    Article  Google Scholar 

  24. Klusch M, Kapahnke P, Fries B, Khalid MA, Vasileski M (2010) OWLS service retrieval test collection. http://projects.semwebcentral.org/projects/owls-tc/

  25. Kopecky J, Vitvar T, Bournez C, Farrell J (2007) SAWSDL: semantic annotations for WSDL and XML schema. Internet Comput IEEE 11(6):60–67

    Article  Google Scholar 

  26. Küster U (2011) An evaluation methodology and framework for semantic web services technology. Ph.D. thesis, Jena, Univ., Diss., 2010

  27. Kuster U, Konig-Ries B (2007) Semantic service discovery with DIANE service descriptions. In: 2007 IEEE/WIC/ACM international conferences on web intelligence and intelligent agent technology—workshops

  28. Küster U, König-Ries B (2008) Evaluating semantic web service matchmaking effectiveness based on graded relevance. In: Proceedings of the second international conference on service matchmaking and resource retrieval in the semantic web, vol 416, pp 32–46. CEUR-WS. org

  29. Lanthaler M, Gütl C (2013) Hydra: a vocabulary for hypermedia-driven web APIs. In: LDOW

  30. Maleshkova M, Philipp P, Sure-Vetter Y, Studer R (2019) Smart web services (smartws)—the future of services on the web. arXiv:1902.00910

  31. Manning CD, Raghavan P, Schütze H et al (2008) Evaluation in information retrieval. Introduction to information retrieval, vol 1. Cambridge University Press, Cambridge

    Chapter  Google Scholar 

  32. Martin D, Burstein M, Hobbs J, Lassila O, McDermott D et al. (2004) OWL-S: semantic markup for web services. W3C Member Submission, vol 22, p 2007–04

  33. Michel F, Faron-Zucker C, Corby O, Gandon F (2019) Enabling automatic discovery and querying of web APIs at web scale using linked data standards. In: Companion proceedings of the 2019 world wide web conference, ACM, pp 883–892

  34. Michel F, Zucker CF, Gandon F (2018) SPARQL micro-services: lightweight integration of web APIs and linked data. In: LDOW 2018-linked data on the web, pp 1–10

  35. Mouhoub ML, Grigori D, Manouvrier M (2015) LIDSEARCH: a SPARQL-driven framework for searching linked data and semantic web services. In: Gandon F, Guéret C, Villata S, Breslin J, Faron-Zucker C, Zimmermann A (eds) The semantic web: ESWC 2015 satellite events. Springer, Cham

    Google Scholar 

  36. Mouhoub ML, Grigori D, Manouvrier M (2017) Towards an automatic enrichment of semantic web services descriptions. In: OTM confederated international conferences on the move to meaningful internet systems, Springer, pp 681–697

  37. Paolucci M, Kawamura T, Payne TR, Sycara K (2002) Semantic matching of web services capabilities. In: International semantic web conference, Springer, pp 333–347

  38. Patil AA, Oundhakar SA, Sheth AP, Verma K (2004) METEOR-S web service annotation framework. In: International conference on World Wide Web, ACM

  39. Pérez J, Arenas M, Gutierrez C (2009) Semantics and complexity of SPARQL. ACM Trans Database Syst (TODS) 34(3):16

    Article  Google Scholar 

  40. Petrie CJ, Margaria T, Lausen H, Zaremba M (2008) Semantic web services challenge: results from the first year, vol 8. Springer, Berlin

    Google Scholar 

  41. Rietveld L, Verborgh R, Beek W, Vander Sande M, Schlobach S (2015) Linked data-as-a-service: the semantic web redeployed. In: European semantic web conference, Springer, pp 471–487

  42. Rijsbergen CJV (1979) Information retrieval, 2nd edn. Butterworth-Heinemann, Newton

    MATH  Google Scholar 

  43. Rodriguez-Mier P, Pedrinaci C, Lama M, Mucientes M (2016) An integrated semantic web service discovery and composition framework. IEEE Trans Serv Comput 9(4):537–550

    Article  Google Scholar 

  44. Roman D, Kopeckỳ J, Vitvar T, Domingue J, Fensel D (2015) WSMO-Lite and hRESTS: lightweight semantic annotations for web services and RESTful APIs. Web Semant Sci Serv Agents World Wide Web 31:39–58

    Article  Google Scholar 

  45. Rosenthal R, Rosnow RL (2008) Essentials of behavioral research: methods and data analysis, vol 3. McGraw-Hill, New York

    Google Scholar 

  46. Schmachtenberg M, Bizer C, Paulheim H (2014) State of the LOD cloud 2014. University of Mannheim, Data and Web Science Group [en ligne], vol 30

  47. Serrano D, Stroulia E, Lau D, Ng T (2017) Linked REST APIs: a middleware for semantic REST API. In: IEEE international conference on web services 2017 (ICWS 2017)

  48. Speiser S, Harth A (2011) Integrating linked data and services with linked data services. In: The semantic web: research and applications, Springer

  49. Taheriyan M, Knoblock CA, Szekely P, Ambite JL (2012) Rapidly integrating services into the linked data cloud. In: ISWC 2012, Springer, pp 559–574

  50. Tomaszuk D (2016) Inference rules for RDF(S) and OWL in N3Logic. arXiv:1601.02650

  51. Tsetsos V, Anagnostopoulos C, Hadjiefthymiades S (2006) On the evaluation of semantic web service matchmaking systems. In: 4th European conference on web services, 2006. ECOWS’06, IEEE, pp 255–264

  52. Ullmann JR (1976) An algorithm for subgraph isomorphism. J ACM (JACM) 23(1):31–42

    Article  MathSciNet  Google Scholar 

  53. Verborgh R, Steiner T, Van Deursen D, Van  de Walle R, Vallés JG (2011) Efficient runtime service discovery and consumption with hyperlinked RESTdesc. In: 2011 7th international conference on next generation web services practices (nwesp), IEEE, pp 373–379

  54. Wei D, Wang T, Wang J, Bernstein A (2011) SAWSDL-iMatcher: a customizable and effective semantic web service matchmaker. Web Semant Sci Serv Agents World Wide Web 9(4):402–417

    Article  Google Scholar 

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Acknowledgements

This work was financially supported by Natural Sciences and Engineering Research Council.

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Authors and Affiliations

  1. Department of Computing Science, University of Alberta, 2-32 Athabasca Hall, Edmonton, Canada

    Diego Serrano & Eleni Stroulia

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  1. Diego Serrano
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  2. Eleni Stroulia
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Correspondence to Eleni Stroulia.

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Serrano, D., Stroulia, E. Semantics-based API discovery, matching and composition with linked metadata. SOCA 14, 283–296 (2020). https://doi.org/10.1007/s11761-020-00301-1

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