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Towards a Project Centric Metadata Model and Lifecycle for Ontology Mapping Governance

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Christophe Debruyne, Brian Walshe, Declan O'Sullivan: Towards a Project Centric Metadata Model and Lifecycle for Ontology Mapping Governance. Paper presented at iiWAS 2015 on the 13th of December 2015, Brussels, Belgium.

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Towards a Project Centric Metadata Model and Lifecycle for Ontology Mapping Governance

  1. 1. Towards a Project Centric Metadata Model and Lifecycle for Ontology Mapping Governance Christophe Debruyne, Brian Walshe and Declan O’Sullivan ADAPT Centre, Trinity College Dublin The ADAPT Centre is funded under the SFI Research Centres Programme (Grant 13/RC/2106) and is co-funded under the European Regional Development Fund.
  2. 2. www.adaptcentre.ieContext •  Seman@c heterogeneity on the Linked Data Web. How can this problem be tackled? With ontology matching and mapping. •  Ontology Matching: detec@ng the correspondences that cons@tute an alignment. •  Ontology Mapping: interpre@ng these correspondences to create an executable mapping (wrt requirements) Image from Shvaiko and Euzenat’s "Ontology Matching: State of the Art and Future Challenges", IEEE Transac@ons on Knowledge & Data Engineering, vol.25, no. 1, pp. 158-176, Jan. 2013.
  3. 3. www.adaptcentre.ieContext •  Though the field of ontology matching and mapping is around for over a decade, Euzenat and Shvaiko iden@fied several challenges that s@ll have to be tackled (2013). •  Infrastructure and support for ontology alignment management: “[t]he challenge is to provide convenient and interoperable support, on which tools and, more importantly, on which applica@ons, can rely in order to store and share alignments. This involves using standard ways to communicate alignments and retrieve them. Hence alignment metadata and annota@ons should be properly taken into account.” •  But…
  4. 4. www.adaptcentre.ieProblem •  Management ac@vi@es are artefact-centric and concerned with storing and sharing. Related work is ofen limited to (annota@ons of) produced ar@facts. •  We argue a project-centric approach should be adopted. •  Mappings are created for a purpose •  Progress is the result of agreement processes between the community of stakeholders •  Generate metadata as the project progresses •  Not only formulate queries about alignment, mappings, AND projects: “What are the most debated aspects in a par@cular ontology mapping project?”
  5. 5. www.adaptcentre.ieRelated work Ontology Mapping Metadata [AF, EDEOL, OM2R, …] •  Focuses on represen@ng alignments or designed to facilitate discovery and reuse. •  Metadata models inappropriately represent the domain; for instance, “requirements are part of a mapping project” and “a mapping project results in a mapping” instead of “requirements are part of a mapping”. Ontology Mapping Lifecycles [OISIN, Thomas et al, …] •  Likle related work. •  Artefact-centric and most contain no feedback loop. •  Reuse, sharing and publica@on of alignments (or mappings) are considered separate ac@vi@es not integrated in a mapping’s lifecycle or workflow. Provenance informaMon of generated data via mappings •  Not covered in this presenta@on.
  6. 6. www.adaptcentre.ieRelated work Provenance •  Provides insights on a resource’s origin, such as who created it, when it was modified or how it was created (Zhao & Har@g, 2012). •  Some ini@a@ves exist to capture provenance informa@on (in part also covered by ontology mapping metadata vocabularies). But, PROV-O – a W3C Recommenda@on – is an important resource. Core concepts and rela@ons in PROV-O, Copyright © 2011-2013 W3C® (MIT, ERCIM, Keio, Beihang).
  7. 7. www.adaptcentre.ieApproach Our proposed approach •  Adopt a project-centric view that •  takes into account all mapping project phases and •  adequately records the ac@vi@es by the stakeholders •  resul@ng in a traceable and transparent process. •  Many more artefacts can be related to mapping projects, including scopes, requirements, decisions, discussions, etc. •  How? 1.  Propose an ontology mapping lifecycle 2.  Propose an ontology mapping metadata model 3.  Elaborate on ontology mapping governance ac@vi@es
  8. 8. www.adaptcentre.ieOntology Mapping Lifecycle ReuseCharacterizationStaging Scope Data Discovery Requirements Analysis Data Analysis Discover Evaluate Reuse? Matching Evaluate Execute Plan No Align and Map Create Alignment Prepare Render Mapping Application Yes Source Data Target Data Candidate Correspondences Alignments Mapping Stakeholders Staging Need for communi@es CharacterizaMon Analyze ontologies wrt to scope and requirements Reuse Par@al or complete reuse? Matching Discovering correspondences Mapping Refine correspondences for alignment and create mapping ApplicaMon Monitor mappings
  9. 9. www.adaptcentre.ieOntology Mapping Metadata Model Ontology Mapping Metadata Model •  First conceptualized with Object Role Modelling. •  In this paper and presenta@on, we adopted a “UML-like” graphical presenta@on. •  The ontology adopts PROV-O and is available as an OWL 2 ontology. hkps://raw.githubusercontent.com/CNGL-repo/mapping- provenance-published/master/mapping-provenance.owl
  10. 10. www.adaptcentre.ieOntology Mapping Metadata Model OR rdfs:subClassOf 0..1 prov:wasInformedBy 1..1 mg:Ontology Analysis 0..* prov:used 1..1 mg:Evaluation mg:Plan mg:Requirement mg:Reuse Evaluation mg:Matcher Configuration 1..* prov:generated 1..* 0..* prov:used 1..* prov:Entity mg:Matcher 0..* mg:withMatcher 1..1 prov:SoftwareAgent rdfs:subClassOf mg:Reuse 0..* prov:used 1..1 xsd:string 0..* mg:withParameter 1..1 mg:Resource 0..* mg:withResource 1..1 rdfs:subClassOf Planning the matching phase
  11. 11. www.adaptcentre.ieMapping Governance •  Data Governance is defined as “a control that ensures that the data entry […] meets precise standards, such as […] data integrity constraints in the data model. The data governor uses data quality monitoring […] to communicate errors in data […]” (Wikipedia) •  OWL 2 is good for publishing data on the LD Web and adopts the Open World Assump@on. However, our platorm would need to adopt a close(r) world assump@on as to meet our constraints. •  For our tools, this is covered by our database schema and applica@on logic. •  What if data comes from elsewhere?
  12. 12. www.adaptcentre.ieMapping Governance •  Because of the OWA, OWL axioms do not work. •  We thus adopt an approach proposed by Tao et al. (2010), where basically constraints are translated into SPARQL SELECT or ASK queries to detect problems !"#$% ⊓ ¬ 1!"#ℎ! . !"#$%&' ⊑⊥ ∃!"#ℎ. !ℎ!"!#$%"&'% ⊓ ¬ ∃!"#ℎ. !"#$% ⊑⊥ ASK WHERE { ?s a mg:Stage. NOT EXISTS { ?project mg:with ?s. } } ASK WHERE { ?p a mg:Project. ?p mg:with ?c. ?c a mg:Characterize. NOT EXISTS { ?p mg:with ?s. ?s a mg:Stage. } }
  13. 13. www.adaptcentre.ieConclusions and Future Work Conclusions •  Crea@on and management of ontology mappings is far from trivial. Metadata models focus on the representa@on of artefacts, on the support for discovery and reuse and are of limited expressivity. •  We proposed a new ontology mapping lifecycle and metadata model that adopts a project- centric view and relates artefacts, stakeholders and an ontology mapping project. Facilita@ng mapping governance. Future Work •  Build tool support for the method and gather data for evalua@on. •  Structure the discussions, adop@ng SIOC and IBIS •  Leverage user involvement of the mul@ple different stakeholders (Ramy et al., 2015) •  Adopt the Design Intent Ontology (Solanki, 2015), which is an Ontology Design Pakern to structure and “reason” over the requirements.
  14. 14. www.adaptcentre.ieReferences T. R. Gruber. Toward principles for the design of ontologies used for knowledge sharing? Int. J. Hum.- Comput. Stud., 43(5-6):907–928, 1995. R. Shosha, C. Debruyne, and D. O’Sullivan. Towards an adap@ve tool and method for collabora@ve ontology map-ping. In I. Ciuciu, H. Paneko, C. Debruyne, A. Aubry, P. Bollen, R. Valencia-Garcia, A. Mishra, A. Fensel, and F. Ferri, editors, On the Move to Meaningful Internet Systems: OTM 2015 Workshops, volume 9416 of Lecture Notes in Computer Science, pages 319–328. Springer, 2015. P. Shvaiko and J. Euzenat. Ontology matching: State of the art and future challenges. IEEE Trans. Knowl. Data Eng., 25(1):158–176, 2013. M. Solanki. DIO: A pakern for capturing the intents underlying designs. In E. Blomqvist, P. Hitzler, A. Krisnadhi, T. Narock, and M. Solanki, editors, Proceedings of the 6th Workshop on Ontology and Seman@c Web Pakerns (WOP 2015) co-located with the 14th Interna@onal Seman@c Web Conference (ISWC 2015), Bethlehem, Pensylvania, USA, October 11, 2015, volume 1461 of CEUR Workshop Proceed-ings. CEUR-WS.org, 2015. J. Tao, E. Sirin, J. Bao, and D. L. McGuinness. Extending OWL with integrity constraints. In V. Haarslev, D. Toman, and G. E. Weddell, eds, Proceedings of the 23rd Interna@onal Workshop on Descrip@on Logics (DL 2010), Waterloo, Ontario, Canada, May 4-7, 2010, volume 573 of CEUR Workshop Proceedings. CEUR-WS.org, 2010. H. Thomas, R. Brennan, and D. O’Sullivan. Using the OM2R meta-data model for ontology mapping reuse for the ontology alignment challenge - a case study. In P. Shvaiko, J. Euzenat, A. Kementsietsidis, M. Mao, N. F. Noy, and H. Stuckenschmidt, eds, Proceedings of the 7th Interna@onal Workshop on Ontology Matching, Boston, MA, USA, November 11, 2012, volume 946 of CEUR Workshop Proceedings. CEUR-WS.org, 2012. J. Zhao and O. Har@g. Towards interoperable provenance publica@on on the linked data web. In C. Bizer, T. Heath, T. Berners-Lee, and M. Hausenblas, eds, WWW2012 Workshop on Linked Data on the Web, Lyon, France, 16 April, 2012, volume 937 of CEUR Workshop Proceedings. CEUR-WS.org, 2012.

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