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Exploiting Natural Language Definitions and (Legacy) Data for Facilitating Agreement Processes.


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Debruyne, C. and Vasquez, C. (2013) Exploiting Natural Language Definitions and (Legacy) Data for Facilitating Agreement Processes. In Proc. of Software Quality. Increasing Value in Software and Systems Development 2013 (SWQD 2013), LNBIP, Springer

In IT, ontologies to enable semantic interoperability is only of the branches in which agreement between a heterogeneous group of stakeholders are of vital importance. As agreements are the result of interactions, appropriate methods should take into account the natural language used by the community. In this paper, we extend a method for reaching a consensus on a conceptualization within a community of stakeholders, exploiting the natural language communication between the stakeholders. We describe how agreements on informal and formal descriptions are complementary and interplay. To this end, we introduce, describe and motivate the nature of some of the agreements and the two distinct levels of commitment. We furthermore show how these commitments can be exploited to steer the agreement processes. Concepts introduced in this paper have been implemented in a tool for collaborative ontology engineering, called GOSPL, which can be also adopted for other purposes, e.g., the construction a lexicon for larger software projects.

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Exploiting Natural Language Definitions and (Legacy) Data for Facilitating Agreement Processes.

  1. 1. Exploiting Natural LanguageDefinitions and (Legacy) Data forFacilitating Agreement ProcessesChristophe Debruyne and Cristian VasquezPresented @ SWQD 2013, January 2013
  2. 2. Introduction• Agreements within a heterogeneous group of stakeholders are vitalfor many domains in IT• Contribution• Presentation of a framework and method• Formal representations grounded in natural language• Informal representations• “There is no entity without identify” (Quine) – Reference structures• Proposal of a layered architecture for such agreements• Nature of different agreements• Exploitation of the layered approach• Exploitation of the natural language aspect for retrieving information• Presentation of the tools implementing proposed ideas• Applied in Ontology Engineering, but fear not …
  3. 3. Introduction• Ontologies• Shared, formal specifications of a domain• Key for semantic interoperability between autonomouslydeveloped information systems• Constitutes a community• The result of social interactions within a community leading toagreements• Ontology-engineering• Sets of guidelines and activities constituting a method forbuilding such ontologies
  4. 4. Hybrid Ontology Engineering• DOGMA Hybrid Ontology Descriptions <Ω, ci, K, G>• Ω a lexon base, a finite set of plausible binary fact types calledlexons, e.g., <Vendor Community, Offer, has, is of, Title>• ci a function mapping community-identifiers and terms toconcepts• K a finite set of ontological commitments containing• A selection of lexons• A mapping from application symbols to ontology terms• Predicates over those terms and roles to express constraints• G is a glossary, a triple with components• Gloss, a set of linguistic, human-interpretable glosses• g1, mapping community-term pairs to glosses• g2, mapping lexons to glosses⟨VCard Community, Email Address⟩  “The addressof an email, a system of world-wide electroniccommunication in which a user can compose amessage at one terminal that can be regeneratedat the recipient’s terminal when the recipient logsin”
  5. 5. Hybrid Ontology Engineering• Example of an application-commitment• Ω-RIDL: Verheyden et al. (SWDB 2004),Trog et al. (RuleML 2007)
  6. 6. Hybrid Ontology Engineering• Grounding ontologies with social processes & NL• Hybrid Ontology Engineering Method
  7. 7. (1) Nature of Agreements• Gloss-equivalence:• Two communities c1 and c2 consider that the glosses they usedto describe their terms – t1 and t2 respectively – refer to thesame concept  EQG(g1(c1,t1),g1(c2,t2))• Synonymy:• Two communities c1 and c2 consider that the labels they used inthe formal descriptions (lexons) refer to the same concept ci(c1,t1) ≣C ci(c2,t2)• Gloss-equivalence and synonymy only an equivalence-relationwithin one agreements process!
  8. 8. (1) Nature of Agreements• Why this distinction?• Glossary-consistency principle: for every two community-termpairs: if the glosses of those terms were deemed to refer to thesame concept (gloss-equivalence), then so should the term-labels(synonymy).• Motivation 1: Separate processes for each type of agreements• Synonymy requires terms already to be present in a lexon• Motivation 2: Glossary-consistency principle used a means fordriving agreements• Revalidation by the community (/communities)
  9. 9. (2) Layered Commitments• Distinction between community-commitment andapplication-commitments• Community-commitment: engagement by the community tocomply with this set of fact types and knowledge• Application-commitment: a selection of community-commitment + additional fact types and constraints forannotating data sources
  10. 10. (3) Exploiting commitments• Hybrid ontology easily translated into other formalisms• E.g. OWL, UML, etc.• Services set up with translation• Natural language interface for annotated data via lexons• LIST Artist NOT with Gender with Code = ‘M’• SELECT DISTINCT ?a WHERE { ?a a myOnto0:Artist.OPTIONAL { ?g myOnto0:Gender_of_Artist ?a.?g myOnto0:Gender_with_Code ?c. }FILTER(?c != "M" || !bound(?c)) }• Object Role Modeling “like” subtype definitions
  11. 11. Tool
  12. 12. Experiment• Experiment in the cultural domain• within the context of a linked data project in Brussels• Selection of terms (at the time of writing)• Non-lexical• At least four interactions involving this term• Appearing in a lexon• Terms were more likely to change in their formal descriptionof the natural language definitions were not provided first• Indeed, freedom was given to the users concerning this aspect
  13. 13. Experiment• We noticed that terms used for attributes were less likely tobe fully articulated• Either the process of teaching the method needs to stress theimportance of such alignment (e.g., encoding)• Tool should encourage the users in articulating all concepts
  14. 14. Conclusions• Importance of agreements• Extended a framework for hybrid ontology engineering• (1) Describing the nature of agreements• (2) Proposing a layered architecture• (3) Exploitation of commitments• Ideas were integrated in a tool• Experiment• Future work• Encouraging users to fully follow the method• Reasoning on the commitments
  15. 15. Thank you!Any questions?
  16. 16. Example of commitments• Community-commitment• A relational DB
  17. 17. BEGIN SELECTION[Cultural Domain’]<MyOrganization, Work Of Art, with, of, WID>END SELECTIONBEGIN CONSTRAINTSLINK(Cultural Domain, Artist, MyOrganization, Artist).LINK(Cultural Domain, Work Of Art, MyOrganization, Work Of Art).EACH Artist with AT MOST 1 AID.EACH Artist with AT LEAST 1 AID.EACH AID of AT MOST 1 Artist.EACH Work Of Art with AT MOST 1 WID.EACH Work Of Art with AT LEAST 1 WID.EACH WID of AT MOST 1 Work Of Art.END CONSTRAINTSBEGIN MAPPINGSMAP ON Name of Artist.MAP Artist.birthyear ON Year of birth of Artist.MAP ON AID of Artist.MAP ON Title of Work Of Art.MAP piece.year ON Year of Work Of Art.MAP ON WID of Work Of Art.MAP artistpiece.a_id ON AID of Artist contributed to Work Of Art.MAP artistpiece.p_id ON WID of Work Of Art with contributor Artist.END MAPPINGS
  18. 18. Tool: Example of a “scenario”