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. Exploiting Natural Language
Definitions and (Legacy) Data for
Facilitating Agreement Processes
Christophe Debruyne and Cristian Vasquez
Presented @ SWQD 2013, January 2013
2. Introduction
• Agreements within a heterogeneous group of stakeholders are vital
for 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. Introduction
• Ontologies
• Shared, formal specifications of a domain
• Key for semantic interoperability between autonomously
developed information systems
• Constitutes a community
• The result of social interactions within a community leading to
agreements
• Ontology-engineering
• Sets of guidelines and activities constituting a method for
building such ontologies
4. Hybrid Ontology Engineering
• DOGMA Hybrid Ontology Descriptions <Ω, ci, K, G>
• Ω a lexon base, a finite set of plausible binary fact types called
lexons, e.g., <Vendor Community, Offer, has, is of, Title>
• ci a function mapping community-identifiers and terms to
concepts
• 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 address
of an email, a system of world-wide electronic
communication in which a user can compose a
message at one terminal that can be regenerated
at the recipient’s terminal when the recipient logs
in”
5. Hybrid Ontology Engineering
• Example of an application-commitment
• Ω-RIDL: Verheyden et al. (SWDB 2004),
Trog et al. (RuleML 2007)
7. (1) Nature of Agreements
• Gloss-equivalence:
• Two communities c1 and c2 consider that the glosses they used
to describe their terms – t1 and t2 respectively – refer to the
same concept EQG(g1(c1,t1),g1(c2,t2))
• Synonymy:
• Two communities c1 and c2 consider that the labels they used in
the formal descriptions (lexons) refer to the same concept
ci(c1,t1) ≣C ci(c2,t2)
• Gloss-equivalence and synonymy only an equivalence-relation
within one agreements process!
8. (1) Nature of Agreements
• Why this distinction?
• Glossary-consistency principle: for every two community-term
pairs: if the glosses of those terms were deemed to refer to the
same 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 for
driving agreements
• Revalidation by the community (/communities)
9. (2) Layered Commitments
• Distinction between community-commitment and
application-commitments
• Community-commitment: engagement by the community to
comply with this set of fact types and knowledge
• Application-commitment: a selection of community-
commitment + additional fact types and constraints for
annotating data sources
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
12. Experiment
• Experiment in the cultural domain
• within the context of a linked data project in Brussels
http://www.oscb.be/
• 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 description
of the natural language definitions were not provided first
• Indeed, freedom was given to the users concerning this aspect
13. Experiment
• We noticed that terms used for attributes were less likely to
be fully articulated
• Either the process of teaching the method needs to stress the
importance of such alignment (e.g., encoding)
• Tool should encourage the users in articulating all concepts
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
18. BEGIN SELECTION
['Cultural Domain’]
<'MyOrganization', Work Of Art, with, of, WID>
END SELECTION
BEGIN CONSTRAINTS
LINK('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 CONSTRAINTS
BEGIN MAPPINGS
MAP 'Artist'.'name' ON Name of Artist.
MAP 'Artist'.'birthyear' ON Year of birth of Artist.
MAP 'Artist'.'id' ON AID of Artist.
MAP 'piece'.'name' ON Title of Work Of Art.
MAP 'piece'.'year' ON Year of Work Of Art.
MAP 'piece'.'id' 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
The hybrid aspect of ontologiesOntologies are resources shared among humans working in a community, and (networked) systemsMapping of terms to a concept is the result of a community agreementCapture those agreements, turn comunities into first class citizens of the ontology, resulting notion called hybrid ontologyFundamental technology: formalized glossaries, special linguistic resources to support the agreement processUse of structured NLVehicle to elicit useful and relevant concepts from community communicationMapping of these social processes to evolutionary process of the emerging ontologyIn conceptualizations, rigorously separate facts from all application specific interpretationsInterpretations are performed by constraining the mapping between application systems and the fact base of the ontology