A Methodological Framework for Ontology and Multilingual Termontological Database Co-evolution C. Debruyne, C. Vasquez, K. Kerremans, and A.D. Burgos LNCS 7567, p. 220 ff. Ontologies and Multilingual Termontology Bases (MTB) are two knowledge artifacts with different characteristics and different purposes. Ontologies are used to formally capture a shared view of the world to solve particular interoperability and reasoning tasks. MTBs are general, contain fewer types of relations and their purposes are to relate several term labels within and across different languages to cat- egories. For regions in which the multilingual aspect is vital, not only does one need an ontology for interoperability, the concepts in that ontology need to be comprehensible for everyone whose native tongue is one of the principal languages of that region. Multilinguality pro- vides also a powerful mechanism to perform ontology mapping, con- tent annotation, multilingual querying, etc. We intend to meet these challenges by linking both methods for constructing ontologies and MTBs, creating a virtuous cycle. In this paper, we present our method and tool for ontology and MTB co-evolution.

1. A METHODOLOGICAL
FRAMEWORK FOR ONTOLOGY
AND MULTILINGUAL
TERMONTOLOGICAL DATABASE
CO-EVOLUTION
CHRISTOPHE DEBRUYNE
CRISTIAN VÁSQUEZ
KOEN KERREMANS
ANDRÉS DOMÍNGUEZ BURGOS

2. INTRODUCTION
Ontologies. Computer-based, shared, agreed, formal
conceptualizations for – amongst others – semantic
interoperability between autonomously developed and
maintained information systems.
Multilingual Terminology Bases (MTBs) are language
resources that contain - in several languages - terms
(including variants) referring to concepts in specialized
domains. Several other types of information can be added to
MTBs in order to describe specific properties of a term, its
meaning or its use in specific communicative contexts.
Ontologies are meant for a specific purpose whereas MTBs
are more general purpose

3. PROBLEM
Ontologies and MTBs have different purposes. How and what
are the benefits of combining these two artifacts and their
methods of construction?
At two levels
• Level of the respective artifacts
• Level of the construction methods

4. METHOD: ONTOLOGY
ENGINEERING
Hybrid Ontology Engineering
• Method  Grounding Ontologies in Social Processes and
Natural Language (GOSPL)
• Community grounded agreements on formal and informal
concept descriptions
• Formal descriptions by means of fact-orientation
• Informal descriptions by means of an artifact called glossary

5. METHOD: TERMINOLOGY
ENGINEERING
Multilingual Termontological Database
• MTB in which some ontological relations are made explicit
• Hierarchical relationships as well as non-hierarchical (*)
• Method  Termontography
• Explicitly distinguishes the linguistic level from the
semantic level

6. METHOD:
HYBRID ONTOLOGY &
MTB CO-EVOLUTION
Propose related terms, synonyms,
existing descriptions, ...
Interaction

Organized Community
(re-internalize)
GOSPL Knowledge
Management
External
(un)structured
data
Platform
"World" Hybrid
externalize
Text Multilingual
Ontology Miner Terminology
Base
implemented TermontoPlatform
ontology
Agreed upon glosses,
terms (and interrelations),
RDF(S)
synonyms, ... OWL
...

7. METHOD:
HYBRID ONTOLOGY &
MTB CO-EVOLUTION
From MTB to Hybrid Ontology
• Retrieval of generic “pre-fact types”
• Retrieval of informal descriptions
From Hybrid Ontology to MTB
• Social interactions lead the mining process
• Alignment with the hybrid ontology enables natural
language querying
• Structuring the query with NLP, generating a first structure
then annotated with the ontology

8. TOOL
First, eating our own dog food: creation of an MTB
(termontography) ontology
Annotation of the MTB to expose data as RDF
• Creation of a SPARQL endpoint
Connection GOSPL Tool with endpoint

9. TOOL

10. USE CASE
Used in the context of the cultural domain
• Retrieval of information on cultural events in Brussels
• Three languages: NL, FR, EN
• Motivation of Multilingual Termontological Databases
• Different data sources motivate the need of Ω
• Application
• Natural language querying. Query is first parsed to a
structure, and alignment with Ω facilitates the translation of
that structure into query
• Multilingual interfaces
• User comprehension of the results

11. CONCLUSIONS
Conclusions
• Ontologies and MTBs are two different artifacts, with distinct
construction processes
• We examined how these two processes and artifacts can be
combined and presented a proposal
• Ideas were implemented in a tool, which will be part of a
greater set up
• Used the tool in the context of a project in the cultural domain.
Future work
• Implementation and integration of the natural language
query interface
• More testing and user evaluation

12. THANK
YOU!
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