TY - JOUR
T1 - Using OODB modeling to partition a vocabulary into structurally and semantically uniform concept groups
AU - Liu, Li Min
AU - Halper, Michael
AU - Geller, James
AU - Perl, Yehoshua
N1 - Funding Information:
This research was (partially) done under a cooperative agreement between the US National Institute of Standards and Technology Advanced Technology Program (under the HIIT contract #70NANB5H1011) and the Healthcare Open Systems and Trials, Inc., consortium. This research was also partially supported by two grants from the New Jersey Commission for Science and Technology, one from the New Jersey Center for Software Engineering and the other from the Multi-lifecycle Engineering Research Center.
PY - 2002/7
Y1 - 2002/7
N2 - Controlled Vocabularies (CVs) are networks of concepts that unify disparate terminologies and facilitate the process of information sharing within an application domain. We describe a general methodology for representing an existing CV as an object-oriented database (OODB), called an Object-Oriented Vocabulary Repository (OOVR). A formal description of the OOVR methodology, which is based on a structural abstraction technique, is given, along with an algorithmic description and a number of theorems pertaining to some of the methodology's formal characteristics. An OOVR offers a two-level view of a CV, with the schema-level view serving as an important abstraction that can aid in orientation to the CV's contents. While an OOVR can also assist in traversals of the CV, we have identified certain special CV configurations where such traversals can be problematic. To address this, we introduce-based on the original methodology-an enhanced OOVR methodology that utilizes both structural and semantic features to partition and model a CV's constituent concepts. With its basis in the notions of area and the recursively defined articulation concept, an enhanced OOVR representation provides users with an improved CV view comprising groups of concepts uniform both in their structure and semantics. An algorithmic description of the singly rooted OOVR methodology and theorems describing some of its formal properties are given. The results of applying it to a large existing CV are discussed.
AB - Controlled Vocabularies (CVs) are networks of concepts that unify disparate terminologies and facilitate the process of information sharing within an application domain. We describe a general methodology for representing an existing CV as an object-oriented database (OODB), called an Object-Oriented Vocabulary Repository (OOVR). A formal description of the OOVR methodology, which is based on a structural abstraction technique, is given, along with an algorithmic description and a number of theorems pertaining to some of the methodology's formal characteristics. An OOVR offers a two-level view of a CV, with the schema-level view serving as an important abstraction that can aid in orientation to the CV's contents. While an OOVR can also assist in traversals of the CV, we have identified certain special CV configurations where such traversals can be problematic. To address this, we introduce-based on the original methodology-an enhanced OOVR methodology that utilizes both structural and semantic features to partition and model a CV's constituent concepts. With its basis in the notions of area and the recursively defined articulation concept, an enhanced OOVR representation provides users with an improved CV view comprising groups of concepts uniform both in their structure and semantics. An algorithmic description of the singly rooted OOVR methodology and theorems describing some of its formal properties are given. The results of applying it to a large existing CV are discussed.
KW - Database models
KW - Knowledge representation
KW - Object-oriented databases
KW - Object-oriented models
KW - Object-oriented systems
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U2 - 10.1109/TKDE.2002.1019218
DO - 10.1109/TKDE.2002.1019218
M3 - Article
AN - SCOPUS:0036648680
SN - 1041-4347
VL - 14
SP - 850
EP - 866
JO - IEEE Transactions on Knowledge and Data Engineering
JF - IEEE Transactions on Knowledge and Data Engineering
IS - 4
ER -