Yan Chen, Yehoshua Perl, James Geller, and James J. Cimino. Analysis of a Study of the Users, Uses and Future Agenda of the UMLS. To appear on Journal of the American Medical Informatics Association. 2006 Dec.

Abstract: Objective: The UMLS constitutes the largest existing collection of medical terms. However, little has been published about the users and uses of the UMLS. This study sheds lights on these issues.
Design: We designed a questionnaire consisting of 26 questions and distributed it to the UMLS user mailing list. Participants were assured complete confidentiality of their replies. To further encourage list members to respond, we promised to provide them with early results prior to publication. Sector analysis of the responses, according to employment organizations is used to obtain insights into some responses.
Result: We received 70 responses. The study confirms two intended uses of the UMLS, access to source terminologies (75%) and mapping among them (44%). However, most access is just to a few sources, led by SNOMED, MeSH and ICD. Out of 119 reported purposes of use, terminology research (37), information retrieval (19), and terminology translation (14) lead. Four important observations are that the UMLS is widely used as a terminology (77%), even though it was not designed as one; many users (73%) want the NLM to mark concepts with multiple parents in an indented hierarchy and to derive a terminology from the UMLS (73%). Finally, auditing the UMLS is a top budget priority (35%) for users.
Conclusion: The study reports many uses of the UMLS in a variety of subjects from terminology research to decision support and phenotyping. The study confirms that the UMLS is used to access its source terminologies and to map among them. Two primary concerns of the existing user base are auditing the UMLS and the design of a UMLS-based derived terminology.

Yue Wang, Michael Halper, Hua Min, Yehoshua Perl, Yan Chen, Kent A. Spackman. Structural Methodologies for Auditing SNOMED. Pending after revision and Journal of Biomedical Informatics.

Abstract: SNOMED is one of the leading health care terminologies being used worldwide. As such, quality assurance is an important part of its maintenance cycle. Methodologies for auditing SNOMED based on structural aspects of its organization are presented. In particular, automated techniques for partitioning SNOMED into smaller groups of concepts based primarily on relationships patterns are defined. Two abstraction networks, the area taxonomy and p-area taxonomy, are derived from the partitions. The highlevel views afforded by these abstraction networks form the basis for systematic auditing. The networks tend to highlight errors that manifest themselves as irregularities at the abstract level. They also support group-based auditing, where sets of purportedly similar concepts are focused on for review. The auditing methodologies are demonstrated on one of SNOMED top-level hierarchies. Errors discovered during the auditing process are reported.

Min H, Perl Y, Chen Y, Halper M, Geller J, Wang Yue. Auditing as part of the Terminology Design Life Cycle. To appear on J Am Med Inform Assoc. 2006 Nov.

Abstract: Objective: To develop and test an auditing methodology for detecting errors in medical terminologies satisfying systematic inheritance. This methodology is based on various abstraction taxonomies that provide high-level views of a terminology and highlight potentially erroneous concepts.

Abstract: Objective: The Enriched Semantic Network (ESN) was introduced as an extension of the Unified Medical Language System (UMLS) Semantic Network (SN). Its multiple subsumption configuration and concomitant multiple inheritance make the ESN's relationship structures and semantic type assignments different from those of the SN. A technique for deriving the relationship structures of the ESN's semantic types and an automated technique for deriving the ESN's semantic type assignments from those of the SN are presented.

Abstract:Objective: A metaschema is an abstraction network of the UMLS’s Semantic Network (SN) obtained from a connected partition of its collection of semantic types. A lexical metaschema was previously derived based on a lexical partition which partitioned the SN into semantictype groups using identical word-usage among the names of semantic types and the definitions of their respective children. In this paper, a statistical analysis methodology is presented to evaluate the lexical metaschema based on a study involving a group of established UMLS experts.
Design: In the study, each expert was asked to identify subject areas of the SN based on his or her understanding of the various semantic types. For this purpose, the expert scans the SN
hierarchy top-down, identifying semantic types, which are important and different enough
from their parent semantic types, as roots of their groups. From the response of each expert,
an “expert metaschema” is constructed. The different experts’ metaschemas can vary widely.
So, additional metaschemas are obtained from aggregations of the experts’ responses. Of
special interest is the consensus metaschema which represents an aggregation of a simple
majority of the experts’ responses. Statistical analysis comparing the lexical metaschema
with the experts’ metaschemas and the consensus metaschema is presented.
Results: The analysis results shows that 17 out of the 21 meta-semantic types in the lexical metaschema also appear in the consensus metaschema (about 81%). There are 107 (about 79%) semantic types covered by identical meta-semantic types and refinements. The results show the high similarity between the two metaschemas. Furthermore, the statistical analysis shows that the lexical metaschema did not grossly underperform compared to the experts.
Conclusion: Our study shows that the lexical metaschema provides a good approximation for
a partition of meaningful subject areas in the SN, when compared to the consensus metaschema capturing the aggregation of a simple majority of the human experts’ opinions.

Abstract: Objective: A metaschema is a high-level abstraction network of the UMLS Semantic Network (SN) obtained from a partition of the SN collection of semantic types. Every metaschema has nodes, called meta-semantic types, each of which denotes a group of semantic types constituting a subject area of the SN. A new kind of metaschema, called the lexical metaschema, is derived from a lexical partition of the SN. The lexical metaschema is compared to previously derived metaschemas, e.g., the cohesive metaschema.

Abstract: The Unified Medical Language System (UMLS) integrates about 880,000 concepts from 100 biomedical terminologies. Each concept is categorized to at least one semantic type of the Semantic Network. During the integration, it is unavoidable that some categorization errors and inconsistencies will be introduced. In this paper, we present an auditing technique to find such errors and inconsistencies. Our technique is based on an expert reviewing the pure intersections of meta-semantic types of a metaschema, a compact abstract view of the UMLS Semantic Network. We use a divide and conquer approach, handling differently small pure intersections and medium to large pure intersections. By using this approach, we limit the number of concepts reviewed, for which we expect a high percentage of errors. We reviewed all concepts in 657 pure intersections containing one to 10 concepts. Various kinds of errors are identified and the analysis of the results are presented in the paper. Also, we checked the pure intersections containing more than 10 concepts for their semantic soundness, where the semantically suspicious pure intersections are presented in the paper and their concepts are reviewed.

Abstract: Object-oriented databases (OODBs) have been utilized for complex modeling tasks within a variety of application domains. The OODB schema, typically expressed in a graphical notation, can serve as a useful presentation tool for the information contained in the underlying OODB. However, such a schema can be a large, complex network of classes and relationships. This may greatly hinder its effectiveness in helping users gain an understanding of the OODB contents and data organization. To facilitate this orientation process, a theoretical framework is presented that guides the refinement\/ of an existing schema subclass-of\/ relationship hierarchy ?the backbone of any OODB. The framework sets forth three rules which, when satisfied, lead to the establishment of a collection of contexts, each of which exhibits an internal subclass-of\/ tree structure. A formal proof of this result is presented. An algorithmic methodology, involving a humanomputer interaction, describes how the approach can be applied to a given OODB schema. An application of the methodology to an example OODB schema is included.

Abstract: Objective: The Unified Medical Language System (UMLS) Semantic Network (SN) two-tree structure is restrictive because it does not allow a semantic type to be a specialization of several other semantic types. In this paper, the SN is expanded into a multiple subsumption structure with a directed acyclic graph (DAG) IS-A hierarchy, allowing a semantic type to have multiple parents. New viable IS-A links are added as warranted.

Abstract: Objective: To develop and test a method for automatically detecting inconsistencies between the parent-child is-a relationships in the Metathesaurus and the ancestor-descendant relationships in the Semantic Network of the Unified Medical Language System (UMLS).

Abstract: Objective: The Unified Medical Language System (UMLS) designed by NLM combines many well established authoritative medical informatics terminologies in one knowledge representation system. Such a resource is very valuable to the healthcare community and industry. However, the UMLS is very large and complex and poses serious comprehension problems for users and maintenance personnel. We present a representation to support the comprehension and navigation of the UMLS.

Perl Y, Geller J. Research on structural issues of the UMLS--past, present, and future. J Biomed Inform. 2003 Dec;36(6):409-13.

Abstract: None.

James Geller, Huanying Gu, and Michael Halper. Semantic refinement and error correction in large terminological knowledge bases, Data & Knowledge Engineering, 45(1), 2003, pp. 1-32.

Abstract: Capturing the semantics of concepts in a terminology has been an important problem in AI. A two-level approach has been proposed where concepts are classified into high-level semantic types, with these types constituting a portion of the concepts' semantics. We present an algorithmic methodology for refining such two-level terminologic networks. A new network is produced consisting of "pure" semantic types and intersection types. Concepts are uniquely re-assigned to these new types. Overall, these types form a better conceptual abstraction, with each exhibiting uniform semantics. using them, it becomes easier to detect classification errors. The methodology is applied to the UMLS.

Li-min Liu, James Geller and Yehoshua Perl,

Abstract: In previous work, we have modeled a vocabulary given as a semantic network by an OODB (Object-Oriented Database). The OODB schema thus obtained provides a compact abstract view of the vocabulary. This enables fast traversal of the vocabulary by a user. In the semantic network vocabulary, the IS-A relationships express the specialization hierarchy. In our OODB modeling of the vocabulary, the SUBCLASS relationship expresses the specialization hierarchy of the classes and supports the inheritance of their properties. A typical IS-A path in the vocabulary has a corresponding shorter SUBCLASS path in the OODB schema. In the current paper we expose several cases where the SUBCLASS hierarchy fails to fully correspond to the IS-A hierarchy of the vocabulary. In these cases there exist traversal paths in the semantic network for which there are no corresponding traversal paths in the OODB schema. The reason for this failure is the existence of some IS-A relationships between concepts of two classes, that are not connected by a SUBCLASS relationship. This
phenomenon weakens the accuracy of our modeling. To rectify the situation we introduce a new OODB semantic relationship IS-A?to represent the existence of IS-A relationships between concepts of a pair of classes which are not connected via a SUBCLASS relationship. The resulting schema contains both SUBCLASS relationships and IS-A?relationships which completely models the ISA hierarchy of the vocabulary. We define a mixed class level traversal path to contain either SUBCLASS or IS-A? relationships. Consequently, each traversal path in the semantic network has a corresponding mixed traversal path in the OODB schema. Hence the introduction of the semantic OODB IS-A?relationship improves the modeling of semantic network vocabularies by OODBs.

Y. Perl, Z. Chen, M. Halper, J. Geller, L. Zhang, and Y. Peng.

Abstract: The Unified Medical Language System (UMLS) joins together a group of established medical terminologies in a unified knowledge representation framework. Two major resources of the UMLS are its Metathesaurus, containing a large number of concepts, and the Semantic Network (SN), containing semantic types and forming an abstraction of the Metathesaurus. However, the SN itself is large and complex and may still be difficult to view and comprehend. Our structural partitioning technique partitions the SN into structurally uniform sets of semantic types based on the distribution of the relationships within the SN. An enhancement of the structural partition results in cohesive, singly rooted sets of semantic types. Each such set is named after its root which represents the common nature of the group. These sets of semantic types are represented by higher-level components called metasemantic types. A network, called a metaschema, which consists of the meta-semantic types connected by hierarchical and semantic relationships is obtained and provides an abstract view supporting orientation to the SN. The metaschema is utilized to audit the UMLS classifications. We present a set of graphical views of the SN based on the metaschema to help in user orientation to the SN. A study compares the cohesive metaschema to metaschemas derived semantically by UMLS experts.

J. Geller, Y. Perl, M. Halper, Z. Chen and H. Gu,

Abstract: Semantic networks are excellent knowledge representation structures.However, large semantic networks are hard to comprehend. To overcome this difficulty, several methods of partitioning have been developed which rely on different mixes of structural and semantic methods. However, little has appeared in the literature concerning the question whether a partition of a semantic network creates subnetworks that agree with human in-sight. We address this issue by presenting a comparison between the results of an algorithmic partitioning method and a partition created by a group of experts. Subsequently, we show how a network partition can be used to generate various partial views of a semantic network, which facilitate user orientation. Examles from the UMLS Semantic Network are used to demonstrate partial views.

Z. Chen, Y. Perl, M. Halper, J. Geller, H. Gu,

Abstract: The unified medical language system (UMLS) integrates many well-established biomedical terminologies. The UMLS semantic network (SN) can help orient users to the vast knowledge content of the UMLS Metathesaurus (META) via its abstract conceptual view. However, the SN itself is large and complex and may still be difficult to comprehend. Our technique partitions the SN into smaller meaningful units amenable to display on limited-sized computer screens. The basis for the partitioning is the distribution of the relationships within the SN. Three rules are applied to transform the original partition into a second more cohesive partition.

Li-Min Liu, Michael Halper, James Geller and Yehoshua Perl,

Abstract: 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).

H. Gu, Y. Perl,  M. Halper, J. Geller, F. Kuo and J.J. Cimino,

Abstract: Controlled medical terminologies are increasingly becoming strategic components of various healthcare enterprises. However, the typical medical terminology can be difficult to exploit due to its extensive size and high density. The schema of a medical terminology offered by an object-oriented representation is a valuable tool in providing an abstract view of the terminology, enhancing comprehensibility and making it more usable. However, schemas themselves can be large and unwieldy. We present a methodology for partitioning a medical terminology schema into manageably sized fragments that promote increased comprehension. Our methodology has a refinement process for the subclass hierarchy of the terminology schema. The methodology is carried out by a medical domain expert in conjunction with a computer. The expert is guided by a set of three modeling rules, which guarantee that the resulting partitioned schema consists of a forest of trees. This makes it easier to understand and consequently use the medical terminology. The application of our methodology to the schema of the Medical Entities Dictionary (MED) is presented.

H. Gu, Y. Perl,  J. Geller, M. Halper, L. Liu and J.J. Cimino, Representing the UMLS as an OODB: Modelling Issues and Advantages. Journal of the American Medical Informatics Association, 7(1), January 2000, pp.66-80

Abstract: Objective: The Unified Medical Language System (UMLS) designed by NLM combines many well established authoritative medical informatics terminologies in one knowledge representation system. Such a resource is very valuable to the healthcare community and industry. However, the UMLS is very large and complex and poses serious comprehension problems for users and maintenance personnel. We present a representation to support the comprehension and navigation of the UMLS.

H.Gu, M. Halper, J. Geller and Y. Perl,  Benefits of an Object-oriented Database representation for Controlled Medical Terminologies. Journal of the American Medical Informatics Association, 6(4), 283-303, July 1999.

Abstract: Objective: Controlled medical terminologies (CMTs) have been recognized as important tools in a variety of medical informatics applications ranging from patient-record systems to decision-support systems. CMTs are typically organized in semantic network structures consisting of tens to hundreds of thousands of concepts. This overwhelming size and complexity can be a serious barrier to their maintenance and wide-spread utilization. In this paper, we propose the use of object-oriented databases (OODBs) to address the problems posed by the extensive scope and high complexity of most CMTs for maintenance personnel and general user alike.

L. Liu, M. Halper, J. Geller and Y.Perl. Controlled Vocabularies in OODBs: Modeling issues and implementation. Distributed and Parallel Databases, 7(1), 37-65, January 1999.

Abstract: A major problem that arises in many large application domains is the discrepancy among terminologies of different information systems. The terms used by the information systems of one organization may not agree with the terms used by another organization even when they are in the same domain. Such a situation clearly impedes communication and the sharing of information, and decreases the efficiency of doing business. Problems of this nature can be overcome using a controlled vocabulary (CV), a system of concepts that consolidates and unifies the terminologies of a domain. However, CVs are large and complex and difficult to comprehend. This paper presents a methodology for representing a semantic network-based CV as an object-oriented database (OODB). We call such a representation an Object-Oriented Vocabulary Repository (OOVR). The methodology is based on a structural analysis and partitioning of the source CV. The representation of a CV as an OOVR offers both the level of support typical of database management systems and an abstract view which promotes comprehension of the CV structure and content. After discussing the theoretical aspects of the methodology, we apply it to the MED and InterMED, two existing CVs from the medical field. A program, called the OOVR Generator, for automatically carrying out our methodology is described. Both the MED-OOVR and the InterMED-OOVR have been created using the OOVR Generator, and each exists on top of ONTOS, a commercial OODBMS. The OOVR derived from the InterMED is presently available on the Web.

H. Gu, Y. Perl, J. Geller, M. Halper and M. Singh, A methodology for Partitioning a Vocabulary Hierarchy into Trees, Artificial Intelligence in Medicine, 15 77-98, 1999.

Abstract: Controlled medical vocabularies are useful in application areas such as medical information systems and decision-support system. However, such vocabularies are large and complex, and working with them can be daunting. It is important to provide a means for orienting vocabulary designers and users to the vocabulary's contents. We describe a methodology for partitioning a vocabulary based on an IS-A hierarchy into small meaningful pieces. The methodology uses our disciplined modeling framework to refine the IS-A hierarchy according to prescribed rules in a process carried out by a user in conjunction with the computer. The partitioning of the hierarchy implies a partitioning of the vocabulary. We demonstrate the methodology with respect to a complex sample of the MED, an existing medical vocabulary.

Li Zhang, Yehoshua Perl, Michael Halper, James Geller, James J. Cimino. Enriching the Structure of the UMLS Semantic Network. In the proceding of the 2002 AMIA Conference

Abstract: The Unified Medical Language System (UMLS) Semantic Network (SN) onsisting of a network of semantic typesas a two-tree structure, where each semantic type has at most one parent semantic type. This arrangement is restrictive because some semantic types are, by their definition, specializations of several parents. As a proposed enhancement to the SN, its semantic types have previously been partitioned into groups, each of which contains semantic types of some specific area. However, some groups of this proposed partition contain forest (i.e., multiple-tree) structures or even isolated semantic types. Both situations imply a disconnected internal structure. Connectivity is actually one way to assess the proposed emantic validity? principle for partitions. It is a desired, although not required, property. In this paper, we introduce a methodology for identifying issing? IS-A links and adding them to the SN. This process transforms the SN into a Directed Acyclic Graph (DAG) structure, with semantic types permitted to have multiple parents. A result of our methodology is the transformation of the proposed SN partition into groups satisfying the connectivity property.

Yi Peng, Michael Halper. Auditing the UMLS For Redundant Classifications. In the proceding of the 2002 AMIA Conference, pp 612-616

Abstract: The UMLS Semantic Network (SN) serves as a valuable abstraction for the underlying concept repository called the Metathesaurus (META). Specifically, the SN forms a classification layer for the META, with each of the META constituent concepts assigned to one or more semantic types in the SN. The rule in the design of the SN is to have concepts explicitly assigned to the lowest possible semantic types in the SN IS-A hierarchy. Implicit assignment to higher semantic types can be inferred via the IS-A relationships. However, in subsequent versions of the UMLS, unnecessary, simultaneous assignments to descendant and ancestor semantic types have been discovered (e.g., 8,622 in the UMLS 1998 version and 12,657 in the 2001 version). The assignment of concepts to such ancestor semantic types is called redundant classification. There is a need for an automated auditing tool that can identify all these redundant classifications. In this paper, an efficient algorithm for this auditing task is introduced. Details of its application to the current (2001) version of the UMLS are presented and the results are discussed.

Huanying (Helen) Hu, Hua Min, Yi Peng, Li Zhang, Yehoshua Perl. Using the Metaschema to Audit UMLS Classification Errors. In the proceding of the 2002 AMIA Conference, pp 310-314

Abstract: li.pdf is for Enriching the Structure of the UMLS Semantic Network; not for this paper. Need to find the ps file then convert it into pdf and link it.

H. Gu, J. Geller, L. Liu, and M. Halper. Using a similarity measurement to partition a vocabulary of medical concepts. In T. Bench-Capon, G. Soda, and A. M. Tjoa, editors, Proceedings of the 10th International Conference on Database and Expert Systems Applications: DEXA'99, Florence, Italy, August 1999. Published as: Lecture Notes in Computer Science, 1677, Springer-Verlag, New York, pages 712-723.

Abstract: Repeat, Auditing concept categorizations in the UMLS

H.Gu,Y. Perl, J. Geller, M. Halper, L. Liu, and J. J.Cimino. Modeling the UMLS using an OODB. In N. M. Lorenzi, editor, Proceedings of the 1999 American Medical Informatics Association (AMIA) Annual Symposium, pages 82-86, Washington, DC, November1999.

Abstract: Objective: The Unified Medical Language System (UMLS) designed by NLM combines many well established authoritative medical informatics terminologies in one knowledge representation system. Such a resource is very valuable to the healthcare community and industry. However, the UMLS is very large and complex and poses serious comprehension problems for users and maintenance personnel. We present a representation to support the comprehension and navigation of the UMLS.

H. Gu, L. Liu, M. Halper , J. Geller, and Y. Perl. Converting an Integrated Hospital Formulary into an Object-Oriented Database Representation. In C. G. Chute, editor, Proceedings of AMIA'98, Orlando, FL, pp 770-774, November, 1998.

Abstract: Controlled Medical Vocabularies (CMVs) have proven to be extremely useful in their support of the tasks of information sharing and integration, communication among various software applications, and decision support. Modeling a CMV as an Object-Oriented Database (OODB) provides additional benefits such as increased support for vocabulary comprehension and flexible access. In this paper, we describe the process of modeling and converting an existing integrated hospital formulary (i.e., set of pharmacological concepts) into an equivalent OODB representation, which, in general, we refer to as an Object-Oriented Healthcare Vocabulary Repository (OOHVR). The source for our example OOHVR is a formulary provided by the Connecticut Healthcare Research and Education Foundation (CHREF). Utilizing this source formulary together with the semantic hierarchy composed of major and minor drug classes defined as part of the National Drug Code (NDC) directory, we constructed a CMV that was eventually converted into its OOHVR form (the CHREF-OOHVR). The actual conversion step was carried out automatically by a program, called the OOHVR Generator, that we have developed. At present, the CHREF-OOHVR is running on top of ONTOS, a commercial OODB management system, and is accessible on the Web.

H. Gu, Y. Perl, J. Geller, M. Halper, J. J. Cimino, and M. Singh. Partitioning a vocabulary's IS-A hierarchy into trees. In D. R. Masys, editor, Proceedings of the 1997 American Medical Informatics Association (AMIA) Annual Fall Symposium, pages 630-634, Nashville, TN, October 1997.

Abstract: Controlled medical vocabularies are useful in application areas such as medical information-systems and decision-support. However, such vocabularies are large and complex, and working with them can be daunting. It is important to provide a means for orienting users to the vocabulary's contents. This paper introduces a methodology for partitioning a vocabulary into small, meaningful pieces. The partitioning is done with respect to the vocabulary's IS-A hierarchy. The methodology, based on a set of rules for refining the IS-A hierarchy, is a process carried out by a user in conjunction with the computer. The methodology is demonstrated on a complex portion of a vocabulary.

L. Liu, M. Halper, H.Gu, J. Geller, and Y. Perl. Modeling a vocabulary in an object-oriented database. In K. Barker and M. T. Ozsu, editors, CIKM-96, Proceedings of the Fifth International Conference on Information and Knowledge Management, pages 179-188, Rockville, MD, November 1996.

Abstract: Controlled vocabularies have been used as the means for unifying disparate terminologies found within an application field. This unification leads to better administration of information and enhanced communication among various parties. Semantic networks have been shown to be excellent vehicles for modeling controlled vocabularies. However, they often lack the necessary access flexibility and robustness required by external agents such
as intelligent information-locators and decision-support systems. In this paper, we describe the process of mapping an existing medical vocabulary based on a semantic network model into an Object-Oriented Database (OODB) system. We first consider two straightforward approaches to carrying out this task and describe their deficiencies. We then present a new approach which yields a very compact OODB schema for the representation of the vocabulary entire hierarchy and inter-connectivity. We refer to the resulting OODB as the Object-Oriented Healthcare Vocabulary Repository (OOHVR), which is currently up and running in the
context of ONTOS, a commercially available OODB system.

M. Halper, H.Gu, J. J. Cimino, J. Geller, and Y. Perl. Comprehending the structure of a medical vocabulary using object-oriented database modeling. OOPSLA'96 Workshop on Object-Oriented Technology for Health Care and Medical Information Systems, San Jose, CA, October 1996. Position Paper.

Abstract: The purpose of this paper is to demonstrate how the transformation of a medical vocabulary based on a Semantic Network (SN) model into a vocabulary based on an Object-Oriented Database (OODB) model helps in the maintenance of the vocabulary. We describe an OODB schema which captures the overall structure of the vocabulary in a compact form and uncovers some errors and inconsistencies made in the vocabulary's original modeling.

H. Gu, J. J. Cimino, M. Halper, J. Geller, and Y. Perl. Utilizing OODB schema modeling for vocabulary management. In J. J. Cimino, editor, Proceedings of the 1996 American Medical Informatics Association (AMIA) Annual Fall Symposium, pages 274-278, Washington, DC, October 1996.

Abstract: Comprehension of complex controlled vocabularies is often difficult. We present a method, facilitated by an object-oriented database, for depicting such a vocabulary (the Medical Entities Dictionary (MED) from the Columbia-Presbyterian Medical Center) in a schematic way which uses a sparse inheritance network of area classes. The resulting Object Oriented Health Vocabulary repository (OOHVR) allows visualization of the 43,000 MED concepts as 90 area classes. This view has provided valuable information to those responsible with maintaining the MED. As a result, the MED organization has been improved and some previously-unrecognized errors and inconsistencies have been removed. We believe that this schematic approach allows improved comprehension of the gestalt of large controlled medical vocabulary.