OBJECTIVE: Each Unified Medical Language System (UMLS) concept is assigned one or more semantic types (ST). A dynamic methodology for aiding an auditor in finding concepts that are missing the assignment of a given ST, S is presented. DESIGN: The first part of the methodology exploits the previously introduced Refined Semantic Network and accompanying refined semantic types (RST) to help narrow the search space for offending concepts. The auditing is focused in a neighborhood surrounding the extent of an RST, T (of S) called an envelope, consisting of parents and children of concepts in the extent. The audit moves outward as long as missing assignments are discovered. In the second part, concepts not reached previously are processed and reassigned T as needed during the processing of S's other RSTs. The set of such concepts is expanded in a similar way to that in the first part. MEASUREMENTS: The number of errors discovered is reported. To measure the methodology's efficiency, "error hit rates" (i.e., errors found in concepts examined) are computed. RESULTS: The methodology was applied to three STs: Experimental Model of Disease (EMD), Environmental Effect of Humans, and Governmental or Regulatory Activity. The EMD experienced the most drastic change. For its RST "EMD intersection Neoplastic Process" (RST "EMD") with only 33 (31) original concepts, 915 (134) concepts were found by the first (second) part to be missing the EMD assignment. Changes to the other two STs were smaller. CONCLUSION: The results show that the proposed auditing methodology can help to effectively and efficiently identify concepts lacking the assignment of a particular semantic type.

OBJECTIVE: Chemical concepts assigned multiple "Chemical Viewed Structurally" semantic types (STs) in the Unified Medical Language System (UMLS) are subject to ambiguous interpretation. The multiple assignments may denote the fact that a specific represented chemical (combination) is a conjugate, derived via a chemical reaction of chemicals of the different types, or a complex, composed of a mixture of such chemicals. The previously introduced Refined Semantic Network (RSN) is modified to properly model these varied multi-typed chemical combinations. DESIGN: The RSN was previously introduced as an enhanced abstraction of the UMLS's concepts. It features new types, called intersection semantic types (ISTs), each of which explicitly captures a unique combination of ST assignments in one abstract unit. The ambiguous ISTs of different "Chemical Viewed Structurally" ISTs of the RSN are replaced with two varieties of new types, called conjugate types and complex types, which explicitly denote the nature of the chemical interactions. Additional semantic relationships help further refine that new portion of the RSN rooted at the ST "Chemical Viewed Structurally." MEASUREMENTS: The number of new conjugate and complex types and the amount of changes to the type assignment of chemical concepts are presented. RESULTS: The modified RSN, consisting of 35 types and featuring 22 new conjugate and complex types, is presented. A total of 800 (about 98%) chemical concepts representing multi-typed chemical combinations from "Chemical Viewed Structurally" STs are uniquely assigned one of the new types. An additional benefit is the identification of a number of illegal ISTs and ST assignment errors, some of which are direct violations of exclusion rules defined by the UMLS Semantic Network. CONCLUSION: The modified RSN provides an enhanced abstract view of the UMLS's chemical content. Its array of conjugate and complex types provides a more accurate model of the variety of combinations involving chemicals viewed structurally. This framework will help streamline the process of type assignments for such chemical concepts and improve user orientation to the richness of the chemical content of the UMLS.

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. DESIGN: Our auditing methodology is based on dividing concepts of a terminology into smaller, more manageable units. First, we divide the terminology's concepts into areas according to their relationships/roles. Then each multi-rooted area is further divided into partial-areas (p-areas) that are singly-rooted. Each p-area contains a set of structurally and semantically uniform concepts. Two kinds of abstraction networks, called the area taxonomy and p-area taxonomy, are derived. These taxonomies form the basis for the auditing approach. Taxonomies tend to highlight potentially erroneous concepts in areas and p-areas. Human reviewers can focus their auditing efforts on the limited number of problematic concepts following two hypotheses on the probable concentration of errors. RESULTS: A sample of the area taxonomy and p-area taxonomy for the Biological Process (BP) hierarchy of the National Cancer Institute Thesaurus (NCIT) was derived from the application of our methodology to its concepts. These views led to the detection of a number of different kinds of errors that are reported, and to confirmation of the hypotheses on error concentration in this hierarchy. CONCLUSION: Our auditing methodology based on area and p-area taxonomies is an efficient tool for detecting errors in terminologies satisfying systematic inheritance of roles, and thus facilitates their maintenance. This methodology concentrates a domain expert's manual review on portions of the concepts with a high likelihood of errors.

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. DESIGN: The technique to derive the ESN's relationship structures finds all newly inherited relationships in the ESN. All such relationships are audited for semantic validity, and the blocking mechanism is used to block invalid relationships. The mapping technique to derive the ESN's semantic type assignments uses current SN semantic type assignments and preserves nonredundant categorizations, while preventing new redundant categorizations. RESULTS: Among the 426 newly inherited relationships, 326 are deemed valid. Seven blockings are applied to avoid inheritance of the 100 invalid relationships. Sixteen semantic types have different relationship structures in the ESN as compared to those in the SN. The mapping of semantic type assignments from the SN to the ESN avoids the generation of 26,950 redundant categorizations. The resulting ESN contains 138 semantic types, 149 IS-A links, 7,303 relationships, and 1,013,876 semantic type assignments. CONCLUSION: The ESN's multiple inheritance provides more complete relationship structures than in the SN. The ESN's semantic type assignments avoid the existing redundant categorizations appearing in the SN and prevent new ones that might arise due to multiple parents. Compared to the SN, the ESN provides a more accurate unifying semantic abstraction of the UMLS Metathesaurus.

OBJECTIVE: The Unified Medical Language System's (UMLS's) Semantic Network's (SN's) two-tree structure is restrictive because it does not allow a semantic type to be a specialization of several other semantic types. In this article, 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. DESIGN: Two methodologies are presented to identify and add new viable IS-A links. The first methodology is based on imposing the characteristic of connectivity on a previously presented partition of the SN. Four transformations are provided to find viable IS-A links in the process of converting the partition's disconnected groups into connected ones. The second methodology identifies new IS-A links through a string matching process involving names and definitions of various semantic types in the SN. A domain expert is needed to review all the results to determine the validity of the new IS-A links. RESULTS: Nineteen new IS-A links are added to the SN, and four new semantic types are also created to support the multiple subsumption framework. The resulting network, called the Enriched Semantic Network (ESN), exhibits a DAG-structured hierarchy. A partition of the ESN containing 19 connected groups is also derived. CONCLUSION: The ESN is an expanded abstraction of the UMLS compared with the original SN. Its multiple subsumption hierarchy can accommodate semantic types with multiple parents. Its representation thus provides direct access to a broader range of subsumption knowledge.

Abstract A semantic relationship is a data modeling construct that connects a pair of classes or categories and has inherent constraints and other functionalities that precisely reflect the characteristics of the specific relationship in an application domain. Examples of semantic relationships include part–whole, ownership, materialization and role‐of. Such relationships are important in the construction of information models for advanced applications, whether one is employing traditional data‐modeling techniques, knowledge‐representation languages or object‐oriented modeling methodologies. This paper focuses on the issue of providing built‐in support for such constructs in the context of object‐oriented database (OODB) systems. Most of the popular object‐oriented modeling approaches include some semantic relationships in their repertoire of data‐modeling primitives. However, commercial OODB systems, which are frequently used as implementation vehicles, tend not to do the same. We will present two frameworks by which a semantic relationship can be incorporated into an existing OODB system. The first only requires that the OODB system support manifest type with respect to its instances. The second assumes that the OODB system has a special kind of metaclass facility. The two frameworks are compared and contrasted. In order to ground our work in existing systems, we show the addition of a part–whole semantic relationship both to the ONTOS DB/Explorer OODB system and the VODAK Model Language. Copyright © 2003 John Wiley & Sons, Ltd.

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.

Semantic networks (SNs) are excellent knowledge representation structures. However, large semantic networks are hard to comprehend. To overcome this difficulty, several methods of partitioning have been developed that 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 insight. 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. Examples from the Unified Medical Language System (UMLS) SN are used to demonstrate partial views.

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 (concept level and schema 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 that are 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.

OBJECTIVE: The Unified Medical Language System (UMLS) combines many well-established authoritative medical informatics terminologies in one knowledge representation system. Such a resource is very valuable to the health care community and industry. However, the UMLS is very large and complex and poses serious comprehension problems for users and maintenance personnel. The authors present a representation to support the user's comprehension and navigation of the UMLS. DESIGN: An object-oriented database (OODB) representation is used to represent the two major components of the UMLS-the Metathesaurus and the Semantic Network-as a unified system. The semantic types of the Semantic Network are modeled as semantic type classes. Intersection classes are defined to model concepts of multiple semantic types, which are removed from the semantic type classes. RESULTS: The authors provide examples of how the intersection classes help expose omissions of concepts, highlight errors of semantic type classification, and uncover ambiguities of concepts in the UMLS. The resulting UMLS OODB schema is deeper and more refined than the Semantic Network, since intersection classes are introduced. The Metathesaurus is classified into more mutually exclusive, uniform sets of concepts. The schema improves the user's comprehension and navigation of the Metathesaurus. CONCLUSIONS: The UMLS OODB schema supports the user's comprehension and navigation of the Metathesaurus. It also helps expose and resolve modeling problems in the UMLS.

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. Controlled medical terminologies 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 widespread utilization. The authors propose the use of object-oriented databases to address the problems posed by the extensive scope and high complexity of most CMTs for maintenance personnel and general users alike. DESIGN: The authors present a methodology that allows an existing CMT, modeled as a semantic network, to be represented as an equivalent object-oriented database. Such a representation is called an object-oriented health care terminology repository (OOHTR). RESULTS: The major benefit of an OOHTR is its schema, which provides an important layer of structural abstraction. Using the high-level view of a CMT afforded by the schema, one can gain insight into the CMT's overarching organization and begin to better comprehend it. The authors' methodology is applied to the Medical Entities Dictionary (MED), a large CMT developed at Columbia-Presbyterian Medical Center. Examples of how the OOHTR schema facilitated updating, correcting, and improving the design of the MED are presented. CONCLUSION: The OOHTR schema can serve as an important abstraction mechanism for enhancing comprehension of a large CMT, and thus promotes its usability.

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's entire hierarchy and inter-connectivity. We refer to the resulting OODB as the Object-Oriented Healthcare Voc...

The part-whole semantic relationship (the part relationship, for short) is an important modeling primitive in many advanced application domains such as manufacturing, design, and document processing. In this paper, we examine the problem of integrating such a construct into an OODB system. Specifically, two questions are addressed in this regard. This first is: Can a part relationship be made an intrinsic construct of an existing OODB system without having to rewrite a substantial portion of the system? The second: Can an “open” OODB system which claims to support such an integration really do so, and, more specifically, can the integration be done using a metaclass mechanism which purports to bring extensibility to the VODAK Model Language (VML)?

Derived schema components are an important aspect of traditional semantic data modeling.In this paper, we address the issue of defining