Showing papers by "Natalya F. Noy published in 2004"

Semantic integration: a survey of ontology-based approaches

Abstract: Semantic integration is an active area of research in several disciplines, such as databases, information-integration, and ontologies. This paper provides a brief survey of the approaches to semantic integration developed by researchers in the ontology community. We focus on the approaches that differentiate the ontology research from other related areas. The goal of the paper is to provide a reader who may not be very familiar with ontology research with introduction to major themes in this research and with pointers to different research projects. We discuss techniques for finding correspondences between ontologies, declarative ways of representing these correspondences, and use of these correspondences in various semantic-integration tasks

The protégé OWL plugin: an open development environment for semantic web applications

Abstract: We introduce the OWL Plugin, a Semantic Web extension of the Protege ontology development platform. The OWL Plugin can be used to edit ontologies in the Web Ontology Language (OWL), to access description logic reasoners, and to acquire instances for semantic markup. In many of these features, the OWL Plugin has created and facilitated new practices for building Semantic Web contents, often driven by the needs of and feedback from our users. Furthermore, Protege's flexible open-source platform means that it is easy to integrate custom-tailored components to build real-world applications. This document describes the architecture of the OWL Plugin, walks through its most important features, and discusses some of our design decisions.

Ontology Evolution: Not the Same as Schema Evolution

Abstract: As ontology development becomes a more ubiquitous and collaborative process, ontology versioning and evolution becomes an important area of ontology research. The many similarities between database-schema evolution and ontology evolution will allow us to build on the extensive research in schema evolution. However, there are also important differences between database schemas and ontologies. The differences stem from different usage paradigms, the presence of explicit semantics and different knowledge models. A lot of problems that existed only in theory in database research come to the forefront as practical problems in ontology evolution. These differences have important implications for the development of ontology-evolution frameworks: The traditional distinction between versioning and evolution is not applicable to ontologies. There are several dimensions along which compatibility between versions must be considered. The set of change operations for ontologies is different. We must develop automatic techniques for finding similarities and differences between versions.

Ontology versioning in an ontology management framework

Abstract: Ontologies have become ubiquitous in information systems. They constitute the semantic Web's backbone, facilitate e-commerce, and serve such diverse application fields as bioinformatics and medicine. As ontology development becomes increasingly widespread and collaborative, developers are creating ontologies using different tools and different languages. These ontologies cover unrelated or overlapping domains at different levels of detail and granularity. A uniform framework, which we present here, helps users manage multiple ontologies by leveraging data and algorithms developed for one tool in another. For example, by using an algorithm we developed for structural evaluation of ontology versions, this framework lets developers compare different ontologies and map similarities and differences among them. Multiple-ontology management includes these tasks: maintain ontology libraries, import and reuse ontologies, translate ontologies from one formalism to another, support ontology versioning, specify transformation rules between different ontologies and version, merge ontologies, align and map between ontologies, extract an ontology's self-contained parts, support inference across multiple ontologies, support query across multiple ontologies.

Specifying ontology views by traversal

Abstract: One of the original motivations behind ontology research was the belief that ontologies can help with reuse in knowledge representation. However, many of the ontologies that are developed with reuse in mind, such as standard reference ontologies and controlled terminologies, are extremely large, while the users often need to reuse only a small part of these resources in their work. Specifying various views of an ontology enables users to limit the set of concepts that they see. In this paper, we develop the concept of a Traversal View, a view where a user specifies the central concept or concepts of interest, the relationships to traverse to find other concepts to include in the view, and the depth of the traversal. For example, given a large ontology of anatomy, a user may use a Traversal View to extract a concept of Heart and organs and organ parts that surround the heart or are contained in the heart. We define the notion of Traversal Views formally, discuss their properties, present a strategy for maintaining the view through ontology evolution and describe our tool for defining and extracting Traversal Views.

Why evaluate ontology technologies? Because it works!

Abstract: We deal with two types of ontology evaluation, content evaluation and ontology technology evaluation. Evaluating content is a must for preventing applications from using inconsistent, incorrect, or redundant ontologies. It's unwise to publish an ontology that one or more software applications will use without first evaluating it. A well-evaluated ontology won't guarantee the absence of problems, but it makes its use safer. Similarly, evaluating ontology technology eases its integration with other software environments, ensuring a correct technology transfer from the academic to the industrial world. We also discuss ontology libraries, ontology tool, and formal evaluation of ontology quality.

Tracking changes during ontology evolution

Abstract: As ontology development becomes a collaborative process, developers face the problem of maintaining versions of ontologies akin to maintaining versions of software code or versions of documents in large projects. Traditional versioning systems enable users to compare versions, examine changes, and accept or reject changes. However, while versioning systems usually treat software code and text documents as text files, a versioning system for ontologies must compare and present structural changes rather than changes in text representation of ontologies. In this paper, we present the PromptDiff ontology-versioning environment, which address these challenges. PromptDiff includes an efficient version-comparison algorithm that produces a structural diff between ontologies. The results are presented to the users through an intuitive user interface for analyzing the changes that enables users to view concepts and groups of concepts that were added, deleted, and moved, distinguished by their appearance and with direct access to additional information characterizing the change. The users can then act on the changes, accepting or rejecting them. We present results of a pilot user study that demonstrate the effectiveness of the tool for change management. We discuss design principles for an end-to-end ontology-versioning environment and position ontology versioning as a component in a general ontology-management framework.

Introduction to the special issue on semantic integration

Abstract: Semantic heterogeneity is one of the key challenges in integrating and sharing data across disparate sources, data exchange and migration, data warehousing, model management, the Semantic Web and peer-to-peer databases. Semantic heterogeneity can arise at the schema level and at the data level. At the schema level, sources can differ in relations, attribute and tag names, data normalization, levels of detail, and the coverage of a particular domain. The problem of reconciling schema-level heterogeneity is often referred to as schema matching or schema mapping. At the data level, we find different representations of the same real-world entities (e.g., people, companies, publications, etc.). Reconciling data-level heterogeneity is referred to as data deduplication, record linkage, and entity/object matching. To exacerbate the heterogeneity challenges, schema elements of one source can be represented as data in another. This special issue presents a set of articles that describe recent work on semantic heterogeneity at the schema level.

Pushing the envelope: challenges in a frame-based representation of human anatomy

Abstract: One of the main threads in the history of knowledge-representation formalisms is the trade-off between the expressiveness of first-order logic on the one hand and the tractability and ease-of-use of frame-based systems on the other hand. Frame-based systems provide intuitive, cognitively easy-to-understand, and scalable means for modeling a domain. However, when a domain model is particularly complex, frame-based representation may lead to complicated and sometimes awkward solutions. We have encountered such problems when developing the Digital Anatomist Foundational Model, an ontology aimed at representing comprehensively the physical organization of the human body. We show that traditional frame-based techniques such as is-a hierarchies, slots (roles) and role restrictions are not sufficient for a comprehensive model of this domain. The diverse modeling challenges and problems in this project required us to use such knowledge-representation techniques as reified relations, metaclasses and a metaclass hierarchy, different propagation patterns for template and own slots, and so on. We posit that even though the modeling structure imposed by frame-based systems may sometimes lead to complicated solutions, it is still worthwhile to use frame-based representation for very large-scale projects such as this one.

Tools for Mapping and Merging Ontologies

Abstract: Researchers in the ontology-design field have developed the content for ontologies in many domain areas. This distributed nature of ontology development has led to a large number of ontologies covering overlapping domains. In order for these ontologies to be reused, they first need to be merged or aligned to one another. We developed a set of tools to support semi-automatic ontology merging: iPrompt is an interactive ontology merging tool that guides the user through the merging process, presenting him with suggestions for next steps and identifying inconsistencies and potential problems. AnchorPrompt uses a graph structure of ontologies to find correlation between concepts and to provide additional information for iPrompt. we present the tools and results of our evaluation of the tools. We discuss other tools and approaches for mapping between ontologies, both in the field of ontology design and database-schema integration.

Making biomedical ontologies and ontology repositories work

Abstract: It is becoming impossible to contemplate successful bio-medical research without canonical data structures The biomedical computation community finds itself grappling with hundreds of different knowledge bases, metadata formats, and database schemas These include primary databases, such as those in GenBank and MEDLINE; metadata that describe the primary data, such as those in caBIO; and knowledge bases that codify biomedical concepts, such as the Gene Ontology and SNOMED-CT These data structures are representable in languages such as DICOM and MAGE-ML Many of these data elements and knowledge bases have emerged out of necessity from work that scientists, unfamiliar with data and knowledge representation standards, have done in isolation Many of these resources fail to follow consistent modeling conventions, so computer programs cannot consistently interpret them Semantic Web technology and languages such as RDF and OWL can rectify the problem somewhat by providing a common metadata and ontology language and Web-based tools for dealing with ontologies and knowledge structures However, even if translation mechanisms exist between various biomedical resources and Semantic Web languages (which, by itself, is unlikely to happen for all resources), this translation is only part of the solution

Accessing and Manipulating Ontologies Using Web Services.

Abstract: Ontologies and Semantic Web Services are the two core technologies of the Semantic Web. The Semantic Web hinges on the ability of computer programs to perform some task involving the autonomous resolution of semantic issues. This ability requires providing standard access for software to ontologies. Moreover, for the Semantic Web to gain widespread acceptance, it needs to reach a critical mass of applications that can interact. This last point requires providing standard access to functionalities for manipulating ontologies. Therefore, it is relevant to bring ontologies and Web Services together by providing access to ontologies through Semantic Web Services. We analyse different kinds of ontology-manipulation functionalities that could be implemented as ontology Web Services (OWS). We then propose an architecture allowing programs to insert calls to ontology Web Services into the more general framework of Web Services. We show that this architecture is a necessary complement to OWL-S for Semantic Web applications to perform dynamic discovery and invocation of Web Services, thus addressing a key requirement of the Semantic Web. We then demonstrate the scalability of our architecture as it allows the composition of (ontology) Web Services for performing complex tasks. 1 Web Service Access to Ontologies Ontologies and Semantic Web Services are arguably the two core technologies of the Semantic Web. Ontologies provide the backbone of the Semantic Web, defining the semantics of the data and Web resources. Web Services enable programs to call functions provided by a remote server. The structure of the parameters and of the result of the function are represented in an explicit way so that the service can be invoked by any client. Web Services, albeit not yet Semantic Web Services, have become important components of business applications. Currently however, most examples of Web Services (and in fact Semantic Web Services) operate on data that conforms to some schema or ontology. At the same time, ontologies themselves are first-class objects on the Semantic Web. Therefore, we believe that any infrastructure for Semantic Web Services will be incomplete without components to access and manipulate ontologies themselves through Web Services. Such access and manipulation include query of ontology

Using Prompt Ontology-Comparison Tools in the EON Ontology Alignment Contest.

Abstract: Objective evaluation and comparison of knowledge-based tools has so far been mostly an elusive goal for researchers and developers Objective experiments are difficult to perform and require substantial resources The EON Ontology Alignment Contest attempts to overcome these problems in inviting tool developers to perform a series of experiments in ontology alignment and compare their results to the reference alignments produced by experiment authors We used our PROMPT suite of tools in the experiment We briefly describe PROMPT in the paper and present our results Based on this experience, we share our thoughts on the experiment design, its positive and negative aspects, and talk about lessons learned and ideas for future such experiments and contests

Ontology Management with the Prompt Pplugin

Abstract: The study of ontologies and their use is no longer just one of the fields in the Artificial Intelligence literature. Ontologies are now ubiquitous in many information-systems enterprises: they constitute the backbone for the Semantic Web, they are used in E-commerce, and in various application fields such as bioinformatics and medicine. As a result, developers are designing a large number of ontologies using different tools and different languages. These ontologies cover unrelated or overlapping domains, at different levels of detail and granularity. Such wide-spread use of ontologies inevitably produces an ontology-management problem: ontology developers and users need to be able to find and compare existing ontologies, reuse complete ontologies or their parts, maintain different versions, and so on. In other words, ontology developers face problems that are very similar to the ones that software engineers have been facing for many years. The following are some of the tasks in managing multiple ontologies.

Semantic integration workshop at the second international semantic web conference (ISWC-2003)

Abstract: In numerous distributed environments, including today's World Wide Web, enterprise data management systems, large science projects, and the emerging semantic web, applications will inevitably use the information described by multiple ontologies and schemas. We organized the Workshop on Semantic Integration at the Second International Semantic Web Conference to bring together different communities working on the issues of enabling integration among different resources. The workshop generated a lot of interest and attracted more than 70 participants.

Semantic Integration Workshop at the 2nd International Semantic Web Conference (ISWC-2003).

Abstract: In numerous distributed environments, including today's World Wide Web, enterprise data management systems, large science projects, and the emerging semantic web, applications will inevitably use the information described by multiple ontologies and schemas. We organized the Workshop on Semantic Integration at the Second International Semantic Web Conference to bring together different communities working on the issues of enabling integration among different resources. The workshop generated a lot of interest and attracted more than 70 participants.

Protégé OWL Plugin Demo

Abstract: We will demonstrate the OWL Plugin [1,2,3], a Semantic Web extension of the Protege ontology development platform. The OWL Plugin can be used to edit ontologies in the Web Ontology Language (OWL), to access description logic reasoners, and to acquire instances for semantic markup. In many of these features, the OWL Plugin has created and facilitated new practices for building Semantic Web contents, often driven by the needs of and feedback from our users. Furthermore, Protege’s flexible open-source platform means that it is easy to integrate custom-tailored components to build real-world applications. The OWL Plugin is now one of the world’s most widely used OWL editors with a community of several thousand users. A technical overview of the tool and its architecture will be presented in the research track of ISWC [1]. Further information about the tool and screenshots are available from http://protege.stanford.edu/plugins/owl/ In this demo, we will walk through selected features of the tool and provide an opportunity to discuss design decisions with the developers.