Integration of knowledge from multiple independent sources presents problems due to their semantic heterogeneity. Careful handling of semantics is important for reliable interaction with autonomous sources. This paper highlights some of the issues involved in automating the process of selective integration and details the techniques to deal with them. The approach taken is semi-automatic in nature focusing on identifying the articulation over two ontologies, i.e., the terms where linkage occurs among the sources. A semantic knowledge articulation tool (SKAT) based on simple lexical and structural matching works well in our experiments and semi-automatically detects the intersection of two web sources. An expert can initially provide both positive and negative matching rules on the basis of which the articulation is to be determined and then override the automatically generated articulation before it is finalized. The articulation may be stored or generated on demand and is used to answe...

Many challenging problems facing information systems engineering involve the manipulation of complex metadata artifacts, or models, such as database schemas, interface specifications, or object diagrams, and mappings between models. The applications that solve metadata manipulation problems are complex and hard to build. The goal of generic model management is to reduce the amount of programming needed to develop such applications by providing a database infrastructure in which a set of high-level algebraic operators, such as Match, Merge, and Compose, are applied to models and mappings as a whole rather than to their individual building blocks. This dissertation presents an initial study of the concepts and algorithms for generic model management. We describe the first prototype of a generic model management system, introduce the algebraic operators that are used to manipulate models and mappings, clarify the semantics of the operators, and develop novel algorithms for implementing them. In particular, we present an innovative algorithm based on fixpoint computation that is used for implementing the generic operator Match, which finds correspondences between two models. Using the prototype and the operators presented in the dissertation, we develop solutions for several practically relevant problems, such as change propagation and reintegration.

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Ontology concerns itself with the representation of the objects in the universe and the web of their various connections. The traditional task of ontologists has been to extract from this tangle a single ordered structure, in the form of a tree or lattice. This structure consists of the terms that represent the objects, and the relationships that represent connections between objects. Recent work in ontology goes so far as to consider several distinct, superimposed structures, which each represent a classification of the universe according to a particular criterion. Our purpose is to defer the task of globally classifying terms and relationships. Instead, we focus on composing them for use as we need them. We define contexts to be our unit of encapsulation for ontologies, and use a rule-based algebra to compose novel ontological structures within them. We separate context from concept, the unit of ontological abstraction. Also, we distinguish composition from subsumption, or containment, the relationships that commonly provide structure to ontologies. Adding a formal notation of encapsulation and composition to ontologies leads to more dynamic and maintainable structures, and, we believe, greater computational efficiency for knowledge bases.

This is the second of a two-part paper to review ontology research and development, in particular, ontology mapping and evolving. Ontology is defined as a formal explicit specification of a shared conceptualization. Ontology itself is not a static model so that it must have the potential to capture changes of meanings and relations. As such, mapping and evolving ontologies is part of an essential task of ontology learning and development. Ontology mapping is concerned with reusing existing ontologies, expanding and combining them by some means and enabling a larger pool of information and knowledge in different domains to be integrated to support new communication and use. Ontology evolving, likewise, is concerned with maintaining existing ontologies and extending them as appropriate when new information or knowledge is acquired. It is apparent from the reviews that current research into semi-automatic or automatic ontology research in all the three aspects of generation, mapping and evolving have so far achieved limited success. Expert

Summary. Ontologies are being applied very successfully in supporting information and knowledge exchange between people and organisations. However, for many reasons, different people and organisations will tend to use different ontologies. Therefore, in order to exchange information and knowledge, either everyone must adopt the same ontology — an unlikely scenario — or it must be possible to reconcile different ontologies. This chapter examines the issues and techniques in the reconciliation of ontologies. First, it examines the reasons why people and organisations will tend to use different ontologies, and why the pervasive adoption of common ontologies is unlikely. It then reviews alternative architectures for multipleontology systems on a large scale. A comparative analysis is provided of a number of frameworks which analyse types of mismatches between ontologies. The process of ontology reconciliation is outlined. Finally, some existing software tools that support reconciliation are surveyed, and areas are identified where further work is necessary. 1

ion of Representation for Interoperation David A. Maluf and Gio Wiederhold Department of Computer Science Stanford University Stanford, CA 94305 Abstract. When combining data from distinct sources, there is a need to share meta-data and other knowledge about various source domains. Due to semantic inconsistencies, problems arise when combining knowledge across domains and the knowledge is simply merged. Also, knowledge that is irrelevant to the task of interoperation will be included, making the result unnecessarily complex. An algebra over ontologies has been proposed to support disciplined manipulation of domain knowledge resources. However, if one tries to interoperate directly with the knowledge bases, semantic problems arise due to heterogeneity of representations. This heterogeneity problem can be eliminated by using an intermediate model that controls the knowledge translation from a source knowledge base. The intermediate model we have developed is based on the concept of abst...

One way of designing a taxonomy is by identifying a number of different aspects, or facets of the domain and then designing one taxonomy per facet. In such a faceted taxonomy, the indexing of objects is done by combining terms from di#erent facets. A faceted taxonomy has several advantages by comparison to a single hierarchical taxonomy, such as conceptual clarity, compactness and scalability. However, a major drawback of faceted taxonomies is the possibility of forming a large number of invalid combinations of terms, i.e. combinations of terms that do not apply to any object of the underlying domain. The presence of such invalid combinations causes serious problems during object indexing or browsing. To alleviate this problem, we propose an algebra of taxonomies whose operators allow the e#cient and flexible specification of only valid combinations of terms. This algebra can be used in order to construct very big compound taxonomies in a very systematic and e#cient way.

The diversity and availability of information sources on the World Wide Web has set the stage for integration and reuse at an unparalleled scale. There remain obstacles to exploiting the extent of the Web’s resources in a consistent, scalable and maintainable fashion. The autonomy and volatility of Web sources complicates maintaining wrappers consistent with the requirements of the data’s target application. Also, the sources ’ semantic heterogeneity requires practical methods to mediate their contents. This paper presents an algebra on semistructured data. This algebra is the tool we use to develop wrappers, and mediate their semantic content. We describe wrapper refinement and maintenance as the process of developing a congruity measure between source data sets and their target application. This measure expresses explicitly the context within which source data is relevant for its target use. Enabling mediation between wrappers corresponds to establishing an articulation between data sources through a similarity measure. Similarity measures encapsulate conditions under which sources may be used together. 1.

We have constructed a set of ontologies modelled on conceptual structures elicited from several domain experts. Protocols were collected from various experts who advise on the selection/ specification and purchase of PCs. These protocols were analysed from the perspective of both the processes and the domain knowledge to reflect each expert's inherent conceptualisation of the domain. We are particularly interested in analysing discrepancies within and among such experts' ontologies, and have identified a range of ontology mismatches. A systematic approach to the analysis has been developed; subsequently we shall develop software tools to support this process.