Conceptual schema

About: Conceptual schema is a research topic. Over the lifetime, 3384 publications have been published within this topic receiving 78788 citations.

Conceptual Schema and Relational Database Design: A Fact Oriented Approach

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Comparison of Schema Matching Evaluations

Abstract: Recently, schema matching has found considerable interest in both research and practice. Determining matching components of database or XML schemas is needed in many applications, e.g. for E-business and data integration. Various schema matching systems have been developed to solve the problem semi-automatically. While there have been some evaluations, the overall effectiveness of currently available automatic schema matching systems is largely unclear. This is because the evaluations were conducted in diverse ways making it difficult to assess the effectiveness of each single system, let alone to compare their effectiveness. In this paper we survey recently published schema matching evaluations. For this purpose, we introduce the major criteria that influence the effectiveness of a schema matching approach and use these criteria to compare the various systems. Based on our observations, we discuss the requirements for future match implementations and evaluations.

Using Schema Matching to Simplify Heterogeneous Data Translation

Abstract: A broad spectrum of data is available on the Web in distinct heterogeneous sources, and stored under different formats. As the number of systems that utilize this heterogeneous data grows, the importance of data translation and conversion mechanisms increases greatly. In this paper we present a new translation system, based on schema-matching, aimed at simplifying the intricate task of data conversion. We observe that in many cases the schema of the data in the source system is very similar to that of the target system. In such cases, much of the translation work can be done automatically, based on the schemas similarity. This saves a lot of effort for the user, limiting the amount of programming needed. We define common schema and data models, in which schemas and data (resp.) from many common models can be represented. Using a rule-based method, the source schema is compared with the target one, and each component in the source schema is matched with a corresponding component in the target schema. Then, based on the matching achieved, data instances of the source schema can be translated to instances of the target schema. We show that our schema-based translation system allows a convenient specification and customization of data conversions, and can be easily combined with the traditional data-based translation languages.

Natural language analyzing apparatus and method

Abstract: A natural language (NL) analyzing system is provided with the capability to analyze NL expressions and to resolve ambiguities and present them to the user for verification of correct interpretation. A conceptual model of the system, relevant to the application in which the invention is implemented, is created (customizing the system) by the user, and is stored as a conceptual schema. The schema is built of logical facts representing entities (concepts) and relationships between entities, forming a description of the universe of discourse or object system in question. The entities of the schema have at least one external connection, namely to natural language terms in a vocabulary. The schema itself is completely language independent, though the components of it may have "names" expressed in a natural language such as English. There may be a second connection to the entities, namely where the system is used in a query system for relational data bases. In this case the entities of the schema represent objects in the data base, and thus there is a connection between the entities and those objects of the data base. The actual analysis of NL expressions is performed by a natural language engine (NLE) in cooperation with an analysis grammar and the schema. The analysis results in an intermediate, language-independent logic form representation of the input, which is paraphrased back to NL for verification. If the input is a query, there is a translation into a query language such as SQL.

An ontological analysis of the relationship construct in conceptual modeling

Abstract: Conceptual models or semantic data models were developed to capture the meaning of an application domain as perceived by someone. Moreover, concepts employed in semantic data models have recently been adopted in object-oriented approaches to systems analysis and design. To employ conceptual modeling constructs effectively, their meanings have to be defined rigorously. Often, however, rigorous definitions of these constructs are missing. This situation occurs especially in the case of the relationship construct. Empirical evidence shows that use of relationships is often problematical as a way of communicating the meaning of an application domain. For example, users of conceptual modeling methodologies are frequently confused about whether to show an association between things via a relationship, an entity, or an attribute. Because conceptual models are intended to capture knowledge about a real-world domain, we take the view that the meaning of modeling constructs should be sought in models of reality. Accordingly, we use ontology, which is the branch of philosophy dealing with models of reality, to analyze the meaning of common conceptual modeling constructs. Our analysis provides a precise definition of several conceptual modeling constructs. Based on our analysis, we derive rules for the use of relationships in entity-relationship conceptual modeling. Moreover, we show how the rules resolve ambiguities that exist in current practice and how they can enrich the capacity of an entity-relationship conceptual model to capture knowledge about an application domain.