Abstract not found

One important step in integrating heteroge-neous databases is matching equivalent at-tributes: Determining which fields in two databases refer to the same data. The mean-ing of information may be embodied within a. database model, a conceptual schema, appli-cation programs, or data contents. Integra-tion involves extracting semantics, expressing them as metadata, and matching semantically equivalent data elements. We present a proce-dure using a classifier to categorize attributes according to their field specifications and data values, then train a neural network to recog-nize similar attributes. In our technique, the knowledge of how to match equivalent data elements is “discovered ” from metadata, not “pre-programmed”. 1

Abstract not found

The integration of information from multiple databases has been an enduring subject of research for almost 20 years, and many di erent solutions have been attempted or proposed. Missing from this research has been a uniform framework. Usually, each solution develops its own ad-hoc framework, designed to address the particular aspects of the problem that are being attacked and the particular methodology that is being used. To address this situation, in this paper we de ne a formal model for multidatabases, which we call Multiplex. Multiplex is a simple extension of the relational model, which may serve as a uniform abstraction for many previous ad-hoc solutions. Multiplex is based on formal assumptions of integrability, which distinguish between scheme and instance reconcilability among independent databases. Multiplex supports database heterogeneity, and it provides several degrees of freedom that allow it to model actual situations encountered in multidatabase applications. In addition, in situations in which a single answer is not obtainable (either because the global query is not answerable, or there are multiple candidate answers), Multiplex de nes approximative answers. Finally, Multiplex provides a practical platform for implementation. A prototype of such an implementation is described brie y.

In order to integrate a wide variety of databases or many diverse sources of information, we need the ability to learn the similarities directly from instances of the data, which may be embodied within a database model, a conceptual schema, application programs, or data contents. The process of determining semantically equivalent data items can not be "pre-programmed" since the information to be accessed is heterogeneous. Intelligent information integration involves extracting semantics, expressing them as metadata, and matching semantically equivalent data elements. Semint (SEMantic INTegrator) is a system prototype for semantic integration being developed at Northwestern University. It provides a graphical user interface and supports access to a variety of database systems and utilizes both schema information and data contents to determine attribute equivalence. In Semint, the knowledge of how to match equivalent data elements is "discovered ", not "pre-programmed". Introduction Ap...

The process to provide integrated access to several, independent information sources is not easy, due to semantic heterogeneities which lead to semantic conflicts or contradictions. In this paper we present a discussion about the existence of contradictions, their importance and how they can be handled when the need of cooperation arises. 1 Introduction The growing need to access information from several information sources that have been designed independently and operate in a autonomous way has become an active research area nowadays. A possible solution to satisfy this need of cooperation is provide integrated access. This means that a user can formulate a single query and receives a single, consolidated answer. The collection of information sources (from now on called Component DataBases, CDBs), jointly with the software layer that manages the integrated access to data stored in CDBs, is known as an interoperable or Federated DataBase System (FDBS) [SL90]. The main characteristic...

. The approach we suggest is based on a graphical specification language possessing formal semantics so that graphical images themselves are precise specifications suitable for implementation. Our specifications are similar to the sketches developed in the category theory but, in contrast to them, enjoy the possibility of setting arbitrary signatures of diagram properties and operations. An important (and sometimes crucial) step in the process of database design is schema (or view) integration, that is, an activity aimed at producing a global conceptual schema of a database from a set of locally developed user-oriented schemas (views). In our approach, correspondence between semantic schemas to be integrated is specified by equations so that the integration procedure can be reduced to algebraic manipulations with sketches representing schemas. This provides the possibility of automated view integration and, correspondingly, automated database design. In the paper the mathemat...

A graphical formalized language is proposed for specifying systems of views over database schemas. The language is based on the notion of arrow (mapping) between data schemas and is suitable for any data model for which schema mappings are defined. In particular, the constructs of query, query language, view and view integration can be consistently expressed in this arrow formalism and correspondingly specified. This gives rise to a general graph-based framework for specifying complex view systems. Basic constructions of the language and the entire framework as well can be considered as specialization of very general constructs developed in the mathematical category theory. 1 Introduction The notion of view is one of the central ones in the database (DB) technology. Views make it possible to provide each application with its own presentation of data and isolate them from inessential (for them) details and changes of DB schemas. The practical importance of views is commonly recognized...

. The aim of the paper is to suggest a formalized data-model-independent language for metadata modeling. That is, the paper explains notions of database schema, instance, query language and view in some abstract way without using specifics of one or another data model. This gives rise to a universal metadata model suitable for specifying heterogeneous federated database systems. In particular, a formalized schema of heterogeneous federal database environment is built. The framework is based on ideas of graphical logic and algebra developed in the mathematical category theory. The latter can be considered as a precise discipline of arrow (graphical) thinking. So, in a wider context, the paper is an attempt to incorporate arrow thinking into the theoretical foundations of CoopIS and set them on the firm mathematical ground. ? Supported by Grants 93.315 and 96.0316 from the Latvian Council of Science ?? Supported partially by Grant 314/94-72II (the scheme for research collaboration wit...

Abstract. RM-ODP is about modeling, and mathematics is one of the oldest, and deserved, modeling disciplines. Experience accumulated in mathematics in general, and some of machineries developed, may well turn out to be relevant for arranging/organizing / formalizing the concepts managed in RM-ODP. Especially promising here is mathematical category theory that is nothing but a discipline and framework for structure engineering considered in an abstract and precise way. 1