21,975 research outputs found

    A Logical Approach to Cooperative Information Systems

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    ``Cooperative information system management'' refers to the capacity of several computing systems to communicate and cooperate in order to acquire, store, manage, query data and knowledge. Current solutions to the problem of cooperative information management are still far from being satisfactory. In particular, they lack the ability to fully model cooperation among heterogeneous systems according to a declarative style. The use of a logical approach to model all aspects of cooperation seems very promising. In this paper, we deŸne a logical language able to support cooperative queries, updates and update propagation. We model the sources of information as deductive databases, sharing the same logical language to ex- press queries and updates, but containing independent, even if possibly related, data. We use the Obj-U-Datalog (E. Bertino, G. Guerrini, D. Montesi, Toward deductive object data- bases, Theory and Practice of Object Systems 1 (1) (1995) 19±39) language to model queries and transactions in each source of data. Such language is then extended to deal with active rules in the style of Active-U-Datalog (E. Bertino, B. Catania, V. Gervasi, A. Ra aet a, Ac- tive-U-Datalog: Integrating active rules in a logical update language, in: B. Freitag, H. Decker, M. Kifer, A. Voronkov (Eds.), LBCS 1472: Transactions and Change in Login Databases, 1998, pp. 106±132), interpreted according to the PARK semantics proposed in G. Gottlob, G. Moerkotte, V.S. Subrahmanian (The PARK semantics for active rules, in: P.M.G. Apers, M. Bouzeghoub, G. Gardarin (Eds.), LNCS 1057: Proceedings of the Fifth International Con- ference on Extending Database Technology, 1996, pp. 35±55). By using active rules, a system can e ciently perform update propagation among di erent databases. The result is a logical environment, integrating active and deductive rules, to perform update propagation in a cooperative framework

    Introducing Dynamic Behavior in Amalgamated Knowledge Bases

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    The problem of integrating knowledge from multiple and heterogeneous sources is a fundamental issue in current information systems. In order to cope with this problem, the concept of mediator has been introduced as a software component providing intermediate services, linking data resources and application programs, and making transparent the heterogeneity of the underlying systems. In designing a mediator architecture, we believe that an important aspect is the definition of a formal framework by which one is able to model integration according to a declarative style. To this purpose, the use of a logical approach seems very promising. Another important aspect is the ability to model both static integration aspects, concerning query execution, and dynamic ones, concerning data updates and their propagation among the various data sources. Unfortunately, as far as we know, no formal proposals for logically modeling mediator architectures both from a static and dynamic point of view have already been developed. In this paper, we extend the framework for amalgamated knowledge bases, presented by Subrahmanian, to deal with dynamic aspects. The language we propose is based on the Active U-Datalog language, and extends it with annotated logic and amalgamation concepts. We model the sources of information and the mediator (also called supervisor) as Active U-Datalog deductive databases, thus modeling queries, transactions, and active rules, interpreted according to the PARK semantics. By using active rules, the system can efficiently perform update propagation among different databases. The result is a logical environment, integrating active and deductive rules, to perform queries and update propagation in an heterogeneous mediated framework.Comment: Other Keywords: Deductive databases; Heterogeneous databases; Active rules; Update

    Cooperative answers in database systems

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    A major concern of researchers who seek to improve human-computer communication involves how to move beyond literal interpretations of queries to a level of responsiveness that takes the user's misconceptions, expectations, desires, and interests into consideration. At Maryland, we are investigating how to better meet a user's needs within the framework of the cooperative answering system of Gal and Minker. We have been exploring how to use semantic information about the database to formulate coherent and informative answers. The work has two main thrusts: (1) the construction of a logic formula which embodies the content of a cooperative answer; and (2) the presentation of the logic formula to the user in a natural language form. The information that is available in a deductive database system for building cooperative answers includes integrity constraints, user constraints, the search tree for answers to the query, and false presuppositions that are present in the query. The basic cooperative answering theory of Gal and Minker forms the foundation of a cooperative answering system that integrates the new construction and presentation methods. This paper provides an overview of the cooperative answering strategies used in the CARMIN cooperative answering system, an ongoing research effort at Maryland. Section 2 gives some useful background definitions. Section 3 describes techniques for collecting cooperative logical formulae. Section 4 discusses which natural language generation techniques are useful for presenting the logic formula in natural language text. Section 5 presents a diagram of the system

    A theorem prover-based analysis tool for object-oriented databases

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    We present a theorem-prover based analysis tool for object-oriented database systems with integrity constraints. Object-oriented database specifications are mapped to higher-order logic (HOL). This allows us to reason about the semantics of database operations using a mechanical theorem prover such as Isabelle or PVS. The tool can be used to verify various semantics requirements of the schema (such as transaction safety, compensation, and commutativity) to support the advanced transaction models used in workflow and cooperative work. We give an example of method safety analysis for the generic structure editing operations of a cooperative authoring system

    Compensation methods to support cooperative applications: A case study in automated verification of schema requirements for an advanced transaction model

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    Compensation plays an important role in advanced transaction models, cooperative work and workflow systems. A schema designer is typically required to supply for each transaction another transaction to semantically undo the effects of . Little attention has been paid to the verification of the desirable properties of such operations, however. This paper demonstrates the use of a higher-order logic theorem prover for verifying that compensating transactions return a database to its original state. It is shown how an OODB schema is translated to the language of the theorem prover so that proofs can be performed on the compensating transactions
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