A common framework for classifying and specifying deductive database updating problems

Several problems may arise when updating a deductive database. Up to now, the general approach of the research related to deductive database updating problems has been to provide specific methods for solving particular problems. However, ali these methods are explicitly or implicitly based on a set of rules that define the changes that occur in a transition from an old state of a database to a new, updated state. Therefore, these rules provide the basis of a framework for classifying and specifying these problems. In this paper we propose to use the event rules [Oli91], which explicitly define the insertions and deletions induced by an update, for such a basis. We also define two interpretations of these rules which provide a common framework for classifying and specifying deductive database updating problems such as view updating, materialized view maintenance, integrity constraints checking, integrity constraints maintenance, repairing inconsistent databases, integrity constraints satisfiability or condition monitoring. Moreover, these interpretations allow us to identify and to specify sorne problems that have received little attention up to now like enforcing or preventing condition activation. By considering only a uniqu~ set of rules for specifying all these problems, we want to show that it is possible to provide general methods able to deal with all these problems as a whole

Twelve Theses on Reactive Rules for the Web

Reactivity, the ability to detect and react to events, is an essential functionality in many information systems. In particular, Web systems such as online marketplaces, adaptive (e.g., recommender) systems, and Web services, react to events such as Web page updates or data posted to a server. This article investigates issues of relevance in designing high-level programming languages dedicated to reactivity on the Web. It presents twelve theses on features desirable for a language of reactive rules tuned to programming Web and Semantic Web applications

Integrity Constraints in Trust Management

We introduce the use, monitoring, and enforcement of integrity constraints in trust management-style authorization systems. We consider what portions of the policy state must be monitored to detect violations of integrity constraints. Then we address the fact that not all participants in a trust management system can be trusted to assist in such monitoring, and show how many integrity constraints can be monitored in a conservative manner so that trusted participants detect and report if the system enters a policy state from which evolution in unmonitored portions of the policy could lead to a constraint violation.Comment: An extended abstract appears in the proc. of the 10th ACM Symp. on Access Control Models and Technologies (SACMAT). 200

Context-Aware Information Retrieval for Enhanced Situation Awareness

In the coalition forces, users are increasingly challenged with the issues of information overload and correlation of information from heterogeneous sources. Users might need different pieces of information, ranging from information about a single building, to the resolution strategy of a global conflict. Sometimes, the time, location and past history of information access can also shape the information needs of users. Information systems need to help users pull together data from disparate sources according to their expressed needs (as represented by system queries), as well as less specific criteria. Information consumers have varying roles, tasks/missions, goals and agendas, knowledge and background, and personal preferences. These factors can be used to shape both the execution of user queries and the form in which retrieved information is packaged. However, full automation of this daunting information aggregation and customization task is not possible with existing approaches. In this paper we present an infrastructure for context-aware information retrieval to enhance situation awareness. The infrastructure provides each user with a customized, mission-oriented system that gives access to the right information from heterogeneous sources in the context of a particular task, plan and/or mission. The approach lays on five intertwined fundamental concepts, namely Workflow, Context, Ontology, Profile and Information Aggregation. The exploitation of this knowledge, using appropriate domain ontologies, will make it feasible to provide contextual assistance in various ways to the work performed according to a user’s taskrelevant information requirements. This paper formalizes these concepts and their interrelationships

An XML Framework for Integrating Continuous Queries, Composite Event Detection, and Database Condition Monitoring for Multiple Data Streams

With advancements in technology over the last ten years, data management issues have evolved from a stored persistent form to also include streaming data generated from sensors and other software monitoring tools. Furthermore, distributed, event-based systems are becoming more prevalent, with a need to develop applications that can dynamically respond to information extracted from data streams. This research is investigating the integration of stream processing and event processing techniques, with expressive filtering capabilities that include queries over persistent databases to provide application context to the filtering process. Distributed Event Processing Agents (DEPAs) continuously filter events from multiple data streams of different formats that provide XML views. Composite events for data streams are expressed using the Composite Event Detection Language (CEDL) and mapped to Composite XQuery (CXQ) for implementation. CXQ is a language that extends XQuery with features from CEDL, including operators for expressing sequence, disjunction, conjunction, repetition, aggregation, and time windows for events. Continuous queries and composite event filters are integrated with techniques for materialized view maintenance and incremental evaluation in condition monitoring to provide efficient ways of enhancing stream filters with database queries. The filtering and event detection load is distributed among multiple DEPAs, with CXQ expressions decomposed to allocate subcomponents of the expression to DEPAs that efficiently communicate in the global detection of composite events. A unique aspect of our research is that it extends XQuery with temporal, composite event features to combine techniques for continuous queries in stream processing, incremental evaluation in condition monitoring, and detection and filtering of composite events, creating an expressive environment for the extraction of meaningful events from multiple data streams with XML views