Global Schema as an Inversed View of Local Schemas for Integration

2006 ◽  
Author(s):  
Gongzhu Hu
Keyword(s):  
Global Schema

A Framework for Ontology-Based Top-K Global Schema Generation

2016 ◽  
Vol 6 (1) ◽  
pp. 31-53 ◽  
Author(s):  
Longzhuang Li ◽  
Yuzhe Wei ◽  
Feng Tian
Keyword(s):  
Global Schema

scholarly journals Consistent query answering via ASP from different perspectives: Theory and practice

2012 ◽  
Vol 13 (2) ◽  
pp. 227-252 ◽  
Author(s):  
MARCO MANNA ◽  
FRANCESCO RICCA ◽  
GIORGIO TERRACINA
Keyword(s):  
Data Integration ◽  
Theory And Practice ◽  
Query Answering ◽  
Data Sources ◽  
Global Schema ◽  
Consistent Query Answering ◽  
Data Integration System ◽  
Unified View ◽  
Decidability And Complexity ◽  
Consistent Information

AbstractA data integration system provides transparent access to different data sources by suitably combining their data, and providing the user with a unified view of them, called global schema. However, source data are generally not under the control of the data integration process; thus, integrated data may violate global integrity constraints even in the presence of locally consistent data sources. In this scenario, it may be anyway interesting to retrieve as much consistent information as possible. The process of answering user queries under global constraint violations is called consistent query answering (CQA). Several notions of CQA have been proposed, e.g., depending on whether integrated information is assumed to be sound, complete, exact, or a variant of them. This paper provides a contribution in this setting: it uniforms solutions coming from different perspectives under a common Answer-Set Programming (ASP)-based core, and provides query-driven optimizations designed for isolating and eliminating inefficiencies of the general approach for computing consistent answers. Moreover, the paper introduces some new theoretical results enriching existing knowledge on the decidability and complexity of the considered problems. The effectiveness of the approach is evidenced by experimental results.

scholarly journals Segmented Partisanship in a Federal System

1993 ◽  
Vol 13 ◽  
pp. 425-443
Author(s):  
Michael A. Maggiotto ◽  
Gary D. Wekkin
Keyword(s):  
The Other ◽  
Performance Evaluations ◽  
Federal System ◽  
Global Schema ◽  
The One ◽  
American Federalism

One intention of American federalism, according to Madison, was to provide different contexts into which politics might be organized. Segmented partisanship is a reflection of and a response to the differentiation of power, roles and opportunities that federalism made possible. Accepting partisanship as a collection of schemata, choice among which is contextually determined, permits us to see a greater consistency among performance evaluations and electoral decisions, on the one hand, and partisanship on the other, than a single, global schema allows.

The MAV-ES Data Integration Approach for Decisional Information Systems (DIS)

2016 ◽  
Vol 11 (4) ◽  
pp. 32-55
Author(s):  
Djamila Marouf ◽  
Djamila Hamdadou ◽  
Karim Bouamrane
Keyword(s):  
Data Integration ◽  
Data Sources ◽  
Added Value ◽  
Integration Approach ◽  
Global Schema ◽  
Mediator Systems ◽  
Data Integration System ◽  
Mixed Approach ◽  
Definition Of ◽  
Diverse Data

Massive data to facilitate decision making for organizations and their corporate users exist in many forms, types and formats. Importantly, the acquisition and retrieval of relevant supporting information should be timely, precise and complete. Unfortunately, due to differences in syntax and semantics, the extraction and integration of available semi-structured data from different sources often fail. Needs for seamless and effective data integration so as to access, retrieve and use information from diverse data sources cannot be overly emphasized. Moreover, information external to organizations may also often have to be sourced for the intended users through a smart data integration system. Owing to the open, dynamic and heterogeneity nature of data, data integration is becoming an increasingly complex process. A new data integration approach encapsulating mediator systems and data warehouse is proposed here. Aside from the heterogeneity of data sources, other data integration design problems include distinguishing the definition of the global schema, the mappings and query processing. In order to meet all of these challenges, the authors of this paper advocate an approach named MAV-ES, which is characterized by an architecture based on a global schema, partial schemas and a set of sources. The primary benefit of this architecture is that it combines the two basic GAV and LAV approaches so as to realize added-value benefits of the mixed approach.

scholarly journals Reasoning about Disclosure in Data Integration in the Presence of Source Constraints

2019 ◽  
Author(s):  
Michael Benedikt ◽  
Pierre Bourhis ◽  
Louis Jachiet ◽  
Michaël Thomazo
Keyword(s):  
Data Integration ◽  
Upper Bounds ◽  
Sensitive Information ◽  
Privacy Policy ◽  
Lower And Upper Bounds ◽  
Multiple Sources ◽  
Integration System ◽  
Global Schema ◽  
Data Integration System ◽  
Access Data

Data integration systems allow users to access data sitting in multiple sources by means of queries over a global schema, related to the sources via mappings. Datasources often contain sensitive information, and thus an analysis is needed to verify that a schema satisfies a privacy policy, given as a set of queries whose answers should not be accessible to users. Such an analysis should take into account not only knowledge that an attacker may have about the mappings, but also what they may know about the semantics of the sources.In this paper, we show that source constraints can have a dramatic impact on disclosure analysis. We study the problem of determining whether a given data integration system discloses a source query to an attacker in the presence of constraints, providing both lower and upper bounds on source-aware disclosure analysis.

Integrating Heterogeneous Data for Big Data Analysis

2014 ◽  
pp. 263-288 ◽  
Author(s):  
Richard Millham
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Heterogeneous Data ◽  
Big Data Analysis ◽  
New Paradigm ◽  
Heterogeneous Data Integration ◽  
Multiple Data ◽  
Global Schema ◽  
Optimal Resource ◽  
Data Virtualization

Data is an integral part of most business-critical applications. As business data increases in volume and in variety due to technological, business, and other factors, managing this diverse volume of data becomes more difficult. A new paradigm, data virtualization, is used for data management. Although a lot of research has been conducted on developing techniques to accurately store huge amounts of data and to process this data with optimal resource utilization, research remains on how to handle divergent data from multiple data sources. In this chapter, the authors first look at the emerging problem of “big data” with a brief introduction to the emergence of data virtualization and at an existing system that implements data virtualization. Because data virtualization requires techniques to integrate data, the authors look at the problems of divergent data in terms of value, syntax, semantic, and structural differences. Some proposed methods to help resolve these differences are examined in order to enable the mapping of this divergent data into a homogeneous global schema that can more easily be used for big data analysis. Finally, some tools and industrial examples are given in order to demonstrate different approaches of heterogeneous data integration.

EGSO in need for a global schema

2002 ◽  
Author(s):  
Frank Hill ◽  
Andre Csillaghy ◽  
Robert D. Bentley ◽  
Jean Aboudarham ◽  
Ester Antonucci ◽  
...  
Keyword(s):  
Global Schema
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