scholarly journals Commutative encryption: an answer to privacy protected query processing of multi data sources

2020 ◽  
Vol 4 (3) ◽  
pp. 170
Author(s):  
Subrata Bose
Keyword(s):  
Query Processing ◽  
Data Sources

Integrating distributed data sources with OGSA–DAI DQP and V iews

2010 ◽  
Vol 368 (1926) ◽  
pp. 4133-4145 ◽  
Author(s):  
Bartosz Dobrzelecki ◽  
Amrey Krause ◽  
Alastair C. Hume ◽  
Alistair Grant ◽  
Mario Antonioletti ◽  
...  
Keyword(s):  
Data Integration ◽  
Query Processing ◽  
Data Access ◽  
Data Sources ◽  
Distributed Data ◽  
Grid Services ◽  
Distributed Query Processing ◽  
Processing Resource ◽  
Distributed Query ◽  
Open Grid Services Architecture

OGSA-DAI (Open Grid Services Architecture Data Access and Integration) is a framework for building distributed data access and integration systems. Until recently, it lacked the built-in functionality that would allow easy creation of federations of distributed data sources. The latest release of the OGSA-DAI framework introduced the OGSA-DAI DQP (Distributed Query Processing) resource. The new resource encapsulates a distributed query processor, that is able to orchestrate distributed data sources when answering declarative user queries. The query processor has many extensibility points, making it easy to customize. We have also introduced a new OGSA-DAI V iews resource that provides a flexible method for defining views over relational data. The interoperability of the two new resources, together with the flexibility of the OGSA-DAI framework, allows the building of highly customized data integration solutions.

Quality-Extended Query Processing for Mediation Systems

2011 ◽  
pp. 23-50
Author(s):  
Laure Berti-Equille
Keyword(s):  
Quality Of Service ◽  
Query Processing ◽  
Query Language ◽  
Data Sources ◽  
Distributed Data ◽  
Quality Of Data ◽  
Adaptive Query Processing ◽  
Research Perspectives ◽  
Language Extension

For non-collaborative distributed data sources, quality-driven query processing is difficult to achieve because the sources generally do not export data quality indicators. This chapter deals with the extension and adaptation of query processing for taking into account constraints on quality of distributed data. This chapter presents a novel framework for adaptive query processing on quality-extended query declarations. It proposes an expressive query language extension combining SQL and QML, the Quality of service Modeling Language proposed by Frølund and Koistinen (1998) for defining in a flexible way dimensions, and metrics on data, sources and services quality. The originality of the approach is to include the negotiation of quality contracts between the distributed data sources competing for answering the query. The principle is to find dynamically the best trade-off between the local query cost and the result quality. The author is convinced that quality of data (QoD) and quality of service (QoS) can be advantageously conciliated for tackling the problems of quality-aware query processing in distributed environments and more generally, that opens innovative research perspectives for quality-aware adaptive query processing.

UPDATE TRANSLATION IN INSTANCE MAPPED HETEROGENEOUS PEER DATABASES

2011 ◽  
Vol 05 (02) ◽  
pp. 211-234
Author(s):  
MEHEDI MASUD ◽  
ILUJU KIRINGA
Keyword(s):  
Query Processing ◽  
Data Sharing ◽  
Real World ◽  
Data Sources ◽  
View Maintenance ◽  
Local Database ◽  
Update Propagation ◽  
Translation Mechanism ◽  
Maintenance Problem

In data sharing systems, peers are acquainted through pair-wise data sharing settings/mappings for sharing and exchanging data. Besides query processing, supporting update exchange for interchanging data between peers is one of the challenging problems in data sharing systems. In update exchange, an update action posed to a peer is applied to the peer's local database instance and then the update is propagated to the related peers. Previous work on update exchange have considered update propagation considering schema-level mappings between peers, which are conceptually similar to the view maintenance problem. However, there are data sharing systems, where peers are acquainted by instance-level mappings. In such a system, peers use different schemas and data vocabularies to represent semantically same real world entities. The instance-level mappings express how data in one peer relate to data in another peer. One of the problems in exchanging updates in instance-mapped data sharing systems is to translate updates correctly between heterogeneous peers. The translation should be such that insertions, deletions, and modifications of the tuples made by an update in a peer and by the translated version of the update in an acquainted peer are related through the mappings between them. In this paper, we investigate such a mechanism for translating update actions between heterogeneous peer data sources. Before discussing the translation mechanism, the paper first formalize the notion of update translation and derive conditions under which the translation mechanism will produce correct translations of updates.

Query Processing in a Mediator Based Framework for Linked Data Integration

2013 ◽  
pp. 98-116 ◽  
Author(s):  
Vânia M. P. Vidal ◽  
José A. F. de Macêdo ◽  
João C. Pinheiro ◽  
Marco A. Casanova ◽  
Fábio Porto
Keyword(s):  
Data Integration ◽  
Query Processing ◽  
Linked Data ◽  
Domain Ontology ◽  
Data Sources ◽  
User Query ◽  
Application Ontology ◽  
Data Source ◽  
Virtual Store ◽  
The Web

In this paper, the authors present a three-level mediator based framework for linked data integration. In the approach, the mediated schema is represented by a domain ontology, which provides a conceptual representation of the application. Each relevant data source is described by a source ontology, published on the Web according to the Linked Data principles. Each source ontology is rewritten as an application ontology, whose vocabulary is restricted to be a subset of the vocabulary of the domain ontology. The main contribution of the paper is an algorithm for reformulating a user query into sub-queries over the data sources. The reformulation algorithm exploits inter-ontology links to return more complete query results. The approach is illustrated by an example of a virtual store mediating access to online booksellers.

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