A taxonomy and current issues in multidatabase systems

Bright, M. W.; Hurson, Ali R.; Pakzad, S. H.

doi:10.1109/2.121509

Cited by 165 publications

(76 citation statements)

References 17 publications

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“…As a consequence, the interest here is to combine all information in a maximal firstorder theory. Such a setting occurs, amongst others, in heterogeneous databases [7]. A third type of information fusion deals with the case where each source provides knowledge by means of a possibility distribution (see, e.g., [38,19]).…”

Section: Merging Of Coreferent Datamentioning

confidence: 99%

Automated Cleansing of POI Databases

Tré

Britsom

Matthé

et al. 2013

Intelligent Systems Reference Library

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In the context of geographic information systems (GIS), points of interest (POIs) are descriptions that denote geographical locations which might be of interest for some user purposes. Examples are public transport facilities, historical buildings, hotels and restaurants, recreation areas, hospitals etc. Because information gathering with respect to POIs is usually resource consuming, the user community is often involved in this task. In general, POI data originate from different sources (or users) and are therefore vulnerable to imperfections which might have a negative impact on data quality. Different POIs referring to, or describing the same physical geographical location might exist. Such POIs are said to be coreferent POIs. Coreferent POIs must be avoided as they could harm the data(base) quality and integrity. In this chapter, a novel soft computing technique for the (semi-)automated cleansing of POI databases is proposed. The proposed technique consists of two consecutive main steps: the detection of collections of coreferent POIs and the fusion, for each collection, of all coreferent POIs into a single consistent POI that represents all the POIs in the collection. The technique is based on fuzzy set theory, whereas possibility theory is used to cope with the uncertainties in the data. It can be used as a component of (semi-)automated data quality improvement strategies for databases and other information sources.

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Section: Merging Of Coreferent Datamentioning

confidence: 99%

Automated Cleansing of POI Databases

Tré

Britsom

Matthé

et al. 2013

Intelligent Systems Reference Library

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“…A lot of research in the past focuses on developing methodologies for querying heterogeneous data sources. Integration data from existing databases in a distributed environment will give the impact of operations on the databases [14]. One of the approaches in database integration is unified global integration [2].…”

Section: Literature Reviewmentioning

confidence: 99%

Architecture for Accessing Heterogeneous Databases

Yusof

Abidin²,

Rahman³

2012

IJITCS

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Abstract-This paper presents the architecture for accessing heterogeneous databases. Two major processes in this architecture which are extracting SQL statement and ontology. The algorithms for extracting SQL statement was created and tested in order to improve time performance during searching and retrieving process. Ontology approach was implemented and combined with these algorithms. In ontology approach, web semantic was implemented in order to retrieve only relevant data from database. A prototype based on this architecture was developed using JAVA technology. JAVA technology was chosen because this technology have Jena library. This library is provide API and support SPARQL. Several experiments have been executed and tested. The result indicates this architecture able to improve web query processing in term of time. The result also indicates this architecture able to retrieve and displayed more relevant data to web users.

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“…A multidatabase system (MDBS) is a database system that resides on top of existing local autonomous component databases systems (CDBSs) and presents a single database to its users [1]. MDBS usually maintains a single global database schema [1], which is integration of all local component database schemas.…”

Section: Introcuctionmentioning

confidence: 99%

“…MDBS usually maintains a single global database schema [1], which is integration of all local component database schemas. In this paper we do not discuss on local schemas integration.…”

Section: Introcuctionmentioning

confidence: 99%

Local Schemas Modifications Propagation and Maintenance of Metadata in Multidatabase System

Ali¹

2010

IJCA

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One of the challenging problems in the multidatabase systems is to find the most viable solution to the problem of interoperability of distributed heterogeneous autonomous local component databases. This has resulted in the creation of a global schema over set of local component database schemas to provide a uniform representation of local schemas. The main objective of this paper is to maintain the Global Schema and the Global Directory/Dictionary/Metadata as the local schemas are autonomous and evolve over time. In this paper we consider uniform object-oriented data models which is used during integration of different heterogeneous distributed databases from different data models and proposed a framework to maintain an objected-oriented Global Schema in the multidatabase system.The Bottom up local schema modifications propagation in the Global schema is proposed and during this process the Global Directory/Dictionary/Metadata is maintained without manual intervention.

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A taxonomy and current issues in multidatabase systems

Cited by 165 publications

References 17 publications

Automated Cleansing of POI Databases

Automated Cleansing of POI Databases

Architecture for Accessing Heterogeneous Databases

Local Schemas Modifications Propagation and Maintenance of Metadata in Multidatabase System

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