Reverse engineering of relational databases: Extraction of an EER model from a relational database

1994 ◽  
Vol 12 (2) ◽  
pp. 107-142 ◽  
Author(s):  
Roger H.L. Chiang ◽  
Terence M. Barron ◽  
Veda C. Storey
Keyword(s):  
Reverse Engineering ◽  
Relational Database ◽  
Relational Databases

SEDRIS Transmittal Storing and Retrieval System using Relational Databases

2014 ◽  
Vol 25 (4) ◽  
pp. 38-65
Author(s):  
Yongkwon Kim ◽  
Heejung Yang ◽  
Chin-Wan Chung
Keyword(s):  
Complex Systems ◽  
Relational Database ◽  
Relational Databases ◽  
Data Representation ◽  
Environmental Data ◽  
Natural Phenomena ◽  
Type Conversion ◽  
Weather System ◽  
Relational Database System ◽  
Efficient Management

Modeling and simulation (M&S) are widely used for design, analysis, and optimization of complex systems and natural phenomena in various areas such as the defense industry and the weather system. In many cases, the environment is a key part of complex systems and natural phenomena. It includes physical aspects of the real world which provide the context for a specific simulation. Recently, several simulation systems are integrated to work together when they have needs for exchanging information. Interoperability of heterogeneous simulations depends heavily on sharing complex environmental data in a consistent and complete manner. SEDRIS (Synthetic Environmental Data Representation and Interchange Specification) is an ISO standard for representation and interchange of environmental data and widely adopted in M&S area. As the size of the simulation increases, the size of the environmental data which should be exchanged between simulations increases. Therefore, an efficient management of the environmental data is very important. In this paper, the authors propose storing and retrieval methods of SEDRIS transmittals using a relational database system in order to be able to retrieve data efficiently in the environmental data server cooperating with many heterogeneous distributed simulations. By analyzing the structure and the content of SEDRIS transmittals, relational database schemas are designed. To reduce query processing time of SEDRIS transmittals, direct storing and retrieval methods which do not require the type conversion of SEDRIS transmittals are proposed. Experimental analyses are conducted to show the efficiency of the proposed approach. The results confirm that the proposed approach greatly reduces the storing time and retrieval time compared to comparison approaches.

Object-Relational Modeling

2009 ◽  
pp. 162-170
Author(s):  
Jaroslav Zendulka
Keyword(s):  
Relational Database ◽  
Relational Databases ◽  
Conceptual Modeling ◽  
Object Oriented ◽  
Database Systems ◽  
Object Relational ◽  
The Difference ◽  
Object Oriented Approach ◽  
Entity Relationship ◽  
Oriented Approach

Modeling techniques play an important role in the development of database applications. Well-known entity-relationship modeling and its extensions have become a widely-accepted approach for relational database conceptual design. An object-oriented approach has brought a new view of conceptual modeling. A class as a fundamental concept of the object-oriented approach encapsulates both data and behavior, whereas traditional relational databases are able to store only data. In the early 1990s, the difference between the relational and object-oriented (OO) technologies, which were, and are still used together to build complex software systems, was labeled the object-relational impedance mismatch (Ambler, 2003). The object-oriented approach and the need of new application areas to store complex data have greatly influenced database technology since that time. Besides appearance of object-oriented database systems, which fully implement objectoriented paradigm in a database environment (Catell et al., 2003), traditional relational database management systems become object-relational (Stonebraker & Brown, 1999). The most recent versions of the SQL standard, SQL: 1999 (Melton & Simon (2001) and SQL: 2003 (Eisenberg et al., 2004), introduced object-relational features to the standard and leading database producers have already released packages which incorporate them.

From Databases to Ontologies

2009 ◽  
pp. 2360-2383
Author(s):  
Guntis Barzdins ◽  
Janis Barzdins ◽  
Karlis Cerans
Keyword(s):  
Conceptual Model ◽  
Relational Database ◽  
Relational Databases ◽  
Database Design ◽  
Database Schema ◽  
Design Problems ◽  
Uml Profile ◽  
Domain Experts ◽  
Owl Ontology ◽  
Rdf Database

This chapter introduces the UML profile for OWL as an essential instrument for bridging the gap between the legacy relational databases and OWL ontologies. We address one of the long-standing relational database design problems where initial conceptual model (a semantically clear domain conceptualization ontology) gets “lost” during conversion into the normalized database schema. The problem is that such “loss” makes database inaccessible for direct query by domain experts familiar with the conceptual model only. This problem can be avoided by exporting the database into RDF according to the original conceptual model (OWL ontology) and formulating semantically clear queries in SPARQL over the RDF database. Through a detailed example we show how UML/OWL profile is facilitating this new and promising approach.

An Evaluation of Dynamic Electronic Catalog Models in Relational Database Systems

2011 ◽  
pp. 73-90 ◽  
Author(s):  
Kiryoong Kim ◽  
Dongkyu Kim ◽  
Jeuk Kim ◽  
Sang-uk Park ◽  
Ighoon Lee ◽  
...  
Keyword(s):  
Electronic Commerce ◽  
Relational Database ◽  
Relational Databases ◽  
Database Systems ◽  
Relational Schemas ◽  
Electronic Catalogs ◽  
Electronic Catalog ◽  
Software Product ◽  
New Models ◽  
Relational Database Systems

Electronic catalogs are electronic representations about products and services in the electronic commerce environment and require diverse and flexible schemas. Although relational database systems seem to be an obvious choice for their storage, traditional designs of relational schemas do not support electronic catalogs in the most effective ways. Therefore, new models for managing diverse and flexible schemas in relational databases are required for such systems. Proposed in this paper are several models for electronic catalogs using relational tables, and an experimental evaluation of their efficiency. The results of this study can be put to practical use and are, in fact, being applied in the design of a commercial software product.

A novel method for providing relational databases with rich semantics and natural language processing

2017 ◽  
Vol 30 (3) ◽  
pp. 503-525
Author(s):  
Kamal Hamaz ◽  
Fouzia Benchikha
Keyword(s):  
Natural Language ◽  
Data Storage ◽  
Language Processing ◽  
Relational Database ◽  
Relational Databases ◽  
Data Access ◽  
New Techniques ◽  
Content Type ◽  
Semantic Tree ◽  
Novel Method

Purpose With the development of systems and applications, the number of users interacting with databases has increased considerably. The relational database model is still considered as the most used model for data storage and manipulation. However, it does not offer any semantic support for the stored data which can facilitate data access for the users. Indeed, a large number of users are intimidated when retrieving data because they are non-technical or have little technical knowledge. To overcome this problem, researchers are continuously developing new techniques for Natural Language Interfaces to Databases (NLIDB). Nowadays, the usage of existing NLIDBs is not widespread due to their deficiencies in understanding natural language (NL) queries. In this sense, the purpose of this paper is to propose a novel method for an intelligent understanding of NL queries using semantically enriched database sources. Design/methodology/approach First a reverse engineering process is applied to extract relational database hidden semantics. In the second step, the extracted semantics are enriched further using a domain ontology. After this, all semantics are stored in the same relational database. The phase of processing NL queries uses the stored semantics to generate a semantic tree. Findings The evaluation part of the work shows the advantages of using a semantically enriched database source to understand NL queries. Additionally, enriching a relational database has given more flexibility to understand contextual and synonymous words that may be used in a NL query. Originality/value Existing NLIDBs are not yet a standard option for interfacing a relational database due to their lack for understanding NL queries. Indeed, the techniques used in the literature have their limits. This paper handles those limits by identifying the NL elements by their semantic nature in order to generate a semantic tree. This last is a key solution towards an intelligent understanding of NL queries to relational databases.

Migration from a Relational Database to NoSQL

2018 ◽  
Vol 8 (3) ◽  
pp. 63-80
Author(s):  
Samah Bouamama
Keyword(s):  
Relational Database ◽  
Database Management ◽  
Relational Databases ◽  
New Technologies ◽  
Management Tools ◽  
Nosql Databases

This article describes how due to the monstrous evolution of the technology and the enormous increase in data, it becomes difficult to work with traditional database management tools; relational databases quickly reach their limits and adding servers does not increase performance. As a result of this problem, new technologies have emerged, such as NoSQL databases, which radically change the architecture of the databases that the authors are used to seeing, thus increasing the performance and availability of services. As these technologies are relatively new, standard or formal migration processes do not yet exist, the authors thought it useful to propose a migration approach from a relational database to a database-oriented columns type HBase and Cassandra.

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