Object-relational Database Research Articles

Model Object Relational Database pada Aplikasi Notifikasi Sms

The purpose of this research is to analyse the database using object oriented approach. In addition, this research develops and designs an object relational database structure to make easier the process of searching for the required information. The benefit of this research is to provide a data structure that can be reused for SMS notification application developer team, so that the developers can use existing objects for future use if there are changes in the current business process. The methods used are data collection, analysis, and design. The result obtained from this research is a database structure of sms notification application, which can be used in various programming languages for using object relational database approach. For conclusion, by using the object relational database structure, application developers will be made easier in developing the current database structure. Programmer can add a new data type simply by creating a new object. Data is accessed or processed as object-oriented.

Graphic Logical Desing for ORDB

This paper presents a model to graphic logical design to Object Relational Database (ORDB). The model proposed allowed mapping from UML class diagram (conceptual model) to elements of an ORDB. It is possible to create a graphic logical model to ORDB. Since version's 1999 ORDBs had presented new elements that can be used for represent object's application in databases. However is necessary to have a model to represent a conceptual model in the object-relational logic model. The model here proposed is based on the other previews works and the differences are discussed. This article introduces an extension made in ArgoUML tool that permits developer to build graphic logical schemas to ORDBs. The professionals can use this tool in your projects. We intend that ORDB can effectively be used in corporates.

An object-relational spatio-temporal geoscience data model

A model for spatially and temporally indexed multi-dimensional geoscience data has been developed by first embedding a combinatorial topological model in terms of G-Maps in the domain Rm×Time(m∈N), and then converting it into an object-relational model which can easily be implemented in an object-relational database system.Geoscience objects referring to space and time often have complex geometries which are usually partitioned into simpler cells and have geometrical, topological, geological, geophysical, geochemical and other relevant properties assigned to their cells. These objects may exist in a Euclidean space Rm of arbitrary dimension m depending on which properties are chosen as “coordinates”, where usually m=3 and refers to three spatial dimensions, and evolve in one dimensional valid time (Time). The valid time is independent of geometry, topology and properties but not vice versa, i.e., the geometry of an object, for example, and all its properties are modeled as functions of the valid time. Then the objects are assumed to be sampled at arbitrary but fixed instances of time, and their evolution between these instances is modeled by appropriate interpolation. The structure of the data model is well adapted to the interpolation required to represent the objects in between the instances of their observation.The data model provides the basis prerequisite of our envisioned spatio-temporal geoscience information system.

Adapting transformations to metamodel changes via external transformation composition

Evolution is inherent to software systemsbecause of the rapid improvement of technologies and business logic. As a software development paradigm, model driven engineering (MDE) is also affected by this problem. More concretely, being metamodels the cornerstone of MDE, their evolution impacts the rest of software artefacts involved in a development process, i.e., models and transformations. The influence over models has been tackled and partially solved in previous works. This paper focuses on the impact over transformations. We propose an approach to adapt transformations by means of external transformation composition. That is, we chain impacted transformations to particular adaptation transformations which deal with either refactoring/destruction changes or construction changes. Our approach semi-automatically generates such transformations by using the AtlanMod matching language, a DSL to define model matching strategies. To provide with a proof of concept for our proposal, we adapt transformations written in terms of object-relational database metamodels when such metamodels evolve in time.

Selection of databases for real estate information systems

The objective of the article is to scrutinise the types of databases and to choose the most appropriate one for property markets computing systems. The problems of the property markets analysis and valuation were characterised and the types of systems that should be created were presented as well. Two types of systems emphasized in the article should be a part of property market`s computing systems. These are: a system of monitoring and analyzing the overall situation in the real estate market (M-A System), an expert system that is designed for the local market analysis and valuation of real estate in the local market (REE system - Real Estate Expert System). The problem is presented at the databases point of view. The characteristics of various types of databases were described taking into account their usefulness and it was decided which of them has the broadest range of application. Analysis has covered: relational databases, object-oriented databases, object-relational databases and a NoSQL databases. For M-A system, a NoSQL type of database was proposed, whereas for the REE system object-relational database or object database.

The Value of a Bounding Box: Moving Historical Charts beyond the Image Browser

The National Oceanic and Atmospheric Administration's (NOAA's) Historical Map and Chart Collection is a showcase of the Office of Coast Survey's (OCS's) rich and lengthy history. It is a digital collection of scanned maps and charts, including OCS's early scientific publications, as well as more modern nautical chart products. Its contents are freely available for searching, previewing, and downloading over the Internet. This article will explore our recent experiences managing the collection, which has been growing in stages since 1997. In order to move the access point for these charts beyond simple keyword searching and image browsing, we had to grapple with past practice and improve upon prior methods of collecting and managing geographic information. This process required a thorough understanding of the collection's contents, as well as the ability to consistently interpret geographic information from various cartographic representations. Once the geographic information was transitioned to an object-relational database management system, a user-friendly search interface capable of producing relevant results by geographic query became possible.

웹 응용 시스템 개발을 위한 보안을 고려한 통합 분석·설계 방법론 개발 - Oracle11g를 중심으로 -

응용 시스템 개발 과정에 있어서 중요하고 핵심을 이루는 작업은 분석과 설계 작업이며 아울러 대부분의 응용 시스템은 데이터베이스 기반으로 구축된다. 또한, IT 시스템들 간 상호 연결이 증가되면서 응용 시스템들은 외부공격에 쉽게 노출되어 지고 있기 때문에 보안과 관련된 처리 과정 역시 중요하다. 보안은 시스템에서 많은 부분과 상호작용을 하는 복잡한 비기능적 요구사항이다. 하지만 이러한 보안은 대부분 개발 마지막 과정에서 고려하기 때문에 보안에 취약한 응용 시스템이 개발될 가능성이 매우 높다. 따라서 개발 초기에 보안을 반영한 분석 및 설계 과정이 매우 중요하다. J2EE는 웹 응용 시스템을 위한 보안 방안을 제공하고, 아울러 객체-관계형 데이터베이스도 보안을 위하여 역할기반 접근제어를 지원하고 있지만 객체-관계형 데이터베이스 및 J2EE의 역할기반 접근제어를 활용하는, 요구사항 수집부터 구현까지 개발 단계 전체에 걸친 보안을 고려한 일관된 개발방법론은 전무한 실정이다. 따라서 본 논문에서는 보안 요구사항을 요구사항 수집부터 분석 및 설계 그리고 마지막 구현 단계까지 반영하여 J2EE 기반의 웹 응용 시스템을 개발하기 위한, 보안을 고려한 일관된 통합 분석 설계 방법론을 제안한다. In the development process of application systems, the most important works are analysis and design. Most of the application systems are implemented on database system. So, database design is important. Also, IT System are confronted with more and more attacks by an increase interconnections between IT systems. Therefore security-related processes belong to a very important process. Security is a complex non-functional requirement that can interaction of many parts in the system. But Security is considered in the final stages of development. Therefore, Their increases the potential for the final product to contain vulnerabilities. Accordingly, Early in development related to security analysis and design process is very important. J2EE gives a solution based on RBAC((Role Based Access Control) for security and object-relational database also has RBAC for security. But there is not a object-oriented analysis and design methodology using RBAC of J2EE and object-relational database for security. In this paper, the unified object-oriented analysis and design methodology is developed for security-critical web application systems based on J2EE and object-relational database. We used UMLsec and RBAC of object-relational database and J2EE for this methodology.

On the Use of a Fuzzy Object-Relational Database for Flexible Retrieval of Medical Images

This paper introduces a novel approach to medical image retrieval using a fuzzy object-relational database management system (FORDBMS). The system stores medical images along with information about the content of the image, such as the presence or absence of certain indicators of pathologies. It allows us to flexibly retrieve them on the basis of these indicators, making it possible to obtain images from patients with similar diagnosis and thus, following a common visual pattern. To illustrate the capabilities of the FORDBMS, this paper focuses on X-ray images of patients suffering from scoliosis (a medical condition in which the patient's spine is curved) from which spine descriptions are obtained. Then queries are performed to obtain a set of images with a certain curvature pattern. Results show high accuracy when evaluated by medical experts. Compared with other ad hoc content-based image retrieval systems, the one presented here is easily adaptable to other application domains, customizable, and very scalable.

Comparative Study on Object Persistence Methods

In last few decades there was rapid shift observed while writing software solutions. Object oriented model is now globally adapted and preferred by most of the application developers. Object persistence plays a key role in designing data model, business objects working with other business objects. Object persistence could be very efficient if designed correctly. A typical design leads extra overheads in terms of cost, resource utilization, and time. Considering the importance of object persistence, it is very essential to concentrate more on this area. Gateway-based, Objectrelational database and Object-oriented Database are the three major groups of solutions available to implement object persistence. In this paper, we discuss about the features available in Object Persistence methodologies, how and where we should use them efficiently based on the application requirements. Our discussion continues further on positive and negative sides of object persistence methodologies by considering limitations and different application requirements.

Efficient processing of probabilistic set-containment queries on uncertain set-valued data

Set-valued data is a natural and concise representation for modeling complex objects. As an important operation of object-oriented or object-relational database, set containment query processing over set-valued data has been extensively studied in previous works. Recently, there is a growing realization that uncertain information is a first-class citizen in modern database management. As such, there is a strong demand for study of set containment queries over uncertain set-valued data.This paper investigates how set-containment queries over uncertain set-valued data can be efficiently processed. Based on the popular possible world semantics, we first present a practical model in which the uncertainty in set-valued data is represented by existential probabilities, and propose the probabilistic set containment semantics and its generalization – the expected Jaccard containment. Second, to avoid expensive computations in enumerating all possible worlds, we develop efficient schemes for computing these two probabilistic semantics. Third, we introduce two important queries, namely probability threshold containment query (PTCQ) and probability threshold containment join (PTCJ), and propose novel techniques to process them efficiently. Finally, we conduct extensive experiments to study the efficiency of the proposed methods. The experimental results indicate that the proposed methods are efficient in processing the uncertain set containment queries.

Research of Security Mechanisms Based on LogicSQL Database

LogicSQL is an object relational database management system implemented with the advanced (formula-lock based) concurrency control protocol, and the steged database architecture. It is independently developed based on the Linux high-level security database system. Ministry of Science and Technology "863" Database Group of the major projects comments LogicSQL database "It is the only hope that China’s database products will be able to contend with America’s mainstream database products in the next few years." Access control policies are security policies that govern access to resources. It can be applied to several new types of databases. In this paper, we discuss access control in multilevel database management systems applies and illustrate the main applies of security mechanisms in the LogicSQL database system.

Data mining: concepts and techniques

The increasing volume of data in modern business and science calls for more complex and sophisticated tools. Although advances in data mining technology have made extensive data collection much easier, it's still always evolving and there is a constant need for new techniques and tools that can help us transform this data into useful information and knowledge. Since the previous edition's publication, great advances have been made in the field of data mining. Not only does the third of edition of Data Mining: Concepts and Techniques continue the tradition of equipping you with an understanding and application of the theory and practice of discovering patterns hidden in large data sets, it also focuses on new, important topics in the field: data warehouses and data cube technology, mining stream, mining social networks, and mining spatial, multimedia and other complex data. Each chapter is a stand-alone guide to a critical topic, presenting proven algorithms and sound implementations ready to be used directly or with strategic modification against live data. This is the resource you need if you want to apply today's most powerful data mining techniques to meet real business challenges. * Presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projects. * Addresses advanced topics such as mining object-relational databases, spatial databases, multimedia databases, time-series databases, text databases, the World Wide Web, and applications in several fields. *Provides a comprehensive, practical look at the concepts and techniques you need to get the most out of real business data

Storing XML Data – The ExDB and CellStore Way in the Context of Current Approaches

In this paper we describe possible approaches how to store XML data, which is a key aspect for their further processing. One popular technique for managing XML data is to map the data to an existing database system, e.g., to the relational or object-relational database management system. We describe possible ways how to store XML data in relational databases, because relational systems are still widely used for various purposes, including XML data management. But XML data are trees, not tables, so the main focus of this article is oriented to native XML databases. We describe general properties of such kind of databases and, in particular, explain possible solutions on two experimental native XML database management systems – ExDB and CellStore. Both have been proposed, implemented and optimized in our research groups in recent years for experimental purposes.

O-ODM Framework for Object-Relational Databases

Object-Relational Databases introduce new features which allow manipulating objects in databases. At present, many DBMS offer resources to manipulate objects in database, but most application developers just map class to relations tables, failing to exploit the O-R model strength. The lack of tools that aid the database project contributes to this situation. This work presents O-ODM (Object-Object Database Mapping), a persistent framework that maps objects from OO applications to database objects. Persistent Frameworks have been used to aid developers, managing all access to DBMS. This kind of tool allows developers to persist objects without solid knowledge about DBMSs and specific languages, improving the developers' productivity, mainly when a different DBMS is used. The results of some experiments using O-ODM are shown.

Enabling Semantic Queries Against the Spatial Database

The spatial database based upon the object-relational database management system (ORDBMS) has the merits of a clear data model, good operability and high query efficiency. That is why ...

On Modeling the Behavior of Comparators for Complex Fuzzy Objects in a Fuzzy Object-Relational Database Management System

Abstract This paper proposes a parameterized definition for fuzzy comparators on complex fuzzy datatypes like fuzzy collections with conjunctive semantics and fuzzy objects. This definition and its implementation on a Fuzzy Object-Relational Database Management System (FORDBMS) provides the designer with a powerful tool to adapt the behavior of these operators to the semantics of the considered application.

A user-defined data type for the storage of time series data allowing efficient similarity screening

The volume of the experimentally measured time series data is rapidly growing, while storage solutions offering better data types than simple arrays of numbers or opaque blobs for keeping series data are sorely lacking. A number of indexing methods have been proposed to provide efficient access to time series data, but none has so far been integrated into a tried-and-proven database system. To explore the possibility of such integration, we have developed a data type for time series storage in PostgreSQL, an object-relational database system, and equipped it with an access method based on SAX (Symbolic Aggregate approXimation). This new data type has been successfully tested in a database supporting a large-scale plant gene expression experiment, and it was additionally tested on a very large set of simulated time series data.

Comparing and Choosing Appropriate Database for Storing Context in Context Aware System

Problem statement: The databases introduce the digital era the fact that requirement to maintain large and ample data. The growth of information development and improvement that pursued it transformed the databases into a global reality. This study enquired and described the vital role of storing the context data to an appropriate database in the area of context aware computing. It also addson limitations of the existing relational and object relational databases with respect to context aware computing. Approach: This article examines traditional database like relational database, object relational database and spatial database. It helps to make an optimal decision while choosing the database for context aware applications. Results: All the traditional databases are compared with context aware features like semantic support, ease of transaction of large data, query optimization, reasoning support, formality, scalability, spatial data and xml support. Conclusion: This study confirmed that using object relational database along with ontology is more apt for storing the context data for context aware computing applications.

An Object-Oriented Modeling and Implementation of Spatio-Temporal Knowledge Discovery System

Spatiotemporal databases deal with changes to spatial objects with time. The Spatiotemporal knowledge discovery process involves the integration of such database systems with data warehousing, data mining and online-analytical processing technologies. The applications in this domain will process spatial, temporal and attribute data elements and use spatio-temporal relationships among these elements. These applications deal with the evolution of spatial objects and changes in their topological relationships, associations along with time. These advanced database applications require storing, management and processing of complex spatiotemporal data. In this paper we consider the classification and modeling requirements for spatiotemporal applications, System modeling, preprocessing spatiotemporal data, discovering spatiotemporal topological relationships and extension of apriori algorithm for mining spatiotemporal frequent predicates. The design of an appropriate system that can capture spatiotemporal features of datasets is discussed. Prototype implementation of the system is carried out on top of open source object relational spatial database management system called postgresql and postgis. The algorithms are experimented on historical cadastral datasets which are created using OpenJump. The results that are visualized using OpenJump software are presented.

Object-Relational Database Based Category Data Model for Natural Language Interface to Database

Domain specific question answering technique allows users to use natural language to express their queries so that users need not have the knowledge about the structures of the information source. For such an application relational model is not suitable as it is not a natural way to represent real world knowledge. Using relational model for representing information source results in scattered relations of data about the real world objects. In this paper an effective category model is presented to organize information according to their contents based on object-relational database. For the discussion of the category model railway domain is used in the paper.