Relational, Object-Oriented and Object-Relational Data Models

A database management system (DBMS) should provide capabilities for defining and enforcing certain integrity constraints that must hold for the data recorded in the database. These constraints are derived from the semantics of the data and from the rules of the system under study (SuS) that database represents. Every DBMS is based on a data model that provides the means to achieve data abstraction and to express database schema. Each data model has a specific set of integrity constraints types. Some of constraint types are common for several data models and some of them are typical for a data model. Beyond well-known constraint types there are more complex ones that are difficult to express and enforce within the data model. In this paper we deal with the extended tuple constraint (ETC) type. It is the extension of tuple constraint that is one of constraint types of relational data model. In this paper we explain the usage of extended tuple constraint in relational data model and its implementation in relational DBMSs. XML data model does not recognize ETC type. We specify the extended tuple constraint in XML data model and propose two techniques for implementation of ETC in XML DBMSs. Each of them depends on the characteristics of a selected XML DBMS. We use XQuery functions in eXist DBMS, and triggers in Sedna DBMS.

Two major techniques commonly available for modeling genomic data are the relational and object oriented approaches. This paper discusses the strengths and weaknesses of both approaches. The comparison was done using two sets of disparate genomic data, one for the E. Coli genome and one for the human genome, in order to demonstrate the generality of the modeling methods and the credibility of the comparison itself. One major strength of the object-oriented approach is its highly flexible data modeling power offering an elegant way of representing complex genomic objects. The approach's major weakness includes the lack of generic way of accessing complex objects. The strength of the relational approach is its full provision of SQL. But the approach's weakness is cumbersome modeling of complex genomic objects that is due to normalization. This paper also includes discussions on broader issues related to the two alternative approaches such as support for ad hoc queries and a federation of heterogeneous genomic databases in which both relational and object-oriented data models are used. >

Developing a three-dimensional (3D) data model for Geographic Information Systems (GIS) is an essential and complex issue. 3D modelling in GIS is becoming ever more important for the development of cyber cities and digital earth, which have recently become feasible. A competent 3D model forms an efficient foundation for 3D visualization, query and spatial analysis. As a development of the existing 3D models, this study proposes particular improvements in handling complex 3D objects. We present an object-oriented data model for handling complex 3D objects in GIS. First, the conceptual data model is developed based on the principle of object-oriented (OO) data modelling. This model is designed based on the following three basic geometric elements: node, segment and triangle. Accordingly, the abstract geometric objects are defined: including points, lines, surfaces and volumes. Second, the corresponding 3D logical model is designed based on the defined abstract objects and the relationships between them. Third, a formal representation of the 3D spatial objects is described in detail. Fourth, a prototype 3D GIS is developed based on the proposed 3D data model. Finally, we describe the results of an experimental study to reconstruct 3D objects using this 3D GIS and a comparison with the performance of other 3D data models. The proposed model is able to handle complex objects, such as complex buildings and TV towers, which is an essential functionality for building large-scale cyber cities, such as for Hong Kong. The proposed data model proves to be very efficient, particularly in visualization and rendering. The experimental results show which the data volume of the proposed model is compacted and the visualization speed for 3D objects is improved, compared with the existing models.

A bi-level object-oriented data model together with a user query language called OFQL is designed which can support applications like GIS (geographic information systems). The data model is divided into two layers, the higher-level data model and the lower-level data model. The higher-level data model or the geographic object data model primarily consists of the geographic objects and a set of semantic spatial functions through which the topological relationships of the geographic objects are defined or derived. The lower-level data model or the geometric object data model has geometric objects which are the actual spatial representations of the geographic objects in the higher-level data model. It also has a set of geometric functions that retrieve, manipulate, and compute for geometric objects. The general architecture of a GIS system using this data modeling approach consists of two modules: the query processor and the function implementor. With the OFQL user-interface, the user is able to pose queries of a geographic nature without knowing the details of the spatial representation and computation of the geographic objects.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

An object-oriented approach to modeling financial accounting systems

To deal with issues of data model transformation and to make combined use of different data models, this paper proposed a database reengineering scheme which includes schema translation and data conversion from object-oriented data model to flattened XML data model with is-a and cardinality data semantics preservation. In this paper, conceptual schema of object-oriented data model and flattened XML data model are elaborated by UML class diagram and XML Schema Definition(XSD) graph respectively. Logical schema is described by UNISQL class definition and XSD respectively. This paper firstly analyzes class definitions from OODB and sorts them from most independent classes to most dependent classes. Secondly schema translation is processed by mapping class to complexType and then creating element definitions in XSD file. Thirdly data conversion is processed automatically. Performance tests have shown that the proposed database reengineering scheme is reliable and efficient.

Current commercialized PDM tools have drawbacks in representing a variety of data types such as CAD data, images, audio, long text, etc. by relational data modeling. For this reason, object-oriented approaches have been suggested as an alternative. In this paper, using the object-oriented paradigm, an object-oriented data model for the PDM system is proposed. The scope of the modeling is limited to management information for drawings, parts, and product structure. Rumbaugh’s OMT (Object Modeling Technique) has been adopted for the system design. In the modeling, classes of data vault and workspace are taken into account for the review or approval of drawings and parts data based on the concurrent engineering concept. For parts and corresponding product structure, classes of phantoms, options, substitutes, etc. are added to the model. In addition, state transition and data flow diagrams are suggested based on the analysis of work and data flows of drawings and parts.KeywordsPDMobject-oriented modelingOMTconcurrent engineering

We propose relational data modeling as a tool for replacing the ad hoc and uncoordinated approaches commonly used throughout the social sciences to gather, store, and disseminate data. We demonstrate relational data modeling using global electoral and political institutional data. We define a relational data model as a map of concepts, their attributes, and the relationships between concepts developed using a formal language and according to a set of rules. To demonstrate the methodology, we design a simple relational data model of six concepts: countries, parties, elections, districts, institutions, and election results. Furthermore, we introduce a data model to solve the particularly vexing issue of party discontinuity (party splits, mergers, and alliances). We show how the solution facilitates computational tasks, such as the calculation of core measures of political phenomena (ex: electoral volatility). Ultimately, a relational data approach will play a central role in collective investments to develop advanced data capabilities, and thereby advance the accuracy, pace, and transparency of scholarship in the social sciences.

Class-centered data models, such as the object-oriented data model, are inadequate for supporting engineering design product models because of their lack of support for object evolution, schema evolution, and semantic and user-defined relationships. Description logic overcomes these limitations by providing constructs for intentional description of classes, relationships, and objects. By combining description logic with object-oriented modelling concepts, design product schemas and data can be uniformly represented and modified throughout the design process.

Most database models are extended to fuzzy database models for managing and retrieving imperfect information. In recent years, considerable attention was focused on the relational data model but more recently greater attention is being turned to the investigation of object-oriented data models. The incorporation of these research results into commercial relational databases management systems (RDBMS) has not as yet a reality. The main reason for this has to do with the rigidity/inflexibility of actual RDBMS. New generation object-oriented databases management systems (OODBMS) offer greater possibilities for incorporating imperfect information thanks to the reusability and extensibility properties of OODBMS. Strategic information systems of the 1990’s should be able to deal with nuanced information, i.e. imprecision, uncertainty, subjective characteristics of economic and sociological data. In this paper, we propose a solution for the representation of fuzzy information in an object-oriented environment. The solution offers facilities for defining membership functions necessary for managing fuzzy information and for retrieving objects close to an established profile in a complex objects base. The economic sciences serve as testing ground for these concepts.

Most data stream management systems are based on extensions of the relational data model and query languages, but rigorous analyses of the problems and limitations of this approach, and how to overcome them, are still wanting. In this article, we elucidate the interaction between stream-oriented extensions of the relational model and continuous query language constructs, and show that the resulting expressive power problems are even more serious for data streams than for databases. In particular, we study the loss of expressive power caused by the loss of blocking query operators, and characterize nonblocking queries as monotonic functions on the database. Thus we introduce the notion of NB -completeness to assure that a query language is as suitable for continuous queries as it is for traditional database queries. We show that neither RA nor SQL are NB -complete on unordered sets of tuples, and the problem is even more serious when the data model is extended to support order—a sine-qua-non in data stream applications. The new limitations of SQL, compounded with well-known problems in applications such as sequence queries and data mining, motivate our proposal of extending the language with user-defined aggregates (UDAs). These can be natively coded in SQL, according to simple syntactic rules that set nonblocking aggregates apart from blocking ones. We first prove that SQL with UDAs is Turing complete. We then prove that SQL with monotonic UDAs and union operators can express all monotonic set functions computable by a Turing machine ( NB -completeness) and finally extend this result to queries on sequences ordered by their timestamps. The proposed approach supports data stream models that are more sophisticated than append-only relations, along with data mining queries, and other complex applications.

Semantic and object-oriented data models, such as ER, OMT, IFO, and others, have been extensively used for modeling geographic applications. Despite their semantic expressiveness, such models present limitations to adequately model those applications, since they do not provide appropriate primitives for representing spatial data. This paper presents OMT-G, an object oriented data model for geographic applications. OMT-G provides primitives for modeling the geometry and the topology of spatial data, supporting different topological structures, multiple views of objects, and spatial relationships. OMT-G also includes tools to specify transformation processes and presentation alternatives, that allow, among many other possibilities, modeling for multiple representations and multiple presentations. In this way, it overcomes the main limitations of the existing models, thus providing more adequate tools for modeling geographic applications. A comparison with other data models is also presented in order to stress the main advantages of OMT-G.

Using an object-oriented approach to model multimedia data

An object wrapper [3,4] is a piece of middleware that provides an object view on top of a legacy database management system. But legacy database management systems such as relational database systems (RDS) and multidimensional database systems (MDS) [5,6,7] are different in many aspects from an Object-oriented Data Model. Among these aspects are semantic management, data structures and data types supported in these models. As a result, it is crucial to understand these data models in order to design and implement an efficient piece of middleware. In this paper, a short discussion of the real-world data modelling requirements is presented. Then, this is followed by a discussion on an Object View’s requirements. The third section of the paper presents the architecture of the Object-to-Multidimensional Mapping Engine (O-MME) [10,11,12,13,14,15,16,17,18,19]. A detail discussion on major interfaces and classes in the Object-to-Multidimensional mapping algorithm are presented next. Issues such as data type conversion and database language statements generation are discussed in this paper also. Finally, some performance issues are presented and future possible researches are outlined.KeywordsStructure Query LanguageMapping EngineCache ManagerBusiness ClassisRelational Database SystemThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

An increasing number of database management systems are expanding their functionality to work with various types of spatial data. This is true for both relational and NoSQL data models. The article describes the main features of those data models for which the functions of storing and processing spatial data are implemented. A comparative analysis of the performance of typical spatial queries for database management systems based on various data models, including multi-model ones, is carried out. The dataset on which the comparison is performed is presented in the form of three blocks of OpenStreetMap vector data for the territory of the Novosibirsk region. Based on the results of the study, recommendations are made on the use of certain data models, depending on the available data and the tasks to be solved.