Database Reengineering Scheme from Object-Oriented Model to Flattened XML Data Model

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>

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.

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.

There are only very few approaches to normalizing object-oriented data. In this paper we present an approach to normalization of the object-oriented conceptual model based on UML class diagrams. First part of the paper describes the current status in the area of formal methods used for object-oriented data modeling. Second part presents four normalization rules, which are based on own experience and modified Ambler-Beck approach. These normalization rules are introduced on an example. Our method has been used in education at several universities. It has been and is also used for database design in software development projects, which we carried out. Recently, development of the CASE tool based on this approach has been started.

Database system reengineering technique has been used to resolve the problem of converting from existing out-of-data database systems to new technique database systems in order to reduce the new system implementation cost. The technique consists of three parts: schema translation, data conversion, and program translation. The schema translation requires the transferring of existing database schema into the new database schema with better semantics. Recapturing the semantics is a complicated and difficult work. During the database design phase, the semantics has been lost from the conceptual data model to the logical data model. It is difficult to recapture it. After recapturing the semantics from the original conceptual database schema, we also need to have a sophisticated knowledge base to store the knowledge. The paper describes a new schema translation system, which can recapture the missing/hidden semantics of a database. The kernel of the system is an extended entity relationship (EER) data dictionary system (DDS), which can store all the semantics of the new database schema.

In this paper we present the Design History Data Model (DHDM), an extended object-oriented data model that explicitly supports the modeling and capture of engineering design histories. An engineering design history is a composite information structure that contains the evolution of engineering design specifications along with the design actions, constraints, and rationale that drove the design process. The capture and classification of engineering design activity is highly beneficial to future designers, assisting in design analysis, design maintenance, design learning, and design reuse. An advantage of the DHDM is that it incorporates a meta data and schema evolution component to support the capture of both pre-specified design activities and dynamic design activities. Pre-specifiable design specifications are those design tasks that are well-known and can be planned in advance of a design activity. Dynamic design involves the specification of design tasks as they actually occur using schema evolution. Modeling design activities is achieved through the use of process classes that are composed of subprocesses through the use of temporal aggregation concepts. Specific occurrences of design activities are modeled as instances of process classes. In addition to introducing the DHDM concepts, this paper describes a prototype implementation of the DHDM on the Itasca object-oriented database system. The prototype DHDM is evaluated with respect to constructibility, comprehensibility, and extensibility of the design history specification.

Using an object-oriented approach to model multimedia data

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.

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.

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. >

Functional dependency (FD) is one of the most analyzed integrity constraints for any data model. In the relational data model, FDs are defined in a natural way: the values of an attribute set Y depend on the values of another attribute set X, that is, "Y is a function of X". FDs are well studied and are widely used in normalization theory. XML functional dependencies (XFD) can be defined in different ways and no universally best definition has been proposed. They are defined by very intricate concepts, and they are mostly based upon XML elements described by XML schema languages such as a DTD or an XML Schema definition. The instances of these elements are semi-structured tuples. A semi-structured tuple is an ordered list of (attribute: value) pairs. We may think of a tuple as a sentence of a formal language, where the values are the terminal symbols and the attribute names are the nonterminal symbols. In this way, the sequence of the attribute names is the left side of a production rule used to accept the next terminal symbol, that is, the next value of the tuple. So the list of values forms the sentence and the list of attributes forms the dual sentence. In this paper, we introduce the notion of the extended tuple as a sentence from a regular language generated by a grammar where the nonterminal symbols of the grammar are the attribute names of the tuple. Sets of extended tuples are the extended relations (relations are instances). We then introduce the dual language, which generates the tuple types allowed to occur in extended relations. We define functional dependencies over extended relations. The syntax of functional dependencies will be given on the graph of the finite state automaton accepting the regular language. Using this model, we can also handle extended relations generated by recursive regular expressions. The implication problem of our class of dependencies is decidable and finitely axiomatizable by a version of the Chase algorithm performed on the graph of the associated finite state automaton.

The relational data model is the dominant paradigm in the commercial database market today, and it has been for several years. However, there have been challenges to the model over the years, and they have influenced its evolution and that of database technology. The object-oriented revolution that got started in programming languages arrived to the database area in the form of a brand new data model. The relational model managed not only to survive the newcomer but to continue becoming a dominant force, transformed into the object-relational model (also called extended relational, or universal) and relegating object-oriented databases to a niche product. Although this market has many nontechnical aspects, there are certainly important technical differences among the mentioned data models. In this article I describe the basic components of the relational, object-oriented, and object-relational data models. I do not, however, discuss query language, implementation, or system issues. A basic comparison is given and then future trends are discussed.

It is widely accepted that object-oriented data models are particularly suitable as canonical models for providing data model transparency. In this paper we address issues of reliability of global object identification in global object views arising from requirements for heterogeneity and autonomy. We propose a taxonomy of object identity management policies for providing reliable global OIDs based on (possibly) unreliable local identities. Based on our analysis of the problem domain, we outline a generic object oriented framework for object view implementations that can be refined and configured to the object management needs of a specific data repository. We also argue for the need for some general design guidelines for object views of heterogenous data repositories in which the reliability of local identity plays a major role. >

In May, 1990, a small workshop was held in New Hope, Pennsylvania, to discuss the fundamental issues raised by continuing work on the interface between databases and programming languages. Four topics were addressed: new directions stemming from object-oriented data models, contributions of type theory to database programming languages (DBPLs), applications of logic to DBPL issues, and DBPL implementations. This workshop was organized under the auspices of the INRIA-NSF program, Languages for Databases and Knowledge Bases .

The Human Genome Project (HGP) plans to sequence the human genome by the beginning of the next century. It will generate DNA sequences of more than 10 billion bases and complex marker sequences (maps) of more than 100 million markers. All of these information will be stored in database management systems (DBMSs). However, existing data models do not have the abstraction mechanism for modelling sequences and existing DBMS`s do not have operations for complex sequences. This work addresses the problem of sequence modelling in the context of the HGP and the more general problem of an extensible object data model that can incorporate the sequence model as well as existing and future data constructs and operators. First, we proposed a general sequence model that is application and implementation independent. This model is used to capture the sequence information found in the HGP at the conceptual level. In addition, abstract and biological sequence operators are defined for manipulating the modelled sequences. Second, we combined many features of semantic and object oriented data models into an extensible framework, which we called the ``Extensible Object Model``, to address the need of a modelling framework for incorporating the sequence data model with other types of data constructs and operators. This framework is based on the conceptual separation between constructors and constraints. We then used this modelling framework to integrate the constructs for the conceptual sequence model. The Extensible Object Model is also defined with a graphical representation, which is useful as a tool for database designers. Finally, we defined a query language to support this model and implement the query processor to demonstrate the feasibility of the extensible framework and the usefulness of the conceptual sequence model.