Constraint-Based Multi-Dimensional Databases

This chapter deals with constraint-based multi-dimensional modelling. The model we define integrates a constellation of facts and dimensions. Along each dimension, various hierarchies are possibly defined and the model supports multiple instantiations of dimensions. The main contribution is the definition of intra-dimension constraints between hierarchies of a same dimension as well as inter-dimension constraints of various dimensions. To facilitate data querying, we define a multi-dimensional query algebra, which integrates the main multi-dimensional operators such as rotations, drill down, roll up… These operators support the constraint-based multi-dimensional modelling. Finally, we present two implementations of this algebra. First, OLAP-SQL is a textual language integrating multi-dimensional concepts (fact, dimension, hierarchy), but it is based on classical SQL syntax. This language is dedicated tospecialists such as multi-dimensional database administrators. Second, a graphical query language is presented. This language consists in a graphical representation of multi-dimensional databases, and users specify directly their queries over this graph. This approach is dedicated to non-computer scientist users.

Conceptual Modeling for XML

The process of conceptual design is independent of the final platform and the medium of implementation, and is usually in a form that is understandable and usable by managers and other personnel who may not be familiar with the low-level implementation details, but have a major influence in the development process. Although a strong design phase is involved in most current application development processes (e.g., Entity Relationship design for relational databases), conceptual design for XML has not been explored significantly in literature or in practice. Most XML design processes start by directly marking up data in XML, and the metadata is typically designed at the time of encoding the documents. In this chapter, the reader is introduced to existing methodologies for modeling XML. A discussion is then presented comparing and contrasting their capabilities and deficiencies, and delineating the future trend in conceptual design for XML applications.

A Content-Based Approach to Medical Image Database Retrieval

Content-based image retrieval (CBIR) makes use of image features, such as color and texture, to index images with minimal human intervention. Content-based image retrieval can be used to locate medical images in large databases. This chapter introduces a content-based approach to medical image retrieval. Fundamentals of the key components of content-based image retrieval systems are introduced first to give an overview of this area. A case study, which describes the methodology of a CBIR system for retrieving digital mammogram database, is then presented. This chapter is intended to disseminate the knowledge of the CBIR approach to the applications of medical image management and to attract greater interest from various research communities to rapidly advance research in this field.

Business Data Warehouse

The retailing giant Wal-Mart owes its success to the efficient use of information technology in its operations. One of the noteworthy advances made by Wal-Mart is the development of the data warehouse which gives the company a strategic advantage over its competitors. In this chapter, the planning and implementation of the Wal-Mart data warehouse is described and its integration with the operational systems is discussed. The chapter also highlights some of the problems encountered in the developmental process of the data warehouse. The implications of the recent advances in technologies such as RFID, which is likely to play an important role in the Wal-Mart data warehouse in future, is also detailed in this chapter.

The Management of Evolving Engineering Design Constraints

This chapter presents research aimed at determining the requirements of a database software tool that supports integrity validation of versioned-design artefacts through effective management of evolving constraints. It has resulted in the design and development of a constraint management model, which allows constraint evolution through representing constraints within versioned objects called Constraint Versions Objects (CVOs). This model operates around a version model that uses a well-defined configuration management strategy to manage the versions of complex artefacts. Internal and inter-dependency constraints are modelled in CVOs. The combination of our versioning, configuration management, and constraint management approaches has produced a unique model which has been implemented in a prototype database tool with an intuitive user interface. The user interface allows designers to manage design constraints without the need to program. The innovative concepts developed in this chapter are introduced using an ongoing example of a simple bicycle design.

Web Service Integration and Management Strategies for Large-Scale Datasets

This chapter presents the Web Service architecture and proposes Web Service integration and management strategies for large-scale datasets. The main part of this chapter presents the elements of Web Service architecture, the challenges in implementing Web Services whenever large-scale data are involved and the design decisions and businessprocess re-engineering steps to integrate Web Services in an enterprise information system. The latter are presented in the context of a case study involving the largest private-sector telephony provider in Greece, where the provider’s billing system datasets are utilized. Moreover, scientific work on Web Service discovery is presented along with experiments on implementing an elaborate discovery strategy over real-world, large-scale data. Thereby, this chapter aims to illustrate the necessary actions to implement Web Services in a corporate environment, stress the associated benefits, to present the necessary business process re-engineering procedures and to highlight the need for more efficient Web Service discovery.

Semantic-Based Dynamic Enterprise Information Integration

Decision support systems or mission control systems for network-centric operations typically need input from multiple heterogeneous information sources. While the number and size of information sources increase, information integration and its semantic interoperability are becoming a growing concern and a major challenge to information management. In this chapter, we will share our experience of enabling semantic-based dynamic information integration across multiple heterogeneous information sources. While data is physically stored in existing/legacy data systems across the networks, the information is integrated based upon its semantic meanings. Informally, it sounds like a virtual data warehousing technique without any physical data conversion required in advance. Ontology is used to describe the semantics of global information content, and semantic enhancement is achieved by mapping the local metadata onto the ontology. For better system reliability, a unique mechanism is introduced to perform appropriate adjustments upon detecting environmental changes.

Database Design Based on B

This chapter is devoted to the integration of the ASSO features in B. ASSO is a database design methodology defined for achieving conceptual schema consistency, logical schema correctness, flexibility in reflecting the real-life changes on the schema and efficiency in accessing and storing information. B is an industrial formal method for specifying, designing, and coding software systems. Starting from a B specification of the data structures and of the transactions allowed on a database, two model transformations are designed: The resulting model, called Structured Database Schema, integrates static and dynamics exploiting the novel concepts of Class-Machine and Specialized Class-Machine. Formal details which must be specified if the conceptual model of ASSO is directly constructed in B are avoided; the costs of the consistency obligations are minimized. Class-Machines supported by semantic data models can be correctly linked with Class-Machines supported by object Models.

Databases Modeling of Engineering Information

Information systems have become the nerve center of current computer-based engineering applications, which hereby put the requirements on engineering information modeling. Databases are designed to support data storage, processing, and retrieval activities related to data management, and database systems are the key to implementing engineering information modeling. It should be noted that, however, the current mainstream databases are mainly used for business applications. Some new engineering requirements challenge today’s database technologies and promote their evolvement. Database modeling can be classified into two levels: conceptual data modeling and logical database modeling. In this chapter, we try to identify the requirements for engineering information modeling and then investigate the satisfactions of current database models to these requirements at two levels: conceptual data models and logical database models. In addition, the relationships among the conceptual data models and the logical database models for engineering information modeling are presented in the chapter viewed from database conceptual design.

Similarity Search for Voxelized CAD Objects

Similarity search in database systems is becoming an increasingly important task in modern application domains such as multimedia, molecular biology, medical imaging, and many others. Especially for CAD (Computer-Aided Design), suitable similarity models and a clear representation of the results can help to reduce the cost of developing and producing new parts by maximizing the reuse of existing parts. In this chapter, we present different similarity models for voxelized CAD data based on space partitioning and data partitioning. Based on these similarity models, we introduce anindustrial prototype, called BOSS, which helps the user to get an overview over a set of CAD objects. BOSS allows the user to easily browse large data collections by graphically displaying the results of a hierarchical clustering algorithm. This representation is well suited for the evaluation of similarity models and to aid an industrial user searching for similar parts.