13.1 Introduction

The Geospatial Information Data Base (GIDB) System is an object-oriented (OO) digital-mapping database system designed by the Digital Mapping, Charting and Geodesy Analysis Program (DMAP) of the Naval Research Laboratory. Development of the GIDB System began in 1994 to demonstrate that representation of spatial data is less cumbersome and more optimal in object format versus relational format. Smalltalk was chosen as the programming language for the database, since at that time it was the most robust pure OO language available. Initially, all management of spatial objects was done in memory. As development grew to the point where memory management was no longer feasible, first ObjectStore and later GemStone was chosen as the OO database management system in which the GIDB database spatial data was stored.

When Java made its debut in 1995, the DMAP team began monitoring its usefulness in Internet-based capabilities. The DMAP team began work on Internet-based digital-mapping capabilities in 1997. This work has resulted in the GIDB Java mapping application and applet, which gives users access to mapping data via the Internet. Given the success of the GIDB mapping application and the growth and stability of the Java programming language, the DMAP team migrated all GIDB database and system code from Smalltalk to Java in 2001. The database component of the GIDB database is now implemented in an Open Source, all-Java, OO database management system called Ozone. Information on Ozone, including documentation and downloads, is available at http://www.ozone-db.org/.

The GIDB database, implemented in Ozone, is able to store spatial data from a variety of sources. Most of the mapping data in the GIDB database is obtained from the National Imagery and Mapping Agency (NIMA). Other data sources include the Naval Oceanographic Office, the U.S. Geological Survey, the National Ocean Survey, the U.S. Census Bureau, and the U.S. Army Corps of Engineers. The most common format of GIS data that can be read by the GIDB System and stored in the database is vector data such as NIMA's Vector Product Format (VPF) (NIMA 1996) and ESRI's Shapefile format (ESRI 1998). The GIDB System can also read in images, audio clips, video clips, and specialized text or binary files. Each data type is ingested into a common object model for uniform retrieval. This common object model was designed primarily to facilitate data retrieval in a mapping environment and so it organizes data in terms of scale, thematic layers, and feature classification types. The structure generally follows the organization of VPF data, the most complex and common data type in the GIDB database. The combination of data structure and spatial indexing facilitates storage of data with worldwide coverage and efficient retrieval for a given area of interest.

Since its inception, the GIDB System has been gradually moving from a monolithic to a truly distributed database system. The latest step in this migration has been the development of the GIDB portal, which allows for connection to and retrieval from many disparate databases, in addition to the GIDB Ozone database. With the widespread use of the Internet, many new sources of geospatial data are available for access. Since storage of the plethora of new data available within a single database system would be impractical, the DMAP team has instead focused on accessing these data sources directly through a GIDB portal. The GIDB portal establishes a common data request format and a common data transfer format. The GIDB mapping application, as well as any other application that interfaces with this common data transfer format, is able to make use of the data that the portal accesses. Use of the GIDB portal allows retrieval of data from many existing data repositories, regardless of whether they are relational, hybrid, or pure OO database management systems. It is important to note that no changes are required by the data source providers in order for the GIDB portal to access the data. All translation of the data from native format to the common transfer format occurs within the portal. For each new type of data source, a driver is written to perform this translation, and this new driver becomes a part of the overall GIDB portal. Each driver provides a common interface between the data source and the GIDB System, hiding the underlying details of how the data source is accessed. Figure 13.1 shows the overall GIDB System architecture.

The overwhelming success of the GIDB System has been due in part to its ability to take advantage of new technologies and standards as they become available. The focus of the rest of this chapter is on how the GIDB System has utilized XML (Walmsley 2002) and XML-based standards to expand its mapping portal capabilities. Initially, a driver was written for the portal to access meteorological and oceanographic data, using an XML catalog to determine the available data and how to retrieve it. Additionally, the DMAP team developed a driver to allow for a portal connection to OpenGIS Consortium (OGC) Web Map Service (WMS) compliant data providers on the Internet. Finally, the DMAP team has implemented the capability to read and write vector data in the OGC's Geographic Markup Language (GML) format (Cox et al. 2001), an XML-based specification for standard data interchange with other Geographic Information System (GIS) applications.

Top Title TOC Preface P.1 What Is XML? P.2 XML Concepts P.3 XML-Related Technologies P.4 XML Data Management P.5 How This Book Is Organized P.6 Who Should Read This Book P.7 Resources Acknowledgments Chapter 8 Chapter 12 Chapter 13 Chapter 14 Chapter 19 Part I: What Is XML? Chapter 1. Information Modeling with XML 1.1 Introduction 1.2 XML as an Information Domain 1.3 How XML Expresses Information 1.4 Patterns in XML 1.5 Common XML Information-Modeling Pitfalls 1.6 A Very Simple Way to Design XML 1.7 Conclusion Part II: Native XML Databases Chapter 2. Tamino-Software AG's Native XML Server 2.1 Introduction 2.2 Tamino Architecture and APIs 2.3 XML Storage 2.4 Querying XML 2.5 Tools 2.6 Full Database Functionality 2.7 Conclusion Chapter 3. eXist Native XML Database 3.1 Introduction 3.2 Features 3.3 System Architecture Overview 3.4 Getting Started 3.5 Query Language Extensions 3.6 Application Development 3.7 Technical Background 3.8 Conclusion Chapter 4. Embedded XML Databases 4.1 Introduction 4.2 A Primer on Embedded Databases 4.3 Embedded XML Databases 4.4 Building Applications for Embedded XML Databases 4.5 Conclusion Part III: XML and Relational Databases Chapter 5. IBM XML-Enabled Data Management Product Architecture & Technology 5.1 Introduction 5.2 Product and Technology Offering Summaries 5.3 Current Architecture and Technology 5.4 Future Architecture and Technology 5.5 Conclusion Notices Chapter 6. Supporting XML in Oracle9i 6.1 Introduction 6.2 Storing XML as CLOB 6.3 XMLType 6.4 Using XSU for Fine-Grained Storage 6.5 Building XML Documents from Relational Data 6.6 Web Access to the Database 6.7 Special Oracle Features 6.8 Conclusion Chapter 7. XML Support in Microsoft SQL Server 2000 7.1 Introduction 7.2 XML and Relational Data 7.3 XML Access to SQL Server 7.4 Serializing SQL Query Results into XML 7.5 Providing Relational Views over XML 7.6 SQLXML Templates 7.7 Providing XML Views over Relational Data 7.8 Conclusion Chapter 8. A Generic Architecture for Storing XML Documents in a Relational Database 8.1 Introduction 8.2 System Architecture 8.3 The Data Model 8.4 Creating the Database 8.5 Connecting to the Repository 8.6 Uploading XML Documents 8.7 Querying the Repository 8.8 Further Enhancements 8.9 Conclusion Chapter 9. An Object-Relational Approach to Building a High-Performance XML Repository 9.1 Introduction 9.2 Overview of XML Use-Case Scenario 9.3 High-Level System Architecture 9.4 Detailed Design Descriptions 9.5 Conclusion Part IV: Applications of XML Chapter 10. Knowledge Management in Bioinformatics 10.1 Introduction 10.2 A Brief Molecular Biology Background 10.3 Life Sciences Are Turning to XML to Model Their Information 10.4 A Genetic Information Model 10.5 NeoCore XMS* 10.6 Integration of BLAST into NeoCore XMS Conclusion Chapter 11. Case Studies of XML Used with IBM DB2 Universal Database 11.1 Introduction 11.2 Case Study 1: "Our Most Valued Customers Come First" 11.3 Case Study 2: "Improve Cash Flow" 11.4 Conclusion Notices Chapter 12. The Design and Implementation of an Engineering Data Management System Using XML and J2EE 12.1 Introduction 12.2 Background and Requirements 12.3 Overview 12.4 Design Choices 12.5 Future Directions 12.6 Conclusion Chapter 13. Geographical Data Interchange Using XML-Enabled Technology within the GIDB System 13.1 Introduction 13.2 GIDB METOC Data Integration 13.3 GIDB Web Map Service Implementation 13.4 GIDB GML Import and Export 13.5 Conclusion Chapter 14. Space Wide Web by Adapters in Distributed Systems Configuration from Reusable Components 14.1 Introduction 14.2 Advanced Concept Description: The Research Problem 14.3 Integration of Components with Architecture 14.4 Example 14.5 Future Generation NASA Institute for Advanced Concepts, Space Wide Web Research, and Boundaries 14.6 Advanced Concept Development 14.7 Conclusion Chapter 15. XML as a Unifying Framework for Inductive Databases 15.1 Introduction 15.2 Past Work 15.3 The Proposed Data Model: XDM 15.4 Benefits of XDM 15.5 Toward Flexible and Open Systems 15.6 Related Work 15.7 Conclusion Chapter 16. Designing and Managing an XML Warehouse 16.1 Introduction 16.2 Architecture 16.3 Data Warehouse Specification 16.4 Managing the Metadata 16.5 Storage and Management of the Data Warehouse 16.6 DAWAX: A Graphic Tool for the Specification and Management of a Data Warehouse 16.7 Related Work 16.8 Conclusion Part V: Performance and Benchmarks Chapter 17. XML Management System Benchmarks 17.1 Introduction 17.2 Benchmark Specification 17.3 Benchmark Data Set 17.4 Existing Benchmarks for XML 17.5 Conclusion Chapter 18. The Michigan Benchmark: A Micro-Benchmark for XML Query Performance Diagnostics 18.1 Introduction 18.2 Related Work 18.3 Benchmark Data Set 18.4 Benchmark Queries 18.5 Using the Benchmark 18.6 Conclusion Chapter 19. A Comparison of Database Approaches for Storing XML Documents 19.1 Introduction 19.2 Data Models for XML Documents 19.3 Databases for Storing XML Documents 19.4 Benchmarking Specification 19.5 Test Results 19.6 Related Work 19.7 Summary Chapter 20. Performance Analysis between an XML-Enabled Database and a Native XML Database 20.1 Introduction 20.2 Related Work 20.3 Methodology 20.4 Database Design 20.5 Discussion 20.6 Experiment Result 20.7 Conclusion Chapter 21. Conclusion References Contributors Editors Chapter 1: Information Modeling with XML Chapter 2: Tamino-Software AG's Native XML Server Chapter 3: eXist Native XML Database Chapter 4: Embedded XML Databases Chapter 5: IBM XML-Enabled Data Management Product Architecture and Technology Chapter 6: Supporting XML in Oracle9i Chapter 7: XML Support in Microsoft SQL Server 2000 Chapter 8: A Generic Architecture for Storing XML Documents in a Relational Database Chapter 9: An Object-Relational Approach to Building a High-Performance XML Repository Chapter 10: Knowledge Management in Bioinformatics Chapter 11: Case Studies of XML Used with IBM DB2 Universal Database Chapter 12: The Design and Implementation of an Engineering Data Management System Using XML and J2EE Chapter 13: Geographical Data Interchange Using XML-Enabled Technology within the GIDB System Chapter 14: Space Wide Web by Adapters in Distributed Systems Configuration from Reusable Components Chapter 15: XML as a Unifying Framework for Inductive Databases Chapter 16: Designing and Managing an XML Warehouse Chapter 17: XML Management System Benchmarks Chapter 18: The Michigan Benchmark: A Micro-Benchmark for XML Query Performance Diagnostics Chapter 19: A Comparison of Database Approaches for Storing XML Documents Chapter 20: Performance Analysis between an XML-Enabled Database and a Native XML Database Remember the name: eTutorials.org Copyright eTutorials.org 2008-2023. 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