This chapter explores the current state of research and key future challenges in geospatial databases, algorithms, and geospatial data mining. Advances in these areas could have a great effect on how geospatial data are accessed and mined to facilitate knowledge discovery.

TECHNOLOGIES AND TRENDS

This section outlines key developments in database management systems and data mining technologies as they relate to geospatial data.

Database Management Systems

The ubiquity and longevity of the relational database architecture are due largely to its solid theoretical foundation, the declarative nature of the query processing language, and its ability to truly separate the structure of the data from the software applications that manipulate them. With the relational model it is possible for applications to manipulate data—query, update, add new information, and so forth—independent of the database implementation. This abstraction of the database to a conceptual model is the hallmark of all modern database technologies. By separating the application logic from the database implementation, the model makes it possible to accommodate changes—for example, in the physical organization of the data—without disturbing the application software or the users’ logical view of the data. This separation also means that efforts made to optimize performance or ensure robust recovery will immediately benefit all applications.

Over the past two decades, the relational model has been extended to support the notion of persistent software objects, which couple data structures to sets of software procedures referred to as methods. Many commercial applications rely on simple data types (e.g., integers, real numbers, date/time, and character strings) and do not require the functionality provided by software objects and their methods.2 Geodata, however,

2  

The scope of software operations that can be performed on a data element is restricted by the type of data. Simple arithmetic operations such as add, subtract, multiply, and divide can be performed on integer numbers (such as 5, 10, and 225) but cannot be performed on character strings such as “National Academy of Sciences.” Conversely, operations that can be performed on character strings (e.g., convert a string of characters to uppercase letters or search for a sequence of characters) cannot be performed on integers. The database management system is aware of which operations are supported for each data type; thus, the system permits the multiplication of two integers to form a third but issues an error when an attempt is made to multiply two strings. For the simple data types (integers, real numbers, strings, etc.), the suite of operations for each data type is well known and implemented by virtually all database and programming systems.



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