Database Management Paradigms pim

In the 1960s, mainframe computers were owned primarily by large organizations and businesses and were applied to their problems. These consisted mainly of clerical database tasks, which usually involved filing, retrieving, sorting, processing, and reporting data. For these applications, the computer represented several advantages over the corresponding manual processes:

Speed -- Data could be retrieved much faster than through manual methods.

Accuracy -- Calculations and manipulations (such as sorting) could be performed more accurately.

Density -- Data could be stored in magnetic form (mainly tape) more compactly than in physical files.

Utility -- The data could be presented in different formats for different purposes.

These advantages of computerized databases over manual processes prompted both database theorists and practitioners to focus on the efficient, reliable manipulation of large volumes of data. It was recognized, early on, that understanding and describing the structure of the data in advance (i.e., at database design time) was a major advantage. Most of the data being manipulated had a repeating, record-oriented structure that could be used to improve processing and storage efficiency. Therefore, relatively little attention was paid to providing richer data description languages or designing systems with more flexible data structures.

As a result, the dominant database management paradigms are not well suited for managing personal data. They are oriented toward the storage and retrieval of large volumes of data with a known, repetitive structure. These databases are mainly used for keeping corporate records and communicating within an organization.

Personal data has different characteristics: it is often of relatively limited volume; its structure is not known in advance and evolves overtime. It contains heterogeneous data types. This information may be generated and managed directly by an individual or may be some body of data that is indexed or accessed according to some idiosyncratic needs. Therefore, mainframe databases and their personal computer counterparts are not very useful for personal data, where discovering presenting, or modifying the structure of information is more important. A different data management paradigm is required.

Many programs designed to manage personal data have adopted a completely unstructured approach, treating all data as free text that is searched and displayed in response to ad hoc keyword queries. This approach confuses the lack of a fixed structure with no structure at all. Personal data has structure, but its structure is fluid, changing in response to evolving needs.

Hypertext systems provide a simple structuring mechanism--links between data elements -which allows the user to create a topological space of adjacent elements. However, structure is fluid, changing in of the grouping of similar items and relationships defined among those groups, not the simple linking of individual items together. Most hypertext systems assume that the information of interest resides exclusively in the data rather than in the structure. They do not provide the user with the means to view and manipulate structure itself or create relationships among groups of data elements.