A framework for understanding large scale digital storage systems

Abstract

The digital revolution is now underway. The use of binary zeros and ones to store data is increasing at a steady rate. They may represent text, images, pictures, sounds, maps, books, music, instructions, programs, or just about anything else which can be represented digitally. As the sizes of the digital data holdings have continued to grow, so too has the need to provide meaningful access to this data. There are a number of efforts now underway to provide such access. In most cases the efforts have been domain specific and progress in one area has been hard to replicate in a different domain. Part of this difficulty has been the lack of a general set of concepts and vocabulary that are sufficiently broad enough to bridge the gaps. The paper presents a general taxonomy of knowledge that is independent of subject matter domain. It begins with knowledge as the most general class and then proceeds to subdivide knowledge into its constituent parts: factual knowledge, procedural knowledge, and judgmental knowledge. Definitions of each type of knowledge are given along with examples sufficient to understand each subclass. A vocabulary is introduced that provides a means to discuss the topic in a manner independent of a specific problem domain. Understanding of the differences between different types or classes of knowledge is necessary if a person or an organization is to begin to build systems that acquire, organize, store, and retrieve various types of knowledge. The paper concludes with a discussion of some tools that are currently available to assist in the building and maintaining of a knowledge resource.