Data

1. Introduction

Despite many attempts at the definition of ‘Data', ‘Information', and ‘Knowledge', there still seems to be a lack of a clear and complete picture of what they are and the relationships between them. Although many definitions are relevant, they are far from being complete. It is not the intention of this paper to criticize those whom have paved the way to better understanding of the topic. Rather, the goal is to provide a different or new perspective in the context of business and knowledge management. Below is a table of various definitions of Data, Information, and Knowledge from different authors. The table also includes definitions from Webster's Collegiate Dictionary. Most if not all of the definitions shared a common anomaly; they are defined with each other, i.e. data in terms of information, information is defined in terms of data &/or knowledge, and knowledge is defined in terms of information. If we are just describing the inter-relationships, that is all very well. However, with regard to definitions, this is a logical fallacy i.e. circular definitions or argumentations.

Definitions

Data are recorded (captured and stored) symbols and signal readings.

? Symbols include words (text and/or verbal), numbers, diagrams, and images (still &/or video), which are the building blocks of communication.

? Signals include sensor and/or sensory readings of light, sound, smell, taste, and touch.

As symbols, ‘Data' is the storage of intrinsic meaning, a mere representation. The main purpose of data is to record activities or situations, to attempt to capture the true picture or real event. Therefore, all data are historical, unless used for illustration purposes, such as forecasting. [Note: However, Rehauser and Kremar (1996, p.6; cited by Probst et al., 2000) made a distinction between symbol and data with syntax.]

Information is a message that contains relevant meaning, implication, or input for decision and/or action. Information comes from both current (communication) and historical (processed data or ‘reconstructed picture') sources. In essence, the purpose of information is to aid in making decisions and/or solving problems or realizing an opportunity.

Knowledge is the (1) cognition or recognition (know-what), (2) capacity to act (know-how), and (3) understanding (know-why) that resides or is contained within the mind or in the brain. The purpose of knowledge is to better our lives. In the context of business, the purpose of knowledge is to create or increase value for the enterprise and all its stakeholders. In short, the ultimate purpose of knowledge is for value creation.

Given the definitions for data, information, and knowledge, the relationships between data and information, information and knowledge, why they are most often regarded as interchangeable and when they are not, the processes and their relevance to our intended application can be explored. The key to understanding the intricate relationship between data, information, and knowledge lies at the source of data and information. The source of both is twofold: (1) activities, and (2) situations. Both activities and situations generate information (i.e. ‘relevant meaning' to someone) that either is captured thus becoming Data, or becomes oblivious (lost).

Examples of activities where information is generated and data can be collected include business activities like production, sales transactions, or advertising campaigns. Situations pertain to changes in the environment that may or may not be related to human activities, such as changes in the climate. Changes in the climate would affect such human activities as agriculture, or other economic activities such as cargo shipping. A situation is a context that affects decisions. For example, the deterioration of a factory building may impact production. In short, activities and situations generate information that feed into the decision-making process. The following diagram illustrates the relationships between data and information.

Once they are captured and stored, data can be processed back into information through compilation and analysis. The picture of past activities and situations can thus be reconstructed. There are two fundamental aspects of data processing, compilation, and/or analysis:

? Data to data.

? Data to context

For example, ‘Anthony' represents a person, and ‘555-2345' represents a phone number. Both pieces of data may have a relationship,