Transition From Data to Information
Jens G. Pohl · DigitalCommons - CalPoly (California State Polytechnic University) · 2001
It is often lamented that we human beings are suffering from an information overload. This is a myth; as shown in Fig.1, there is no information overload. Instead, we are suffering from a data overload. The confusion between data and information is not readily apparent and requires further explanation. Unorganized data are voluminous but of very little value. Over the past 15 years, industry and commerce have made significant efforts to rearrange this unorganized data into purposeful data, utilizing various kinds of database management systems. However, even in this organized form, we are still dealing with data and not information. Fig.1: The information overload myth. Fig.2: Data, information and knowledge. Data are defined as numbers and words without relationships. In reference to Fig.2, the words “town”, “dog”, “Tuesday”, “rain”, “inches”, and “min”, have little if any meaning without relationships. However, linked together in the sentence, “On Tuesday, 8 inches of rain fell in 10 min. ” they become information. If we then add the context of a particular geographical region and historical climatic records, we could perhaps infer that “Rainfall of such magnitude is likely to cause flooding and landslides. ” This becomes knowledge. Context is normally associated solely with human cognitive capabilities. Prior to the advent of computers, it was entirely up to the human agent to convert data into information and to infer knowledge through the addition of context. However, the human cognitive system performs this function subconsciously (i.e., automatically); therefore, prior to the advent of computers, the difference between data and information was an academic question that had little practical significance in the real world of day-to-day activities. As shown in Fig.3, the intersection of the data, human agent, and context realms provides a segment of immediately relevant knowledge.