Data is content represented by numbers, text, pictures, sounds, etc. On its own, data does not have meaning. Meaning manifests only when data undergoes manual or computerized processing (analysis). It is only at the point at which something has meaning that it can be considered information. Data therefore is the raw material and analysis processes are the means by which the raw material (data) is transformed into the finished consumable product (information).

To illustrate the data-information concept, think of a situation where someone shows you a photograph of a person you didn't immediately recognize. That same someone points out to you that the picture is of a friend taken 20 years ago. Suddenly you recognize the person as being a younger version of the person you know. The photograph was the source data, more data was applied (a name, a temporal context), the data was analyzed (a mental image of the person associated with the name was applied to the photograph and making allowances for age, the two images were deemed similar), recognition occurred and information (meaning) was derived. Data plus analysis equals information.

Another example of the data-information concept is to think of a point on a piece of paper, which as a component of a larger pattern of points, becomes the letter a. In an even greater pattern, the a becomes a component of the word data, which again, in a larger pattern becomes part of a sentence, part of paragraph, part of a chapter, part of a book and so on. At each stage, the data, through an analysis process looking for recognizable patterns, becomes information, which in turn becomes data composing a larger pattern that provides even more information.

A final example of the data-information concept involves bleach. The word bleach could be considered a data element. When we analyze the word bleach we recognize the individual letters, we recognize that the letters in the specific sequence displayed comprises a word which we have prior context for. In other words we know what bleach is, a whitener and a disinfectant. So what does bleach have to do with data? Bleach can be considered a single data element and as such not much analysis can be done to it therefore its use as information is extremely limited and our assumption as to its meaning is limited and cannot be verified. The more data that is available the more analytical techniques that can be effectively applied and the more patterns that can therefore be identified and recognized the greater the potential for information as the example below illustrates:

Bleach.
Bleach was stolen.
Bleach was stolen in jurisdiction 1.
Bleach was stolen in jurisdiction 1 in January.
Bleach was stolen in jurisdiction 1 in January 2004.
Bleach was stolen in jurisdiction 1 in January 2004 six times.
Bleach was stolen in jurisdiction 1 in January 2004 six times. Bleach was stolen in jurisdiction 2 in January 2004 seven times.
Bleach was stolen in jurisdiction 1 in January 2004 six times. Bleach was stolen in jurisdiction 2 in January 2004 seven times. Bleach was not stolen in jurisdiction 3 and 4 in January 2004.
Bleach was stolen in jurisdiction 1 in January 2004 six times. Bleach was stolen in jurisdiction 2 in January 2004 seven times. Bleach was not stolen in jurisdiction 3 and 4 in January 2004. Bleach can be used to manufacture plastic explosive.
Bleach was stolen in jurisdiction 1 in January 2004 six times. Bleach was stolen in jurisdiction 2 in January 2004 seven times. Bleach was not stolen in jurisdiction 3 and 4 in January 2004. Bleach can be used to manufacture plastic explosive. Bleach was not stolen in jurisdiction 1 or jurisdiction 2 in December 2003. Records show a person of interest with a history of violence and minor bombing offenses with a last known address in jurisdiction 2. Corrections records indicate this person was released from prison in January 2004 after a four-year incarceration.

The example above illustrates that more data provides for more potential pattern recognition and ultimately more potential meaning. Note that more data does not necessarily equate to more information. Data must be analyzed for recognizable patterns to be considered information. More data simply means a greater potential for patterns which means greater potential information. It is impossible to perform analysis of the single data element bleach therefore no patterns can be recognized therefore no information can be gleaned.

More data allows for more potential meaning as greater patterns can be discerned between the data elements - this is the motivation for data sharing and it is also why data sharing is critical to the Enforcement Community.