It is funny how limitations, when they have been around for a while, can be turned into beliefs that there is only one way of thinking. The right way. This is the case of databases and the information they store. We have been staring at the limitations of what databases can store for so long that we have started to think that the world works in the same way. Today I want to put such a misconception to rest. Databases store facts, so naturally we look for facts everywhere, but the truth is, in the real world there are very few facts.
The definition of a fact is “a piece of true information” and “things that are true or that really happened, rather than things that are imaginary or not true” according to the MacMillian dictionary. Let me then ask you, what do you know to be true? It is a fact that “the area of a square with the side x is x squared”, however, limited to squares on a euclidean plane. Mathematics, as it turns out, is one of the few disciplines in which we actually can talk about truth. This is not the case for science in general though.
Is the statement “There are no aliens on the dark side of the moon” a fact? You would, if asked if there are aliens on the dark side of the moon, probably answer that there are no aliens there. However, if you were pushed to prove it, you may think otherwise. The reasoning would be that there is this extremely miniscule chance there could be something alien there. We could leave it at that and disqualify the statement as a fact, but let’s not just yet. What is more interesting is why you are almost sure it is a fact.
Back in days of the ancient greeks, Aristarchus of Samos suggested that the Earth revolves around the Sun. Heliocentrism was then forgotten for a while, but brought back by the brave Galileo Galilei almost 2000 years later. You have to rely on these guys being right to begin with, and that the moon is not painted on the sky or made of cheese. Then, you have to rely on the Apollo 8 mission, in which astronauts actually observed the dark side. The photographs that were taken further imply that you rely on the science behind imagery and that any images have not been tampered with. You need to rely on that aliens do not have cloaking devices, or that aliens in generals seem unlikely, and that any claimed observations are not made by credible sources.
You can build a tree view of all the things you rely on in order to feel assured that there are no aliens on the dark side of the moon. I just need to put one of them in doubt for the fact to become a non-fact. This illustrates how fragile facts are, and that they therefore constitute a small small small minority of the information we manage on a daily basis. Yet, for the most part we continue to treat all of it as facts.
For this reason, in transitional modeling, the concept of a fact is omitted, and replaced by a posit. A posit has no truth value at all and is merely a syntactical construct. Assuming “There are no aliens on the dark side of the moon” is a posit just means that it is a statement that fits a certain syntax. In order for such a statement to gain meaning and some kind of truth value, someone called a positor must have an opinion about it. A second construct, the assertion, semantically binds a posit to a positor, and expresses the degree of certainty with which the positor believes the statement to be true or not true. Together they express things like ‘Peter the positor is almost completely sure that “There are no aliens on the dark side of the moon”‘. Concurrently it may also be the case that ‘Paulina the other positor thinks there is a slight chance that “There actually are aliens on the dark side of the moon”.
Information, is in this view factless and instead has two parts, the pieces of information (posits) and the opinions about the pieces (assertions), better representing its true nature. That two such simple constructs can lead to a rich theory, from which other modeling techniques can be derived as special cases, such as Anchor modeling, Data Vault, and the third normal form, may be a bit surprising. Read more about it in our latest scientific paper, entitled “Modeling Conflicting, Uncertain, and Varying Information”. It can be read and downloaded from ResearchGate or from the Anchor Modeling homepage.