Why should databases care about aristotle?

Aristotle and the Database

For the last 9 months, I’ve been playing Ars Magica, a game set in Mythic Europe in the 13th century. The beauty of this game is that it requires thinking in a different paradigm. And yes, I use the term Paradigm in the proper Kuhnian sense – a complete way of thinking and understanding the universe.

The root of the Aristotelian paradigm, instead of the scientific falsification that we espouse (note, not actually do, but say we do), the paradigm seeks rigorously logical and plausible explanations based on prior authority. Consider someone in the Aristotelian paradigm trying to explain a volcano. We start by exploring the things known. I’ll quote here from Art and Academe, the sourcebook for Ars Magica that explores these things:

At the very center of the world is a perfect sphere of earth upon the surface of which all material life can be found. Surrounding the sphere of earth on all sides is the sphere of water that constitutes the seas, although in some places the expansive water enters into the pores of the earth and runs beneath it, leaving dry land. Surrounding the sphere of water is the sphere of air and surrounding that is the sphere of fire. The fire in this outer layer is of the purest kind found, not the smoky fire found on earth, and when illuminated by the sun it burns with a bright blue flame giving the sky its colour.

Of note here is the rigorous logic and acceptance of precedent. Given one thing and observations, we logically deduce others.

Given that authority has stated the above (and that phrase is essential to Aristotelian scholarship, "given-that-authority". Not our own “holy grail” of experimental results (not that anyone actually follows our holy grail, but that’s beside the point) ) let us look at how we’d explain a volcano. We start by considering the basis of natural philosophy: earth is below us, and loves itself, which is why it seeks to rejoin itself. Fire is above us, and as fire loves fire, it rises. Thus, a volcano, fire which has somehow been drawn under the earth, is perfectly logical. The lava rises because the fire wants to return to its natural place, but falls again due to love of the earth as the essence of fire departs. It is liquid because it uses the same pores of the earth that water does, and thus shares its properties. Just as air trapped underground causes earthquakes as it escapes, so too does fire cause volcanoes.

The above explanation is perfectly logical… and horribly incorrect as our modern understanding goes. The question now becomes – how does this relate to databases? The process described above is functionally building a constructed reality from observed phenomena and applying observations within that framework to arbitrary categories. Whether those categories involve picking up a lump of earth and calling it “earth!” or doing the same with data, the process of metaphysical creation is the same.

Metaphysical creation: the creation of those categories, those frameworks, those relationships. In the process of creating databases, we find ourselves doing the same thing. We’re taking stuff, making categories for it, and thinking that those categories explain the stuff.

But the parallels continue. Our present practices are the Aristotelian fabrication of data and data models. We have a profound tradition of scholarship designed around these practices, these constructed artifacts. We have “best practices” for designing a database, a data warehouse. We have a number of design methodologies for taking a project through to a theoretical conclusion. We have an entire field of Knowledge Management that purports to give us ways of manipulating knowledge for business gain. We have extensive debates on whether positivist or post-positivist or interpretivist or (my own favorite) post-modern methodologies are scientifically useful for constructing facts in Information Systems. And yet, to a mind used to the paradigm switches between a constructed reality of Aristotelian logic and whatever we want to label whatever it is I’m living in… my academic reality seems just as artificial as this game.

We have rules, we have tenets, we have peer review, but all of that creates scholarship. A profound scholarship, to be true: a /useful/scholarship. We explore that which has come before us, identify holes in the literature and try to fill those holes with created knowledge. And here is why I firmly believe that the contributions we’re making aren’t science.

In the investigations I’ve made so far in the literature, there are tens or hundreds of definitions of data, information, and knowledge. For every constructed reality of the speaker’s perspectives, every single damn definition is true. The problem is not that we’re trying to disprove certain definitions, or we’re trying to create a covering model of information that we can use a scientific basis for business interactions in the world, we’re performing scholarship into how different facets of knowledge, information, data, observations, business intelligence, facts, whatever-the-hell-it-is-we’re-talking-about are used by different people, constructing logical and convincing stories about those researches, and calling those stories science.

Discussing qualitative and quantitative approaches to data-gathering along with other uses of the artifacts of science matters. It matters because these approaches determine the relative merits of our scholarship in this field. Just as citing the correct “authorities” in an Aristotelian treatise on lava makes one more believable to the bishops and cardinals and other intelligencia of the time, discussing the right methodology here makes it more likely to get a bloody piece of paper saying that I’m a Ph.D, or that I’ve gotten the paper published in a journal.

More to the point, better scholarship does indeed produce better results. If I carefully (as I have) refine my research objectives to look at interesting things, and then carefully refine my methodology to accurately capture those objectives, I will have produced better scholarship. What I won’t have produced is science.

Here’s my parting thought. If we accept that what I’m doing is not science… then where does the tugging on these strings of scholarship stop? What “scientific” fields unravel? What don’t? Why?