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Universal Data Analytics as Semantic Spacetime(Part 7)

Part 7. Coincidence and the Four Horsemen of Semantics

After taming the tools in foregoing episodes, we now have a robust set of techniques for comprehending and organizing data, i.e. for turning input streams into analytical structures. These dynamical “knowledge representations” describe information flows or spacetime processes on all levels. Let’s now dive deeper, with some examples, and return to some subtle questions of modelling. To tell a story about causation — whether to uncover the internal workings of nature, or to invent new services for ourselves — we need to map out the scenarios in space and in time. It doesn’t matter whether the space is physical, simulated, or completely imaginary — the principles for representing the characteristics of locations and times along a system path are central to making this map.

In this installment, we examine the four previously mentioned core relationships of Semantic Spacetime so that we can identify them quickly for use in model scenarios. We’ll see how to recognize them in the context of key-values, documents, and graphs. We start, of course, by returning to teh central topic of semantic spacetime: processes and how they interact.

Eventful coincidence (x-x’)!

Coincidence is what happens when several things or processes meet at the same location: their timelines or trajectories join or cross — they are “incidentally” together. A related term co-activation is also used in biology for coincident proteins that activate processes in a kind of “logical AND” handshake, with proposal AND confirmation both required to switch on a process. It’s the same idea used in forensic investigations: if A and B are observed together, then there is some kind of connection between them — perhaps to be discovered or elaborated upon later. The role of coincidence is not always easy to discern, but in spacetime it’s simply a matter of expressing how events are composed from their coincident parts.

Co-activation is an important “valve” mechanism for regulating processes, in everything from control systems to immunology. In linguistics, coincident words convey compound semantics by forming phrases and sentences. It leads to a hierarchy of meaning from the bottom up — a kind of semantic chemistry. The particular combination of components present in the same place at the same time is the basis for encoding and elaborating specific meaning by composition of generic parts. But, we need to understand what “the same place” means for each process: when are processes independent, and when should they be seen as parts of a larger whole? The answer depends basically on characteristic scales for the processes. This is a subtle and difficult topic that I’ve addressed in my book Smart Spacetime. Combinatorics is a huge topic that spans subjects from chemistry to category theory.

As a taster of things to come, take a look at figures 1 and 2. These are process graphs translated directly into semantic spacetime by the Linux version of the traceroute program. It might come as a surprise to some that an Internet traversal isn’t just a linear chain — of course each individual observation does follow a unique path, but over coarse time, the map of possible paths splits into a multi-path integral view — quite analogous to a quantum multi-slit experiment. Along the path, the intensity of traffic at each point may be a sum over several coincident paths.