![[photo-1474314243412-cd4a79f02c6a.jpg]] Photo by [Marius Masalar](https://unsplash.com/@marius?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText) on [Unsplash](https://unsplash.com/photos/WlmerCi_Tpg?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText) The major difference between information vs. data is simply an understanding of content within the context encoded in correct form vs. structured (or unstructured) data without unambiguously defined interpretation. This observation might seem insignificant any first, but it is vital for ecosystem communication and correct interpretation of just everything happening around us. So, how to enable ecosystem-wide communication, distribution and processing of events, storage and interpretation of MetaSystems with associated MetaData? This post will introduce InfoTrance theory as one of the possible approaches to address complex questions related to unified information streams and their interpretation. > Information is processed, organized and structured data. More technically, information can be thought of as the resolution of uncertainty; it answers the question of "What an entity is" and thus defines both its essence and the nature of its characteristics. The concept of information has different meanings in different contexts. Information is associated with data. The difference is that information resolves uncertainty.[1] Let's start with the basics. How do we store and encode data today? Well, our computers are using binary logic for just about everything (not counting evolving quantum computing). They encode and decode data in binary form to process it. You might ask: What data? Well, all data: Text, pictures, sound, video etc. OK, but how do we know what does the data represent? It is our "human" interpretation of text ,picture... Unless, we associate he data with some metadata to support correct interpretation - i.e. metadata to picture like "date of picture", "location", "description" and more. But even this "metadata" is only interpreting particular data (in limited form) to audience understanding the metadata interpretation - i.e. "description" is in english language, not really helping other language speaking people without translation, therefore there is still a need for interpretation. And therein lies the problem we are trying to solve here - encoding, distribution and interpretation of any data in unified way for M:H (machine to human), H:M (human to machine), H:H (human to human) and M:M (machine to machine). > Thomas Stewart argues that transformation of information into knowledge is critical, lying at the core of value creation and competitive advantage for the modern enterprise. [2] Taking into the consideration all above, we believe there is a need for a **coherent information design** methodology resolving stated problems and establishing a clear path forward towards unified information streams (not data). It is crucial to clarify major differences between data encoding and information definition moving forward (picture below). ![[Pasted image 20230708125514.png|Figure1: DataStream and InfoStream flows]] Broadly speaking, #data might be encoded in many possible ways (today we encode text data in ASCII form and form there to binary form) but information must be **semantically based** and **syntactically encoded** for correct interpretation. Therefore logically, there are vast differences between data streams and information streams. All our communication today is "data" only and we use data streams on daily basis (video, voice, data channels, buffers etc.) and we are clearly missing upper part of the diagram (semantic information interpretation). Additionally, to clearly identify #semantic blocks, we need to unify syntactic form to make information distribution and processing effective. At the right side of the picture you can identify **InfoTrance information** building blocks - InfoStructure, Raw Information and finally Data distributed at the lower level of computing translation into binary form. At the first picture of this article "DataStream and InfoStream flows", you can identify "**InfoBlock**" as the vehicle to transport "**InfoElements**" connected together. The #InfoBlock can have fixed or variable size, however InfoElements are always ordered in sequence for correct interpretation of semantic information. Elemental **syntax** of each InfoBlock is driven by "3W+". Mandatory InfoElements are "Who"+"What"+"When", optionally we can add as many as needed within the InfoBlock to make desired information comprehensive (picture below). ![[Pasted image 20230708125543.png|Figure 2: System Spheres and InfoStreams]] The picture also represents conceptual encapsulation of InfoStream distributed and processed by #TechnoSystem to "Command & Control" particular Ecosystem and enable "Connect & Communicate" for all spheres via semantically based "InfoElements". --- The reason behind the name "**InfoTrance**" (used in this excerpt) is the realization of different speeds of data (consequently information) in dependency of each sphere. The speed variability (velocity) is different - it oscillates in different frequencies (cycle/second). ![[Pasted image 20230708125613.png|Figure 3: Information Frequency]] This (conceptual) observation influences speed of encoding and interpretation of information as well as ability to use multiple information channels within each InfoStream limited by processing capability (parallel InfoBlock sequence). We briefly talked about InfoHubs as a distribution and processing centers of semantically based information at "[[Open vs. Closed Systems]]" article, here we are connecting these two concepts together. ![[Pasted image 20230718205144.png|Figure 4: InfoHubs as processing and distribution nods of Ecosystem InfoStreams]] InfoHubs are processing InfoStreams and enabling Ecosystems to communicate in unified way despite different velocity of data (data streams) produced by each sphere. InfoHubs are aimed to support AI with **coherent information blocks** with recognized macro level abstractions (ecosystem architecture entities) and **dynamic semantic granularity** (dynamic ontologies). Connected InfoHubs as nodes are enforcing the idea of semantically based information network serving the purpose of H:M-M:H-M:M-H:H communication and understanding. You can learn more about InfoStreams and InfoStructures in the next article "Ecosystem Communication: InfoStructure". ## References [1] Wikipedia; Definitions [2] Stewart, Thomas (2001). Wealth of Knowledge. New York, NY: Doubleday. ## Related to [[Ecosystem Communication - InfoCode]] [[Ecosystem Communication - InfoElement and InfoBlock]] [[Ecosystem Communication - InfoStructure]] [[Ecosystem Communication - Information Processing]]