Presuming a systems theory approach, one might look at different classifications of information and their dependent relationships with one another in order to understand the nature, and possibly the behavior of various information classifications.
In order to perform a systemic analysis on the nature of information, one might look at the system as a whole, possibly inclusively-juxtaposing it with other systems, in order to understand the behavior of the system as a whole and how said system relatively yet absolutely dictates the behavior of its subsystems.
Looking at Dr. Floridi’s identified five classifications of data/information as described in chapter 2 of his book, Information: A very short Introduction:
Primary – The principal information
Secondary – The absence of primary information
Meta – The indications about the nature of non-meta information
Operational – The “[information] regarding the operations of the whole [information] system and the system’s performance”
Derivative – “The information that can be extracted from some information whenever the latter are used as indirect sources in search of patterns, clues, or inferential evidence about other things than those directly addressed by the information themselves, for example for comparative and quantitative analysis.”
Each of these five classifications of information could presumably be described to be of their own respective system. The interrelationships of these systems should have great effect to a singular piece of semantic media, such as a news article, which is observable by simply reading written language (organized communication). In order to understand the effects of these respective systems on the greater whole (e.g.: a news article), and how the whole affects its respective subsystems, a systemic analysis should be performed only after providing quantitative evidence that these five classifications of information can be controlled and predicted. Only after proceeding through a systems science methodology, applying meaningful metrics and predicting the effects of semantic information, can we then begin to understand the dynamics between semantic information and biological information.
In chapter 6 of Dr. Floridi’s book, he describes biological information as including:
Information as reality, e.g. patterns, fingerprints, tree rings;
Information for reality, e.g. commands, algorithms, recipes;
Information about reality, e.i. with an epistemic value, e.g. train tables, maps, entries in an encyclopedia.
Something may count as information in more than one sense, depending on the context.
These possibly open-loop systems (in some contexts) and closed-loop systems (in other contexts) presumably affect the value of semantic information. In order to appreciate an analysis using a complex adaptive system approach, it may be possible to quantify certain aspects of information synthesis when building knowledge because of the unique ways that we encounter semantic information according to these three biological information classifications. Such an undertaking should be treated holistically, i.e. systemically.