<nettime> C5 at openX

[brett <beestal@cadre.sjsu.edu>]

Paper presented in conjncton with the release of the C5 SoftSub data
mining freeware application at Ars Electronica:  openX. 
http://www.c5corp.com/softsub/ . 


Ontology of Organization as System     
Joel Slayton and Geri Wittig      

Research into knowledge representation is resulting in a new generation of
techniques and tools with the ability to automatically and intelligently
assist humans in analyzing complex forms of data to discover useful
information. Knowledge representation requires a presumptive notion with
regard to a 'model' (predictive or descriptive) against which pattern
recognition and iterative algorithmic processes involving machine
learning, pattern recognition, statistics, and artificial intelligence are
employed. Although these are well developed disciplines, emergence of
knowledge from complex data structures may also include non-model and
non-probabilistic based strategies. 

The procedural-declarative controversy of the 1970's illustrates the
dialectic around model and non-model based strategies over how to best
design knowledge representation systems. Both the procedural and
declarative approaches presuppose domain expertise and a potentiality of
objective, and are intended to interactively emerge interesting knowledge
about something specific. In the procedural view, encoded expertise is
determined by domain-specific algorithms--the model is composed from a
large database of information from which a specific sequence of questions
asked leads towards an optimum solution represented within the domain. The
declarative view involves the design of 'knowledge' acquisition within a
general purpose, and most often heuristically oriented, reasoning system.
Whereas, the procedural view stresses characterization of a detailed model
enabling optimization of decision accuracy, the declarative approach
emphasizes agencies and satisficing scenarios from which representations
emerge. The declarative approach has prevailed, resulting in a surge of
domain specific expert systems in the 1970's and 1980's, establishing the
basis for research into non-model based strategies. 

Knowledge representation deals with methods for encoding data in a form
that can be processed by a computer to derive interesting consequences. A
notion of consequences can be interpreted to include those which are also
spontaneous, non-linear, self-organizing, include high levels of
uncertainty and are derived from non-causal relationships. Such an
approach suggests new forms of data acquisition involving the emergence of
interesting information from ambiguous (non-predictive or non-descriptive)
systems. The strategy of discovering interesting information by revealing
the nature of complexity present in a system is a provocative theoretical
problem with implications influencing our fundamental understanding of the
basis of knowledge acquisition and its representation. 

Autopioesis

"A reliable way to get the attention of others is to produce information
that meets the input conditions of their domain-specific competencies." 
-Dan Sperber and Lawrence Hirschfeld

Autopoiesis, a term developed by biologists Humberto Maturana and
Francisco Varela, is a form of system organization where the system as a
whole produces and replaces its own components and differentiates itself
from its surrounding environment on a continual basis. Principles of this
basic system organization appear in more complex systems, what are known
as third order couplings or systems that emerge out of social
interactions, such as languaging. Third order structural couplings and
consensual domains, are rich in organizational concepts, and have
potential applicability in knowledge discovery research. The ontogeny of a
data system being an obvious starting point. 

Ontogeny, as defined by Maturana and Varela, is "the history of structural
change in a unity without loss of organization in that unity"; ontogeny is
of primary concern in autopoietic systems analysis. Continual structural
change takes place in a unity, either through external interactions from
the environment or through its own internal dynamics. The complexity of a
persistent unity is increased within structural couplings. In a structural
coupling, interactions between a unity and another unity, or the
environment, will consist of reciprocal perturbations. In these
interactions, the structure of the environment only triggers structural
changes in autopoietic unities, it doesn't determine or govern them, and
vice versa for the environment. 

Maturana refers to behavior in a consensual domain as "linguistic
behavior". A language exists among a community of individuals, and is
continually regenerated through their linguistic activity and the
structural coupling generated by that activity. Autopoiesis as related to
data, could potentially be realized in linguistic, consensual domains. 
Language, as a consensual domain, is a patterning of behavior that
possesses a shared orientation. The observer is a languaging entity,
operating in language with other observers, generating linguistic
distinctions in a linguistic domain. Observing emanates with language as a
co-ontogeny in the process of delineating. Meaning or knowledge discovery
emerges as a relationship of linguistic distinctions. Patterns of
recurrent interactions or minglings make possible ontogenic structural
drift in a structural coupling, that affords coordination of actions
specified through our data minglings. 

Clustering of data components emerging from these minglings, result in
dynamically coherent unities. These unities or systems, profiled in a
nearest neighbor array, possess similar or related ontological structure
with the capacity for recurrent systems occurrence. The membrane of
separation from other data unities lying in the barrier between classes,
defined by classification of attribute flow. 

Interiority/Exteriority

Gilles Deleuze states, "Everything is everything that happens, no matter
what happens." Or in other words everything has a concept, that is,
everything has an outside. The ontogenically based identity of a unity is
a mere definition posited by one term (the defined) with at least two
other terms (definers or reasons). Unlike the traditional semiotic model
of signifier/signified, ontogenic identity is a composite of attributes
that exist as predicates, which serve to characterize the defined. The
unity is, of course, irreducible, its predicates constituting the whole
and the parts of the defined. The defined is real, as any subject is real,
yet whose predicates are mere relations along the intermediary between the
functions of the inside and the outside, the barrier between classes.
According to Deleuze, "the inner character of the defined can be
understood from the outside, through successive experiments, which permit
the predicates to abandon being attributes in order to become relations." 

Severing the relations of the inside from the outside reveals an infinity
of possible codes which form the unity's definition. The autonomy of the
inside, an inside without an outside, and the autonomy of the outside,
without an inside, results in two infinite code sets as relations, not
predicates. Clarity endlessly plunges into obscurity. Our perception of
things is limited to the composiblity of these relations. That is, the
prolongation of continuation of code as series, a mingling of one into the
other, a wholeness of an interiority and exteriority, but only divisible
by itself, a composite as identity derived from the complexity of
auto-inclusionary relations as predicates. 

Based within codes of ambiguity, ontogenic identity is promoted via
associations with domains of unitites that possess more than one meaning.
Unities often belong to more than one organization and are operational on
multiple levels. The appearance of membranes clarifying interiority from
exteriority results in a blurred distinction, in an entailment of multiple
linguistic associations among consensual domains that place the membrane
as lexicon into the world. Explication of this lexical placement, as a set
of operations or regularities determining the relations of code within
codes, illuminates an ontology of organization as system derived from the
autopoietic nature of data. 

Prehension

In that a folder (a directory of files) can be considered a unity, it is a
unity having parts (or the potential for parts) and yet is simultaneously
a part. The folder is a prehension of its antecedents and concomitants
and, by degrees, acts to prehend a larger system which prehends itself.
Like the eye is a prehension of light or the body a prehension of person,
the folder is a prehension of its own organization and the domain to which
it belongs, a domain constituted within a network of language like
relations. 

In a unique twist of semiotic fate, to be a folder implies that the unity
of another folder must therefore prehend it (if A prehends BCDEFG then
BCDEFG prehends A). In other words, data expects other data, unitites
other unities, domains other domains, networks other networks. This notion
is critical, for prehension based systems illustrate the reciprocal and
self-referencing nature of data unities. As is implied, these unities tend
to evolve in complex, self-organizing and auto-catalytic systems which
exhibit behaviors which can be understood as code relations resulting from
their actions as attributes or predicates, including echoes, reflections,
iterations, traces, deformations, thresholds, and folds. 

As theoretical agencies, prehensions somehow anticipate themselves as
members of a domain and are evidenced by their formation in clusters
shaped as specific networks of coded relations. Fluctuating between
predicate or attribute status, the unity as a data object emerges actions,
which define its identity within a member class domain, which in turn
enables organization through relations with other organizations, which
ultimately formulate into networks. Operating in both first and third
person capacity, the folder as a unity is self-referencing, establishing
identity within the membranes of separation where coded relations are
evidenced. Each localization of a folder represents a new prehension
status for the folder and the organization to which it is a member. The
organization in turn, considered as a unity, emerges as a member of a
network domain. Unities and domains are therefore continuous. In a formal
sense, every organization is composed of unities shaped as coded relations
which necessarily prehend their other. A substantiation of these relations
is clear evidence of the public nature of data and serves to suggest that
no meaning of organization outside of the prehensive nature of code
exists. Appearance of functionality or purpose is but a mere reflection of
the expectation of data expecting other data. 

All A expect B        If A thinks that B thinks about C.
No B are C            And B is unaware of C, but realizes A is thinking.
All C expects B       B and C meet, A thinks about it.
All A expect C        B and C are aware of A thinking about them.


Further investigation of theoretical structures enabling prehension
including: predication, extensors, irreducibles, inclusionaries,
exclusionaries, permeables and entailments may illuminate our
understanding of the ontology of organization as system. Applications
which might be informed from research into these topics include: desktops
which organize themselves relative to profiling user organization
including potentials for interaction, self-organizing of memory, and
machine to machine dialectics. 

                                   
Predication:

Predicate logic represents the structure within propositions themselves
through quantifiers and the attributes and predicates that they bind
including representation between propositions and the codification of
relations referencing the minglings of interiority/exteriority.
Application of predicate logic is used in linguistics, philosophical logic
and the philosophy of language to represent natural language processing. 

Extensors:

In stable organizations enlargement of scope or operation is specific to
expansions in the population of unities or collective enhancement of
individual unities of the member class as networks. In complex systems,
those which exhibit non-linear and self-organizing tendencies, extensors
are those attributes enabling auto-catalytic clustering into dramatically
complex organizations. 

Irreducibles:

Nearly decomposable systems are those in which the hierarchical
associations of elements comprising the system can never be fully reduced
to autonomous relations. Irreducibles are evidenced in object oriented
computational environments in which coded relations are defined by
stratification of actions within agencies in the form of increasingly
smaller structures of interaction. 

Inclusionaries:

Inclusionary knowledge is a socially and materially embodied activity
arising within the specific details of a particular domain through
abstracted and non-optimized forms of rationalization. Essential in
constraint satisficing, inclusionaries are those attributes which can be
formally incorporated into the domain to influence the evolution of
heuristic searches enabling an organization to learn. 

Exclusionaries:

Exclusionary knowledge is a socially and materially embodied activity
arising external to the specific details of a particular domain of
organization through non-probabilistic, abstracted and non-optimized forms
of rationalization. Exclusionary attributes bar from participation
specific unities, thus pruning those non-essential unities from the member
class domain, stimulating the transformative identity of an organization. 

Permeables:

Code relations between unities are defined by classification of prehensive
attribute flow. The membrane of separation, the interiority/exteriority of
one unity formed as a coded relation to the interiority/exteriority of
other unities, acts as both inhibitor and filter. Networks composed of
organizations require permeables, which enable actions of diffusion
through clustering. 

Entailments:

An entailment is a set of rules pertaining to the emergence of
self-organization by a system in which uncertain conditions and influences
are present. Entailment meshworks are coded into patterned actions of
unity behavior, entailment being the product and feedback of meshwork
conditionals (auto-catalytic patterns) which are signified only by the
computational behavior of data. 


Self-organization and non-linearity

Organization cannot be stopped. The prehensive relation of interiority to
exteriority is to blame. 

Self-organizing systems are those in which spontaneous ordering tendencies
are observed. Complex systems (artificial or natural) are composed of
excessively large numbers of elements that interact simultaneously and in
a parallel fashion including certain computational systems, networks and
databases. Such systems exhibit self-organizing behavior, are
auto-catalytic, are nearly decomposable and are sensitive to initial
conditions when they are in the chaotic regimen. A significant phenomena
observed in complex systems is their non-deterministic bifurcation
evidenced in dynamic trajectories, which emerge as higher-level processes
and include adaptive properties resulting from interactions between
simpler ones. 

Exactly how elements comprising a complex system cooperate to form
higher-level processes and bifurcations leading toward adaptation is the
subject of intense research. At present it would seem that autopoieses is
fundamental to this research. 

Most, if not all complex systems exhibit deterministic chaos as a
principal feature of their adaptive and evolutionary nature. In classical
non-linear theory, a system arrives at a stable equilibrium or oscillates
permanently in a limit cycle. A chaotic system however, may arrive at
state in which it would remain permanently unless affected by a strange
attractor. Complexity theory identifies attractors (static, periodic, and
chaotic) as perturbations that influence direction and course of a
system's evolution. 

Conceptualizing attractors as perturbation patterns of linguistic activity
suggests redirection of attention from a simple structural orientation to
one in which the state transitions of an organization as system is more
fully explored. This is particularly true in complex organizations such as
databases or networks, which are clearly deterministic yet unpredictable.
It would seem, for example, that chaotic patterns of prehensive activity
emerge in specific clustering and nearest neighbor representations. Based
on the features of deterministic chaos, a prehensive based interpretation
may illuminate how an organization is bound to seek new pattern as well as
sustain its tendency for adaptation. 

Clustering and Nearest Neighbors

All of this implies that the study of organizations as systems requires a
phase of investigation preceding any specific analysis of the unities from
which it is comprised. The ontology of an organization is not necessarily
the ontology of its elements. Initial research is exemplified as
interaction with the organization as an act of archeology, an act of
directed experimentation intended to lead to a hypothesis. Allowing the
organization to lead the way is critical. 

The primary goals of knowledge representation are prediction and
description. Prediction involves sampling unities (elements) from the
domain (database) to predict unknown or future values of other relations
(variables) of interest. Description focuses on finding
human-interpretable patterns which illuminate solutions to problems which
can be defined within the domain. In highly complex systems where
non-linearity is a factor, the techniques of clustering and nearest
neighbor may be employed to reveal multiple ontological assessments of a
particular system without determining its purpose or function. 

A cluster is a set of elements grouped together because of their
similarity or proximity. The elements are often deconstructed into an
exhaustive and/or mutually exclusive set of clusters, resulting in a
multi-dimensional mapping of their coded relations. The nearest neighbor
method of representation is non-parametric, that is, a model-free method
sustaining non-model constrained elements for visualizing proximity
estimation through discrimination between unities and unity domains. These
forms of representation respond well to local variations enabling
informative visualization of specific associations of data without concern
for probabilistic and causal quantification, techniques particularly
useful in systems where high degrees of uncertainty are present. Whereas,
clustering is a common descriptive technique for representing the emergent
actions of a finite set of categories, the nearest neighbor technique
enables estimation of these relations which result from the diversity they
contain. 

Data Public

There is no discrete computer. Broadcast television, radio and more
recently the Internet have redefined the notion of 'public', necessitating
that architectonic views be complimented by the infomatic. Every computer
is a mirror of every other computer and every computer is capable of
emulating any other computer or computer network, but the distinction
between interiority and exteriority is arbitrary.  Nevertheless, the
ontology of organization as system often creates the semiotic illusion of
a distinct computer: what is contained within the plastic shell as
commodity. But, every networked computer is by necessity a continuum and
must therefore be considered as public. 

The concept of a 'public' as that defined as an information organization
is applicable to biological, physical, civic, economic, and computational
systems. The specificity of coded relations with regard to unities among
other unities, systems among systems, organizations among organizations,
and networks among networks is meaningful only in the sense of their
'public' implementation. It is in this ontological sense that the public
nature of prehensive unities, which give structural form to the desktop,
folder, and operating system are necessarily public. The prehensive
agencies described, predicates and attributes as coded relations, exist at
all simply because, to be an organization is to be capable of identity. 

This social life of data implies cooperation and competition. Competition
between organizational systems clearly plays a central role in
evolutionary theory and is therefore not at all puzzling, but the very
existence of cooperation among organizational systems is more difficult to
ascertain and requires a discourse formed from alternative theoretical
frameworks. The dynamics of cooperation (which are well characterized in
complexity and game theory) embrace competencies within data itself to
bifurcate codes of relations as self-organizing tendencies. All data is
public data. 

Conclusion

No one doubts the capacities of organizations to sustain meaning in and of
themselves. Prediction of systems behavior of an organization from
knowledge of its goals and its outer environment, with only minimal
assumptions about the inner environment is delimited to perceptions based
on assumptive models and causal functionality. The ontological status of
an organizational system also stems directly from its public nature which
is contextualized in relation to other organizations containing similar
unities. Certain organizations can only be studied through knowledge
representation techniques generated by experimental interaction with the
organization's domain (the networks of coded relations), with little or no
regard for function or purpose. Such experimental research may or may not
reveal a hypothesis regarding the nature and implications of a particular
organization. Let us not forget that the primary goal of knowledge
representation is to reveal something interesting from something unknown. 

Organization leads, directs, and emerges what data wants to be. 
Ontological characterization does and should remain elusive and ultimately
independent of highly specific models about why 'something interesting' is
the way it is. Non-model approaches represent a unique approach to
formulating hypotheses based on experimentation, not to predict or
describe, but rather to reveal. 
                                   



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