The Minimal Ontology Principle
Philosophical Foundations of OPM-based Modelling and Simulation
James Brucato
1
and Dov Dori
2,3
1
Palermo Euro Terminal srl, Banchina Sammuzzo Porto, Palermo, Italy
2
Massachusetts Institute of Technology, Boston, U.S.A.
3
Technion, Israel Institute of Technology, Haifa, Israel
Keywords: Object Process Methodology, Software Engineering, System Engineering, Computability, Compositional
Logics.
Abstract: Traditionally, Software Engineering (SWE) and Systems Engineering (SE) were almost different disciplines
with little overlap and with a different set of approaches and concepts. Yet, both SWE and SE reflect two
sides of the same coin: both revolve around development and lifecycle support of systems. While SWE
focuses on software-intensive systems, SE has focused on systems in general. However, most systems
nowadays not only combine hardware and software, ever more intertwined and increasingly interdependent,
they also comprise humans and organizations as stakeholders. This work aims to underline the importance
of the holism as highly effective approach to both SWE and SE as it is the result of a huge and very
representative set of philosophical investigations, partially illustrated in this work, assuming that the
historical distinction between SWE and SE is becoming ever less relevant and that it is high time they be
treated as one overarching discipline provided with a minimal ontology in order to facilitate the conceptual
modelling process and improve models understandability. We propose the Object Process Methodology
(OPM), together with its holistic approach to systems modelling and simulation, as main building block of
the bridge between SWE and SE disciplines with respect the issues above.
1 INTRODUCTION
This work is intended to investigate the validity and
usefulness of the distinction between SWE and SE
with respect to the modelling and simulation
approach. Since they are considered as different
disciplines, despite the fact that they are becoming
ever more interdependent because of the highly
increasing number of systems that nowadays
combine hardware and software to succesfully meet
the stakeholders expectations and the users needs,
we claim that an effective modelling and simulation
approach shall be able to merge all the different
aspects pertaining both the disciplines. To reach this
goal it shall be provided, first, with a strong
philosophical background in order to take into
account the most wide set of historical facts, second,
it shall be domain independent in order to be highly
flexible and useful beyond the disciplines
boundaries, third, with the smallest set of symbols
composing its vocabulary and its syntax in order to
be easy to learn maximizing, in the same time, the
system models understandability and sharing.
Along and as results of their evolution, humans have
been able to invent a huge set of languages (oral,
written, iconic, sculpture, architectural, melodic,
scientific and so on) in order to create amazing
pictures of the world. Even those all the languages
are limited in their constituents (building blocks)
they provide the human kind with a source of
potentially infinite combinations, but only and only
if there is a set of rules to combine simple symbols
and/or set of symbols generating more complex
combinations of them.
We propose the OPM (Dori, 2002) as a bridge
between SWE and SE because of its strongly holistic
oriented modelling and simulation approach that
properly fulfils the requirements above.
In the same time, the minimal ontology principle
is illustrated in order to provide the OPM with a
clear definition of its assumtions.
405
Brucato J. and Dori D..
The Minimal Ontology Principle - Philosophical Foundations of OPM-based Modelling and Simulation.
DOI: 10.5220/0005140804050409
In Proceedings of the International Conference on Knowledge Engineering and Ontology Development (KEOD-2014), pages 405-409
ISBN: 978-989-758-049-9
Copyright
c
2014 SCITEPRESS (Science and Technology Publications, Lda.)
2 PHILOSOPHICAL
FOUNDATIONS OF
MODELLING AND
SIMULATION
From a philosophical point of view, the systems-
software dualism can be traced back to the 1950’s
and early 1960’s when the AI (Artificial
Intelligence) was emerging as a new, unpredicted
and unpredictable discipline, historically identified
as a branch of the cognitive sciences paradigm. AI
was founded at a conference held during the summer
of 1956 at Dartmouth College in Hanover, New
Hampshire where John McCarthy, Marvin Minsky,
Nathaniel Rochester and Claude Shannon presented
a very innovative work able to merge a considerable
number of philosophical theories developed in the
early 20th century, including linguistics
investigations and epistemological approaches, and
the most advanced engineering experimental works
(McCarthy, Minsky, Rochester and Shannon, 1955).
Since the Dartmouth conference, the
international scientific community interest toward
the AI rapidly increased and the most part of further
investigations proofed the presence of an
epistemological lack of effectiveness specially with
respect to the human knowledge representation area.
This, in turn, led the scientific community to explore
the possibility of finding a common terrain where
would be possible a productive confrontation
between different disciplines, methodologies and
approaches in order to establish a new common
paradigm serving as scientific and academic
theoretical bridge, the Cognitive Science paradigm.
Recently it has been defined as a contemporary,
empirically, based effort to answer long-standing
epistemological questions – particularly those
concerned with the nature of knowledge, its
components, its development, and its deployment
(Gardner, 1986).
It is relevant that there was a close constant
overlap between the results and the assumptions of
most of those theories similar to a chain reaction
even those they were developed in different times
and places, sometime very distant one from each
other, and that it has been demonstrated that all of
them were founded assuming the validity of the
Frege’s Principle, (Frege, 1893), known as Principle
of Compositionality, that states the meaning of a
complex expression is determined by the meanings
of its constituent expressions and the rules used to
combine them (Brucato, 2003).
Early Cognitive Science scopes and assumptions,
including for first the Frege’s Principle of
Compositionality we assume as its main
epistemological pillar, they continue to play a
central role in many contemporary disciplines like
SWE and SE modelling and simulation. More
specifically, they are the philosophical foundations
of OPM-based modelling and simulation holistic
approach to SWE and SE we identify with but not
limit to:
Wittgenstein's Tractatus logico-philosophicus
(1921). It contains the distinction between the
World, and the Language (s) used to describe
(give a picture of) it. This is the main
assumption of the well known Picture Theory
of the Meaning Wittgenstein developed to state
that the language is a picture of the world and it
is obtained combining the language building
blocks (the signs, later called symbols) into
propositions according to the predetermined set
of syntactic rules specifically pertaining to the
adopted language. He often used to compare
the process of composing a syntactically
correct proposition to the work of an architect
who designs and constructs a new building. If
something has been designed wrongly, the
building will not be able to be used for the
intended purposes, hence it will be basically
useless, with respect to the language, if the
syntactic rules are not properly followed the
proposition will be non-sensed and, in some
cases, it will also be not understandable;
Hierarchy of Languages (Russell, B., 1905).
Here Bertrand Russell illustrated the necessity
to adopt a higher level language to completely
and consistently describe a lower level
language. This theory has been formalized as
Type Theory;
The Mathematical Theory of Communication
developed by Shannon and Weaver (Shannon,
1938). The communication is assumed to be
the result of the information transmitting
process. Using a physical channel, a
predetermined quantity of information the
sender previously compressed through a code
he shares with the receiver, is possible to
reproduce at one point (the destination) either
exactly or approximately a message selected at
another point (the source);
The ballistic researches of Von Neumann
(1945) led him to the definition of a stable
machine structure, known as Von Neumann
Architecture, which served as the basis of all
the modern calculators and computational
machines;
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Alan Turing’s definition of Computability
(Turing, 1936), a reformulation of Gödel’s
Undecidable Problem and inspired by
Newman investigations onto the decidability
of mathematical propositions.
3 PHILOSOPHICAL OUTCOMES
OPM is different from other modelling languages
not only because it allows to go beyond what
Wittgenstein called the limit of the Language,
consisting of the impossibility to completely
describe the World, it also subsumes most of the
theories involved in the foundations of the Cognitive
Science paradigm.
In addition, OPM provides stakeholders with
both the iconic, graphical, view of the systems and
its equivalent textual description. The two reinforce
one each other recursively through the dual-channel
processing, as they cater to the visual and verbal
cognitive processing channels (Mayer, 2005; Dori,
2008).
OPM also takes into account both the structure
and the behavior of systems in order to provide a
comprehensive vision of the building blocks that
compose a system together with the processes
involved and requested to perform the tasks it has
been designed for.
All these widely appreciated OPM features
impressively allow to model its own theoretical
foundations as well with all the positive effects this
can have in particular with respect to SWE and SE
as OPM represents a unique and highly effective
meta-modelling and simulation domain independent
holistic approach.
Following are the Shannon’s schematic diagram
of a general communications system (Figure 1) and
its OPM system model version according to the
Shannon and Weaver Mathematical Theory of
Communication.
Figure 1: Schematic diagram of a general communications
system according to Shannon definition.
Figure 2: OPD of Shannon’s Mathematical Theory of
Communication and related OPL.
4 THE MINIMAL ONTOLOGY
PRINCIPLE DEFINITION
A parallel development on a smaller scale has
happened within both SWE and SE with the
realization that models should serve as foundational
architecting and design artifacts. For SWE this
happened in the early 1990s, when the object-
oriented (OO) idea grew out of being a paradigm
underlying OO programming languages to the
realization that prior to coding, the program, or the
software system, should be modelled. Initially there
was the “war of languages” with over 30 different
notations and ideas trying to prevail. Then, in 1997
UML was adopted under the auspices of OMG with
9 different diagram types, which grew to 13 with the
transition to UML 2.0 in 2005. The first author's
proposal at an OMG Technical Meeting in Florida in
2000 to extend UML from the software domain to
the general systems domain was dismissed with no
consideration whatsoever, only to be resurrected six
years later with the birth of SysML. SysML was
developed and adopted in 2007 in response to OMG
UML for Systems Engineering RFP. Like UML 1.x,
it had 9 diagram types, but not quite the same set.
Some were removed from UML 2, some modified
and a couple added. Why 9 diagram type (or views,
or viewpoints)? Why 13? Why not more? Isn’t it the
case that more is better? If so, why not adopt
DODAF 2.0 from 2009? It has 51 Viewpoints
(BTW, up from 26 in DODAF 1.x from 2003)!
This trend of "diagram creep" – adding more
diagram types to a language – just adds
complicatedness to an already complicated world of
conceptual modeling languages. AS a reaction, in
order to put a stop to this trend, we offer the
following Minimal Ontology principle: If a system
can be specified at the same level of accuracy and
detail by two languages of different sizes, then the
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language with the smaller size is preferred over the
one with the larger size.
This principle does not only make perfect sense,
it is also in line with the long accepted Ockham’s
Razor (Ockham, 1495) – a principle attributed to the
14th century logician and Franciscan friar William
of Ockham, England. The principle states that
"Entities should not be multiplied unnecessarily."
Or, in one of its original Latin forms: "Pluralitas non
est ponenda sine necessitate." The most useful
statement of the principle for scientists is "when you
have two competing theories that make exactly the
same predictions, the simpler one is the better."
Ockham’s Razor inspired also the Minimum
Description Length (MDL) Principle (Rissanen,
1978), a method for inductive inference that
provides a generic solution to the model selection
problem, i.e., how does one decide among
competing explanations of data given limited
observations. MDL is based on the insight that any
regularity in a given set of data can be used to
compress the data by describe it with fewer symbols
than the number of symbols needed to describe the
original data. In a similar vein, any symbol system
(i.e., a language) that can describe a given system
using fewer symbols (a smaller language) is more
succinct and therefore preferable over a larger
language (a language with more symbols), as using
the smaller language exerts a smaller amount of
cognitive load on the human modeler. Alleviating
the cognitive load off the human modeler is highly
desirable because the modeler must cope with the
inherent complexities of man-made systems to be
built (systems engineering) or natural systems to be
investigated (science), so anything that we can do to
help by providing a simpler language is of
tremendous value.
A second principle that caters to the same
objective of facilitating the conceptual modeling
process and making the model more accessible and
comprehensible is the dual channel processing
(Mayer, 2005; Dori, 2008): A model that can be
presented bi-modally in both graphic and text is
preferred over a model that can be presented in only
one of the modalities.
The cognitive-physiological basis for this
principle is that the human mind is geared to accept
both visual-pictorial-graphic signals and audio-
verbal-written signals. Popularly, this is often
referred to as the left brain/right brain functions.
Indeed the left hemisphere is dominant in language,
processing what one hears and handling most of the
duties of speaking. The right hemisphere is mainly
in charge of spatial abilities, face recognition,
comprehending visual imagery and making sense of
what we see. Thus catering to “both sides of the
brain” through language and pictures is more likely
to get the message—in our case the conceptual
model—across.
If we accept these two principles, then we need
to find the minimal universal ontology—the
ontology that is necessary and sufficient to model
the universe and systems in it. We start by first
asserting that any thing in the universe either exists
or happens. We proceed with a series of questions
and answers:
Q1: What are the things that exist in the
universe?
A1: Objects exist or might exist.
Q2: What are the things that happen in the
universe?
A2: Processes happen or might happen. But
processes cannot happen in vacuum! So:
Q3: What are the things to which processes
happen?
A3: Processes happen to objects.
Q4: What do processes do to objects?
A4: Processes transform objects.
Q5: What does it mean for a process to transform
an object?
A5: Transforming of an object by a process
means:
creating (generating) an object
destroying (consuming) an object
affecting an object.
Q6: What does it mean for a process to affect an
object?
A6: A process affects an object by changing its
state. Hence, objects must be stateful, i.e., they must
have states.
Q7: What are the main aspects that define any
existing system?
A7: A system can be defined with respect to two
major aspects: structure and behavior. Structure is
the static aspect; it relates to the question what is the
system made of?
From the structural aspect, a System is a finite
set of components and their time-invariant
interconnections. Behavior is the dynamic aspect; it
relates to the question how does the system change
over time?
Q8: What additional aspect pertains to man-made
systems?
A8: Function – the utilitarian, subjective aspect:
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why is the system built? for whom? who benefits
from operating it? What is the context of its use?
If we accept these answers, then we are ready to
prove the following theorem:
The Object-Process Theorem
Stateful objects, processes, and relations among
them constitute a necessary and sufficient universal
ontology.
The following is a complementary statement:
The Object-Process Corollary
Using stateful objects, processes, and relations
among them, one can model systems in any domain
and at any level of complexity.
Proof: Part 1 - necessity
Stateful objects and processes are necessary to
specify the two system aspects:
Specifying the structural, static system aspect
requires stateful objects and relations among them.
Specifying the procedural, dynamic system
aspect requires processes and relations between
them and the objects they transform.
Proof: Part 2 - sufficiency
Stateful objects and processes are sufficient to
specify any thing in any system:
Anything that exists can be specified in terms of
stateful objects and relations among them.
Anything that happens to an object can be
specified in terms of processes and relations between
them and the object they transform.
5 CONCLUSIONS
Having determined and proved the Object-Process
Theorem, according to the minimal ontology
principle, the optimal conceptual modeling language
must have just two types of concepts - stateful
objects and processes - along with relations among
them. Indeed, this is the theoretical foundation of
OPM. It is in the process of becoming ISO 19450
Standard - Publicly Available Specification, a freely
available ISO document that defines the syntax and
semantics of OPM (ISO, 2014). The document
length is around 140 pages, compared with 1400
pages of the current OMG UML 2.2 Standard plus
272 pages of SysML that builds on the UML
Standard documentation.
With respect to the current regrettable chasm
between SWE and SE, we should do everything in
our power to unify these two seemingly disparate
disciplines, because both handle two complementary
views that each contemporary system features: the
physical view (the focus of SE) and the informatical-
cybernetic view (the focus of SWE). To marry SE
with SWE we need a simple common language that
both domains will speak freely. Catering to both
physical and informatical things (objects and
processes). OPM can serve as an ideal bridge
between the two.
ACKNOWLEDGEMENTS
This work was supported by EU FP7 VISIONAIR
Project 262044 and Gordon Center for Systems
Engineering at Technion.
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