1. The OSI network communications model in diagrammatic context
Jim Curran
Dissertation submitted in partial fulfilment of the requirements for the
Master of Arts in Information Design
University of Reading
2004

2. Abstract
I examine a popular model of computer network communications from three primary angles:
history, taxonomy, and psychology. I argue that the model in question is important because
it provides structure to an otherwise invisible, intangible system and facilitates teaching
about and understanding of its concepts. In tracing the development of the model over a
period of about 15 years I reveal that it emerged in parallel to the challenges encountered and
problems solved when disparate, geographically dispersed computer systems were to be
inter-connected. I attempt to place the model in the context of diagram taxonomy and review
psychological literature relevant to the diagrammatic communication process. I analyse the
model in the light of visual ‘grammars’ based on perceptual research and of studies of
metaphor. I discuss the idea of transformation and conclude by explaining the most
important factors in achieving successful transformations of abstract technical material: the
transformer’s knowledge of viewers’ tasks, visuo-spatial abilities, and background
knowledge, the relation between the representation and the real system, and the
representation’s adherence to perceptual conventions.

3. Acknowledgements
My thanks to these people who went out of their way to make sure I got copies of papers I
couldn’t find anywhere else: Alison Black, David Feinstein of the School of Computer and
Information Sciences at the University of South Alabama, Lawrence Lipsitz of Educational
Technology Magazine, and Barbara Tversky of Stanford University. Special thanks go to
Richard Lowe of Curtin University of Technology, Australia, for discussing my project with
me and sending me copies of several enlightening articles.
I’m grateful to the library staff at Imperial College London, the University of Illinois at
Chicago, Illinois Institute of Technology, and Northwestern University for allowing me
access to their collections.
To my parents, Jim and Fran Curran, who helped me manage my affairs in the US while I
was at Reading, all thanks and love and especially to Sheow Lu, my fiancée, who tolerated my
absence for a year and gave me support and encouragement throughout.

4. Contents
Introduction 1
What are diagrams? 2
Meaningful space 2
Making the invisible visible 3
The value of diagrams 3
Externalization 3
Why study diagrams? 4
How to study diagrams 4
Background and history 5
What the OSI model depicts 5
Communication protocols 6
The power of the OSI model 7
Development of the OSI model 7
The situation before the introduction of the OSI model 8
The problem of incompatibility and potential solutions 8
Widespread acceptance of the layering concept 11
The influence of X.25 11
The influence of datagram services 12
Active work on the model 13
Reception of the model 13
What the model was expected to be used for 14
What the model turned out to be best for 14
Taxonomy 15
What taxonomies can do 15
Meta-taxonomies for diagram research 15
Blackwell and Engelhardt (1998) 15
Blackwell and Engelhardt (2002) 17
A taxonomic analysis of the OSI model 19
Doblin’s taxonomy 19
Owen’s taxonomy 19
Psychology 23
Perceptual processing 24
Visual syntax 25
Cognitive processing 28
Background knowledge 29
Mental representations 29
Visuo-spatial ability 30
Metaphor 30
The transformer and transformation 32

5. Achieving successful transformation 34
Addressing the viewers’ needs 34
The viewers’ tasks 34
The viewers’ visuo-spatial abilities 34
The viewers’ background knowledge 35
Structuring the diagram appropriately 35
Relation between the representation and the real system 35
Accompanying text 35
Adherence to perceptual conventions 36
Drawing inspiration from exemplars 37
References 38

6. Introduction
In this dissertation I examine the Open Systems Interconnection reference model (the ‘OSI
model’) and place it in the context of diagramming research and practice in general and in
particular.
The OSI model provides the standard framework for explaining how computers
communicate with one another. First published in 1984 by the International Organization for
Standardization (ISO), the OSI model was developed over several years. Its roots go back to
the late 1960s and the start of the precursor to today’s Internet, the ARPANET, and the
challenges its designers met in getting disparate, geographically separated computers to
communicate.
Though the OSI model is conceptual and completely intangible, it has been expressed
diagrammatically since its origin. Diagrams that would be recognizable to any network
engineer today were hand-drawn in the very first meeting of the committee that created the
model (McKenzie 1978).
Figure 1. Layers in the reference model (from ISO 1978)
Compare with the published version in Figure 2
Figure 2. The OSI model (from ITU-T 1994)
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7. Although the OSI model was originally intended to be used as a reference structure for
the development of communications standards, it largely failed in that regard (e.g., Day and
Zimmerman 1983; Wikipedia 13 April 2004). The OSI model remains, however, the model of
choice for teaching, understanding, and communicating networking concepts (Testerman
1999).
Open any networking textbook published since the mid-1980s and you are sure to find a
rendition of the OSI diagram. Walk through any organization that concerns itself with
networking and you are sure to see diagrams based on the OSI model drawn on whiteboards.
Ask a network engineer what he does and he may tell you he’s a ‘layer two’ or ‘layer three’
specialist. The pervasiveness and utility of the model have convinced me of its importance
and motivated me to undertake the fairly detailed examination of it that follows.
◆
The first question facing me was, ‘Just how do I go about examining a diagram?’ Behind that
question, I found, lurked another: ‘What is a diagram, anyway?’
What are diagrams?
A diagram is a form of picture. Twyman (1985) defines a picture as ‘some hand-made or
machine-made image that relates, however distantly, to the structure of real or imagined
things’. But it is a special kind of picture, one that exhibits relationships (Garland 1979;
Richards 2002) using symbols and their spatial arrangement (e.g., Vekiri 2002). Kim et al.
(2000) call diagrams ‘abstractions of real systems’ and Tversky (2002) adds that graphics
used in this way are a ‘modern (18th c.), Western invention’.
The OSI model is an abstraction of a real system, and it exhibits relationships among its
components using symbols (in the form of rectangular boxes) and their spatial arrangement.
The OSI model is expressed as a static diagram, and so it aligns with Engelhardt’s (2002)
definition as a ‘visible artifact on a more-or-less flat surface, that was created in order to
express information’.
As well, it agrees with this observation by Albarn and Smith, quoted in Sless (1981): ‘The
diagram is evidence of an idea being structured – it is not the idea but a model of it, intended
to clarify characteristics of features of that idea’.
Among the properties of diagrams, two stand out as most important in explaining the
power of the OSI model: meaningful spatial arrangement and making the invisible visible.
Meaningful space
I have borrowed the term ‘meaningful space’ from Engelhardt (2002), and am using it to
refer to a key property of diagrams. In fact, Tversky (2001) calls ‘using space and elements in
it to convey meaning’ the key to graphics.
About this there is wide agreement (e.g., Sless 1981; Winn and Holliday 1982; Richards
2002): The spatial arrangement of the elements of a diagram provides information not
available in straight text. According to Sen, ‘When we represent problems using diagrams, it
usually implies that locational or adjacency properties are important, e.g., organic chemical
structures, free body diagrams in physics, architect’s plans, data structures in computer
science’ (Sen 1992).
2

8. Tversky (2001; 2002) maintains that that spatial arrangements are ‘usually not accidental
or arbitrary’ and that some devices are ‘cognitively natural’.
Indeed the spatial arrangement of the OSI model is highly meaningful and not accidental
or arbitrary. I will have more to say about this in a later section.
Making the invisible visible
The property of diagrams that is perhaps most relevant to this dissertation is their ability to
render the invisible visible. Owen (1986), Richards (2000; 2002), and Tversky (2001; 2002)
make much of this. According to Richards, diagrams make the invisible visible using graphic
metaphor [something regarded as representative or suggestive of something else], while
Tversky attributes the effect to analogy [equivalency or likeness of relations].
In computer networking, the visible components of the systems do little to explain the
underlying processes. At the most tangible level, data transmissions are electromagnetic
waveforms. These waveforms, whether conducted over copper wire as electricity or in the air
as radio waves, are naturally invisible. Even the light carried over optical fibres pulses too
rapidly for the eye to detect. For this reason, abstract diagrams such as the OSI model tend to
be more useful than literal ones in explaining inter-computer communications.
The value of diagrams
Many claims are made for the value of diagrams. They are held to be more direct than
alphabetic written language (Tversky 2001), with reduction of complexity achieved by
omitting unnecessary detail (Lowe 1994; Tversky 2001), allowing inspection of related pieces
of information at a glance (Winn and Holliday 1982).
The value of diagrams in facilitating learning is noted by Winn and Holliday (1982) and
Vekiri (2002). Lowe (1993) cites evidence from Mayer that ‘diagrams can make processing
more effective, resulting in improvements in tasks such as conceptual recall and performance
on related problem-solving tasks’.
Tversky (2001) reviews a number of functions of graphic displays, including the attraction
of attention and interest, stimulation of memory, the recording of ideas and the ability to
make them public, and facilitation of discovery and inference.
Externalization
The ability of diagrams to externalize thought is given special attention by Sless (1981), Sen
(1992), and Ittelson (1996), who hold that the cumulative nature of scientific and technical
progress depends upon diagramming. This is likely because once the concepts are ‘taken out
of our heads’ (Ittelson 1996), they can be more easily shared with other people, who can
‘inspect, reinspect, and revise them’ (Tversky 2002). This externalization of thought
facilitates group communication (Tversky 2001).
3

9. Why study diagrams?
In other words, by studying them, what do we hope to achieve?
The ideal, from a practical rather than theoretical point of view, is to increase the
effectiveness of diagrams for users and learners (e.g., Winn 1993; Vekiri 2002). This can be
done in two ways: by using the results of studies of diagram effectiveness to inform the
designer and by using them to inform the instructor.
Lowe (1994) notes that ‘the way diagrams are used in scientific instruction typically is not
informed by a deep understanding of how people process information presented in this
format’. This understanding is necessary because diagrams ‘have the potential to be far more
difficult to process than more “realistic” pictures because of the nature of the subject matter
and their high degree of abstraction’ (Lowe 1994).
The trouble for the practising designer or instructor is that the findings of particular
studies are difficult to generalize from their contexts (Scaife and Rogers 1996). Still, findings
on the effects of several factors on the usefulness of diagrams to learners can provide
guidance to the designer or instructor. These include knowledge of the viewers’ tasks, visuo-
spatial abilities, and background knowledge in the subject, the relation between the diagram
and the system it depicts, and adherence to perceptual conventions. Each will be elaborated
on in later sections.
How to study diagrams
Now that I have discussed what diagrams are, what they are good for, and why it is
worthwhile to study them, I can return to my first question, which was ‘Just how do I go
about examining a diagram?’
The path, of course, has been trod before. The most valuable suggestions, which largely
overlap, come from Sless (1981) and Sampson (1985). Sless calls for a ‘formal analysis of
diagrams, a psychological account of their use, an historical study of their development, and
a review of their current status in our culture’ (Sless 1981). Sampson, examining the
linguistic study of writing, proposes three categories: typology, history, and psychology.
Taking their lead, I examine the OSI model from three angles: background and history,
taxonomy, and psychology.
For background and history, I explain the concepts involved and trace the history of the
development of the OSI model in some detail. Under taxonomy, I look at classification
systems for graphics and explain the place of the OSI model within them. For psychology, I
view diagrammatic communication as a process that occurs in two separate parts: between
the viewer and the diagram and between the designer and the diagram. I explore factors that
affect communication on both sides of the divide. I finish by reviewing implications for the
design of diagrams that depict abstract systems.
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10. Background and history
In the field of computer networking, diagrammatic explanations are frequently used. Semi-
literal drawings such as the one in Figure 1 may be useful for hardware installation but are
ineffective for describing the mechanisms of inter-computer communications.
Figure 3. A semi-literal drawing of inter-computer connectivity.
This is because the visible components of networking systems do little to explain the
underlying processes. At the most tangible level, data are electromagnetic waveforms. These
waveforms, whether conducted over copper wire as electricity or in the air as radio waves,
are naturally invisible. Even in the case of optical transmission, the light carried over the
fibres pulses too quickly for the eye to detect. The signals are further abstracted by the
software on each computer that controls communications, making the processes ‘even more
invisible’.
Abstract diagrams tend to be more useful than literal ones in explaining inter-computer
communications. Green explained the importance of examining the functions a system
performs when characterising networks: ‘There are other ways of characterising networks
(by application, by geography, by ownership, by topology), but ‘None of these four
approaches really reveals what the network is actually doing. A much better scheme is to
examine the total repertoire of functions that the network must provide in making up an
effective access path between two end users’ (Green 1980a).
The best framework we have for explaining how networks work is the OSI model,
developed by ISO in the late 1970s–early 1980s. The OSI model introduced to a wide
audience a logical structure that can be presented in graphic form and which provides a
framework for people to ‘hang concepts on’.
What the OSI model depicts
The OSI model is a conceptual device that abstracts the complex functions and relationships
involved in inter-computer communications. Diagrammatically, it can be described as two
identical columns of seven rectangles each placed atop a long rectangle.
5

11. Figure 4. A simplification of the OSI model (adapted from X.200)
Each column represents a computer, and each rectangle in the column represents a
collection of related functions performed by software components of the computer. The long
rectangle at the bottom represents the physical medium (for example, a copper wire, an
optical fibre, or air in the case of wireless transmission) through which signals exchanged
between the two systems are propagated.
The columns are hierarchically arranged. The lowest layer, closest to the physical
medium, concerns itself with transmitting and receiving electromagnetic signals through the
medium. As one progresses up through the column, the functions become more abstract.
They range, for example, from error-checking and retransmission mechanisms at the lower
layers through to message routing in the middle to setting up a file transfer near the top.
Each layer has a name and number. The layers are numbered bottom-to-top from one
(Physical) to seven (Application).
There is a lateral dimension to the model as well. Each layer must be matched by its peer
in the computer opposite (or relayed by another device) for intelligible communication to
take place.
Communication protocols
The model cannot be explained without delving into communication protocols. ‘For one
computer to send a message to another computer across a network, more has to be done than
simply pump the bit-train [a series of electromagnetic ‘on–off’ signals] down an appropriate
wire’. Protocols – ‘a system of standard message formats together with a set of rules for their
use’ (Whitby-Strevens 1976) – are necessary.
Such protocols are required for intelligible communication between peer layers. ‘To cater
for the various kinds of communication between processes possible in a network, it is
essential to have sets of rules governing interactions to ensure they proceed in an orderly
fashion’ (Davies and Barber 1973).
Protocols can be an intimidating concept, but they are not unique to computers, as Black
(1991) points out: ‘One of the most interesting aspects about computers is how they exchange
information with each other. Remarkably, their communications are similar to the
communications between humans, because, like humans, computers communicate with each
other through symbols and agreed-upon conventions’.
6

12. The power of the OSI model
When a preliminary OSI model was first published in the 1978, it was praised as a conceptual
breakthrough. Green (1980b) called it a ‘particularly clear way of visualizing all of the layers
of a network architecture and their component protocols’.
By the late 1980s, the model became ‘pervasive’ (Black 1991). Today, virtually every text
on computer networking presents it or takes it for granted. Its usefulness as a teaching tool is
frequently mentioned (e.g., Testerman 1999; Wikipedia 13 April 2004). But the OSI model
was not ‘invented’ by the ISO study group that developed it in the late 1970s and early 1980s.
Its roots go back farther than that.
Development of the OSI model
Black (1991) lists two developments that provided the impetus for the development of the
OSI model: ‘(a) the emergence of layering and structured techniques in the design of
complex networks and (b) the recognition of the need for compatible communications
architectures between different manufacturers’ protocols’.
The ARPANET, which we know today as the Internet, evolved a layered approach. The
ambitious goal of its founders was to interconnect several computer systems made by
different manufacturers. Green (1980a) pointed out that a layered concept naturally emerges
when an ordered list is made of the functions involved in interconnecting heterogeneous
systems. Of course, Green says this in hindsight. ISO makes it sound similarly effortless: ‘A
model is an abstraction or simplification that makes a concept more understandable. In
order to comprehend models of complex systems, it is important to partition the structures
into easily comprehended parts. Communications systems are often envisioned in terms of
“layers” of functions’ (ISO 1978).
The model did not spring forth from nowhere. It evolved over the course of more than a
decade. I will trace its origins and development in the next sections.
The situation before the introduction of the OSI model
Before the model was created, networking was a haphazard business. ‘Everybody is building
networks, but as yet nobody really knows how – we lack any formal, or “high level”,
framework in which to assess networking issues’ (Whitby-Strevens 1976).
Writing soon after the development of the model, Green explains that ‘For a long time it
has not been entirely clear just how one should think about the bits and pieces that make up
a computer network and how they should fit together. This confusion has been felt at all
levels by researchers, architects, implementers, and researchers.’ And ‘it used to be the case
that each software implementation was neither modularly organized nor generic, but instead
was put together ad hoc to do a particular job; when the job changed or the means of
carrying out a single function changed, everything had to be rewritten’ (Green, 1980b).
Black concurs: ‘The early computers that provided communications services were
relatively simple.…These early systems used conventions based on the telegraph and telex
applications, and transmitted messages with special codes…These codes were often used and
interpreted differently by the manufacturers of communications products.…Moreover, the
earlier networks…often used several different proprietary protocols that had been added in a
somewhat evolutionary and unplanned manner….The protocols in the networks were often
poorly and ambiguously defined’ (Black 1991).
7

13. The problem of incompatibility and potential solutions
In actuality, the situation began to change in 1966, when we find Marill and Roberts groping
with the problem of computer incompatibility. ‘Incompatible machines represent an old
problem in the computer field’ (Marill and Roberts 1966). They examined the two ‘time-
honored remedies’ to the problem: using identical computers and writing the programs in a
high-level language that could be compiled on different machines. They judge that ‘these
remedies have worked quite badly in the past and will probably work as badly in future time-
sharing environments’ (Marill and Roberts 1966). They explain a possible solution – ‘the
establishment of a message protocol, by which [they meant] a uniform agreed-upon manner
of exchanging messages between two computers in the network’ (Marill and Roberts 1966).
In June 1967, Roberts reported that an experiment connecting one type of computer in
Cambridge, Massachusetts to another in Santa Monica, California using the message-
protocol method had been a success. Also, a generalized ‘communication protocol’ was in
development and researchers across the country had ‘agreed to accept [the] single network
protocol so that they may all participate in an experimental network’ (Roberts 1967) – the
ARPANET.
Carr et al. (1970) report their progress in getting different ‘host’ computers
communicating with each other. They had to use a network specified by a contracting firm.
In their words, ‘The format of the messages and the operation of the network was specified
by the network contractor (BB&N)’, and so ‘it became the responsibility of representatives of
the various computer sites to impose such additional constraints and provide such protocol
as necessary for users at one site to use resources at foreign sites’ (Carr et al. 1970). This
implies a clean division of functions between the host computers and the network itself.
The first precursor to the OSI model that I am aware of appeared in Crocker et al. (1972),
who were reporting their work on ARPANET protocols. It is reproduced in Figure 5. They
explain the big picture this way: ‘A user at his terminal, connected to a local HOST, controls a
process in remote HOST as if he were a local user of the remote HOST’ (Crocker et al 1972).
Figure 5. The layers of protocol (from Crocker et al. 1972)
Crocker et al. (1972) make an interesting distinction between communication at the
lowest layer and that at the layers above: ‘actual’ versus ‘virtual’. This is because the only
8

14. signals being sent and received are at the lowest level. For the rest, a process of ‘packing’ and
‘unpacking’ the messages occurs on each host computer. (This process is explain further in
the section on metaphor on page 32.)
The layered concept apparently took some time to take hold. Analysis of Mills (1972)
provides evidence that the concept had not yet propagated outside the ARPANET
community. Mills provides what he describes as ‘a greatly simplified block diagram of a
typical teleprocessing system. In this diagram the communication subsystem is shown as a
collection of functional components’. A collection implies a random ordering, and indeed the
diagrams in the paper reflect this, with one showing the communication network at the top
and one at the bottom.
Figure 6. Typical teleprocessing system (from Mills 1972)
(Note that the communication network is at the top and the application programs are at the
bottom, the reverse of the OSI model.)
Figure 7. Typical front-end processor (from Mills 1972)
(In this case, the communication network is at the bottom.)
9

15. Davies and Barber (1973) also show ambivalence in the way they represent layers. In an early
chapter, they arrange the protocol elements in a line, horizontally, as shown in Figure 7.
Figure 8. Variety of protocols in a network (from Davies and Barber 1973)
In a later chapter, they adopt a layered approach. This is no oversight on their part. ‘The
protocol structure of packet switching networks was described at length in Chapter 11. It is
apparently at this point that much of the conceptual difficulty arises in modern data
networks. One of the figures of that chapter is redrawn in Figure 14.1 to show the ‘higher-
lower’ relationships of these protocols’ (Davies and Barber, 1973 – italics mine).
Figure 9. Examples of protocols and interfaces (from Davies and Barber 1973)
10

16. That they redrew the diagram with stacked protocol layers and used terms such as
HOST–HOST protocol, HOST–IMP control module, and IMP suggests that they were
familiar with ARPANET concepts. As Green (1980a) states: ‘The ARPANET…had a great
influence on all succeeding computer networks’.
Widespread acceptance of the layering concept
By 1975, the layered concept was common currency. ‘A basic principle, generally accepted
nowadays, is a layered structure, made up of quasi-independent levels’ (Pouzin 1975). Pouzin
included a diagram that takes on the familiar ‘U’ shape of the OSI model.
Figure 10. Network structure (from Pouzin 1975)
The influence of X.25
In the mid-1970s, work proceeded on the protocol that was to be called X.25. Rybczynski
(1980) contends that the development of X.25 was ‘a response to the rise of public data
networks’, especially within countries whose communication systems were controlled by
government-based Post, Telephone and Telegraph administrations (PTTs). In order to
interconnect the countries’ networks, standard protocols needed to be agreed. In fact, ‘the
commercial viability of these networks hinged largely on the development and adoption of
standard access protocols’ (Rybczynski 1980).
Cotton and Folts (1977) reported that the first three levels in the ‘hierarchy of interface
levels’ they present had been worked out for the X.25 protocol. The fourth level was simply
‘higher level’ (end-to-end system and user protocols), which would later become four
independent levels itself.
While X.25 predates the OSI model, and indeed was not designed with the OSI model in
mind (Cotton and Folts 1977; Marsden 1985), it could not help but to have been influenced
by work on the ARPANET. We can see the resemblance clearly in Figure 11.
11

17. Figure 11. Hierarchy of interface levels (from Cotton and Folts 1977)
(I have ‘ghosted in’ the right half that was implied in the original diagram.)
The lower levels covered by X.25 were not where the action was, however. According to
Rose, ‘To be sure, OSI has introduced terminology and notation for discussing end-to-end
services in a consistent fashion. Nevertheless, in terms of technical advancement, the lower-
layer infrastructure of OSI is uninteresting’ (Rose, 1990).
The influence of datagram services
I was not able to determine whether the paper Generic Requirements for Datagram Services
was submitted before or after ISO decided to form the committee. But this paper, submitted
to ISO in February 1977 by the American National Standards Institute (ANSI), contained a
fairly mature diagram with six levels of protocol. It is shown in Figure 12.
Figure 12. Protocols of the datagram network (from ANSI 1977)
12

18. Active work on the model
In 1977, ISO created a new subcommittee called ‘Open Systems Interconnection’
(Zimmerman 1980). The task they faced at their first meeting in February 1978 was ‘to define
a model for network architecture and to consider the standardization of higher-level
protocols’ (McKenzie 1978).
The task does not seem to have presented much difficulty for the committee. During the
first meeting, they produced a provisional model of open-systems architecture (McKenzie
1978). The provisional model, shown in Figure 13, was published in July 1978.
Figure 13. Layers up to network control may be chained (from ISO 1978)
Several authors report the ease with which a unanimous decision was made on the
diagram (e.g., ISO 1978, Zimmermann 1980). The report on the preliminary model indicates
that there was ‘a high degree of commonality between the views expressed by all member
bodies on this subject’ and that ‘The various models which have been proposed all conform
with the principles of layered architecture’ (ISO 1978).
The task was complete in less than 18 months (Zimmerman 1980), but it took a few more
years for its approval in May 1983 (Folts 1983). The results were published in 1984 as ISO
International Standard 7498 and CCITT Recommendation X.200.
Folts concludes that ‘The architectural principles have now been firmly established, with
the definition of the seven layers of functions necessary to create an Open Systems
Interconnection environment’ (Folts 1983). The evidence presented in this section, however,
suggests that most of it had already been worked out before the meeting began.
Reception of the model
The OSI model was taken as an immediate success. Green (1980b) wrote that ‘A particularly
clear way of visualizing all of the layers of a network architecture and their component
protocols has been worked out by the International Standards Organization’. Marsden
acknowledges the value of the model in that ‘it…allows existing standards (e.g. X25) to be
placed into perspective’ (Marsden 1985). Black also seems to have thought the endeavour
worthwhile: ‘The initial 2 1/2 years that SC16 spent developing the Basic Reference Model
has more than paid off in the long run’ (Black 1991).
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19. What the model was expected to be used for
The model was intended to be used as a reference structure for the development of open
standards for computer interconnection (ISO 1978; Zimmerman 1980; Day and
Zimmermann 1983). It may have been thought of this way at the time, but the future did not
bear this out. Although many protocols were developed, few of them were actually were
actually implemented as they were found to be too complicated. According to the Wikipedia,
‘The OSI approach was eventually eclipsed by the Internet’s TCP/IP protocol suite and its
simplified pragmatic approach to networking’ (Wikipedia 13 April 2004).
What the model turned out to be best for
The true success of the model was to clarify a complex system. ‘The most significant
achievement of OSI has been to provide a flexible framework for describing the diverse
transmission media and protocols that combine to form end-to-end services’ (Rose 1990).
Testerman (1999) acknowledges that the OSI model ‘has become the model for
understanding and communicating telecommunications concepts’. He concludes that ‘As a
teaching tool, the OSI Model is unsurpassed’ (Testerman 1999).
◆
Having explained the OSI model, traced its history, and demonstrated its usefulness as an
explanatory framework, I now turn to examining the model in the context of the study of
diagramming.
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20. Taxonomy
Diagram research is replete with taxonomies. In fact, there are so many competing
taxonomies, with no single standard (e.g., Scaife and Rogers 1996; Vekiri 2002), that
Blackwell and Engelhardt (1998; 2002) have proposed a taxonomy of diagram taxonomies
(or meta-taxonomy).
Before I examine the details of Blackwell and Engelhardt’s approach, let me step back and
discuss a problem I encountered with taxonomies from the beginning of my research. That
is, suppose that I find a place for the OSI model in a taxonomy. I can label it and see what
other kinds of diagram relate to it, but then what? What does it do for me? What is a
taxonomy good for?
What taxonomies can do
The purported benefits of taxonomy can be divided into those useful for practice and those
useful for theorizing. Taxonomies are seen as practically useful in that they provide an
inventory of potential solutions to design problems (Macdonald-Ross 1989). When levels of
taxonomic variables are laid out in matrices, they can suggest possibilities for new
diagramming systems (Owen 1986). And they provide a framework for discussing
approaches to the solution of design problems – a potential means of determining whether a
design is appropriate for a given task (Engelhardt 2002; Macdonald-Ross 1989).
In terms of theory, taxonomies structure domains of inquiry (Lohse et al. 1994;
Engelhardt 2002) and can be used to predict future research needs (Lohse et al. 1994). Lohse
et al. (1994) argue that ‘Classification lies at the heart of every scientific field’. In a
developing field such as diagram research (e.g., Macdonald-Ross 1989; Vekiri 2002) such
rigour could certainly have its appeal.
Meta-taxonomies for diagram research
Blackwell and Engelhardt (1998; 2002) have surveyed dozens of taxonomic approaches and
have produced two ‘meta-taxonomies’ that do much to make sense of them. As well, their
work provides an excellent route into the literature. In their 1998 paper, they analysed
taxonomies in terms of six taxonomic dimensions, while in their 2002 paper, which seems to
be a refinement of the earlier one, they used nine taxonomic aspects. Since I find each
approach useful and informative, I will review them both.
Blackwell and Engelhardt (1998)
In attempt to make sense of the taxonomies, Blackwell and Engelhardt (1998) propose six
dimensions: representation, message, relationship between representation and message,
task and process, context and convention, and mental representation. Each of these
dimensions is divided into two categories. Each taxonomy they review can belong to one or
more of these categories depending on which aspects the taxonomy covers.
15

21. Table 1. Taxonomic dimensions of Blackwell and Engelhardt (1998)
Dimension Sub-dimension
Representation the organization of the graphic vocabulary individual marks or
graphic display components
graphic structure the way the components
are related to one another
Message the information that is information domain ontological categories
represented (time, space, quantity)
that constrain variation
information relationships present in
structure the data
Relationship the way information is pictorial from realistic to abstract
between the mapped to the correspondence
representation and representation analogical structural analogy
the message correspondence
Task and process interpreting and modifying information internal perception and
representations processing problem solving
tools interaction with the
external representation
Context and cultural and communicative roles of diagrams in
convention communicative context context discourse
cultural conventions influence of society on
diagrammatic forms
Mental diagrams in the head mental imagery nature of internal
representation representations
interpersonal differences between
variation people that have some
constancy
Figure 14. Graphic depiction of the taxonomic dimensions in
Blackwell and Engelhardt (1998).
They found that most of the taxonomies they reviewed covered the first few dimensions.
They explain this finding this way: ‘These dimensions concern formalisable structure, and
the attributes of diagrams that are most apparent by inspection’ (Blackwell and Engelhardt
1998). The later dimensions ‘concern questions of performance, interpretation, and
cognition…They are less easily formalised’ (Blackwell and Engelhardt 1998).
16

22. To narrow the field to the dimensions I was most interested in, I assigned weightings to
the dimensions. They were as follows.
Table 2. My weightings of Blackwell and Engelhardt’s (1998) dimensions and
sub-dimensions
Weighting Dimension Sub-dimension
Most interested (2 points) Representation graphic structure
Message information domain
Message information structure
Relation analogic correspondence
Less interested (1 point) Representation graphic vocabulary
Relation pictorial correspondence
Context and convention cultural conventions
Neutral (0 points) Context and convention communicative context
Mental representation mental imagery
Mental representation interpersonal variation
Not interested (-1 point) Task and process information processing
Task and process tools
I weighted Task and process negatively because I found that most taxonomies that
covered that dimension were concerned with logic problem solving for artificial intelligence
applications, and I was more interested in the educational benefits of providing learners with
a graphic model of a system.
Adding the weights for each taxonomy gave me a good idea of which taxonomies were
likely to cover issues of relevance to the OSI model. The highest rated, in descending order
were those of: Owen (8 points), Tversky (6 points), and Roth et al. (6 points). The work of
Owen and Tversky in particular feature in this dissertation.
As I did this early in my investigation, I found later that my instincts were wrong, and
that I was more interested Context and convention: cultural conventions and Mental
representation: interpersonal variation than I thought at the time. Later sections will
elaborate on these topics.
Blackwell and Engelhardt (2002)
In their 2002 paper, Blackwell and Engelhardt enhance their meta-taxonomy, breaking it
into nine taxonomic aspects.
17

23. Table 3. Taxonomic aspects of Blackwell and Engelhardt (2002)
First grouping Second grouping Aspect
Representation-related Signs Basic graphic graphic primitive
vocabulary elements
Types of tokens words, shapes, and
pictures
Pictorial abstraction continuum of pictorial
abstraction
Graphic structure Graphic structure principles for arranging
signs
Meaning Mode of correspondence relationship between a
representation and its
meaning
The represented information
information represented by the
diagram
Context-related Context-related Task and interaction what people do with the
aspects diagram
Cognitive processes mental representations,
cognitive implications,
and individual
differences
Social context cultural context and
conventions of the type
of medium
Figure 15. Taxonomic aspects of diagram research
(adapted from Blackwell and Engelhardt 2002).
18

24. A similar weighting analysis yielded Tversky, Doblin, Richards, and Bertin. I ruled out,
perhaps injudiciously, delving into Bertin’s semiology of graphics, as I found it to be too
cumbersome for a dissertation of this length. I do, however, discuss the work of the others
throughout this paper.
A taxonomic analysis of the OSI model
From the most relevant taxonomies I have chosen those of Doblin (1980) and Owen (1986)
to situate the OSI model within. These two taxonomies are related to each other, and one
provides a relatively simple introduction; the other a more elaborate analysis.
Doblin’s taxonomy
Doblin’s (1980) taxonomy is a good place to start because it is relatively easy to explain.
Doblin divides media into presentational and sequential.
A presentational medium, such as a poster, is seen all at once. It gives a total
impression, then the eye tracks over it, picking up details in the order of their
importance…Sequential media – books area an example – are strings of meaning
units in time or space. These are perceived and matched to stored meaning units in
our memories and then accumulated into a total message. (Doblin 1980)
While the mechanisms Doblin explains would surely be seen as simplistic to perceptual
and cognitive researchers such as Winn or Lowe, I find the division useful.
Doblin proposes another dimension, that of static-dynamic. ‘The messages of static media
are tangible, and as permanent as the material used…The messages of dynamic media are
transient, only there in real time as they are being presented’ (Doblin 1980). He proposes a
matrix, which might look like the one in Table 4.
Table 4. Matrixed media (adapted from Doblin 1980)
presentational sequential
static presentational static sequential
static
drawing, photography writing, printing
dynamic presentational dynamic sequential
dynamic
movies, television speech, telephony
It is clear that the OSI model fits into the static presentational category of Doblin’s
model. In the spirit of exploring the taxonomy, we can imagine what an alternative
presentation might do. For instance, a dynamic presentational version of the OSI model
might be an animated clip of the sequence of communications between two computers, while
a static sequential version could show the sequence one step at a time – say, one step per
diagram, on pages in a book.
Owen’s taxonomy
Owen (1986) organizes graphics three ways: by purpose, by structure, and by operation. His
taxonomy by purpose would likely find its place in the latter half of Blackwell and
Engelhardt’s meta-taxonomy, while his structural taxonomy would come up near the middle.
19

25. Because his operational taxonomy deals with interaction – the way people change diagrams
while working with them – I find it less relevant for examining the OSI model and am
excluding it.
By purpose Owen plots graphic forms in a two-dimensional space with one axis as the
purpose of supplying information and the other as the purpose of creating an impression. He
further divides this field into four regions: identification, stimulation, enlightenment, and
persuasion.
Table 5. Owen’s (1986) graphic communication purposes
Purpose Used when Examples
identification impression need not be strong and information pictograms and symbols
only denotational
stimulation impression is strong and information relatively swastika, skull-and-crossbones
unimportant
enlightenment need for information greatly exceeds that for charts and graphs
impression
persuasion both impression and information are maximized political cartoons, business
presentations
Figure 16. Graphic systems ‘mapped’ according to their purpose to create impression or
deliver information (adapted from Owen 1986)
The OSI model would likely fall in the area occupied by organization charts when used by
programmers and engineers, but could move up into persuasion when the goal is, for
example, to sell a customer a network system.
20

26. By structure Owen, echoing Doblin, begins by defining a continuum between sequential
and presentational graphic systems and notes that ‘it is almost possible’ to show a decrease
in grammatical structure as we proceed through the continuum.
Figure 17. Graphic systems ordered according to the way they are transmitted and received
(adapted from Owen 1986)
In addition, Owen presents what he calls a ‘kit of parts’ for graphic systems. It consists of
contexts, entities, attributes, and operators.
Table 6. Owen’s (1986) ‘kit of parts’ for graphic systems.
Part Definition Options
contexts used implicitly, may be space, time, or domain (the abstract field of the
combined subjects of the diagram)
entities visual elements symbolic, analogic, or iconic
attributes qualities taken on by entities discrete, rank order, or continuous
operators relations among entities organizational, procedural, or spatial
It is helpful to visualize the interaction of entities, attributes, and operators.
Figure 18. Entities have attributes; between entities there may be relations
(adapted from Owen 1986)
Interestingly, he presents each part as a triangle and indicates where various systems fit
in. I feel that system diagram in Figure 19 corresponds most closely to the OSI model so to
draw attention to it I have shaded its circle.
21

27. Figure 19. Owen’s ‘kit of parts’, showing where the system diagram fits in on each (adapted
from Owen 1986 – note: several diagramming systems have been left off each triangle)
It is clear that the OSI model’s context is domain – in this case, the domain of inter-
computer communication, which is not inherently spatial. Neither does the OSI model make
any effort to depict time. The OSI model’s entities are analogic – rectangles are analogous to
software components. They are not icons or symbols of the software components. The OSI
model’s attributes are discrete (nominal). What distinguishes each rectangle from the others
is a text label. There is a flavour of ordinality in the way the rectangles are stacked, and they
are usually numbered, but they could as easily have been numbered from top to bottom as
from bottom to top. There is no concept of continuousness in the model. Finally, the vertical
relations between the rectangles in the OSI model are organizational, based on the layering
concept. The horizontal relations are vaguely spatial, however, in that each stack of
rectangles represents a separate computer and vaguely procedural (for someone who knows
the subject matter) in that communications travel ‘down’ from one computer, ‘over’, and ‘up’
to the other, tracing a ‘U’-shaped path.
22

28. Psychology
In an attempt to make sense of the myriad angles from which psychological aspects of
diagrams have been studied, I have devised a model to structure this discussion. It is
inspired by the work of Blackwell and Engelhardt (1998; 2002), but differs in that it includes
the role of the diagram’s designer (or transformer) and that its purpose is to contextualize
the psychological literature I found relevant to this dissertation rather than to analyse
diagram taxonomies.
This model has four primary components: the diagram itself (representation), the real
system the diagram represents, the viewer of the diagram, and the transformer. Both the
viewer and the transformer approach the diagram with some goal or intent, and both rely on
their perceptual/cognitive systems and background knowledge in arriving at a conception of
the real system. The viewer, however, presumably does not have the same access to the real
system and experts in its structure and function as does the transformer.
Figure 20. A model for contextualizing the psychological literature relevant to diagramming
One of the motivations for the devising of this model was to accommodate the stance of
Sless (1981), Ittelson (1996), and Richards (2000): that the relation between the viewer and
the representation is distinct from the relation between the transformer and the
representation. The representation might then be seen as the mid-point of a communication
process – the end-point for the transformer and the starting-point for the viewer. In
Ittelson’s (1996) words, ‘the creator of the marking starts with a set of intentions and
produces a marking: the perceiver starts with the marking and tries to reconstruct the
intentions’.
Another was MacEachren (1995), who, in arguing for more focus on the role of the viewer
in the field of cartography, actually drew my attention to the right side of the model. In
cartography, graphic depictions of the communication process ‘share a basic structure with
an information source tapped by a cartographer who determines what (and how) to depict, a
map as the midpoint of the process, and a map user who “reads” the map and develops some
understanding of it by relating the map information to prior knowledge’ (MacEachren 1995).
I found it fascinating that cartographic models explicitly included the transformer and
23

29. transformation process and needed to be encouraged to put more emphasis on the viewer,
which is quite the opposite of most work in psychology.
◆
Let’s start with the viewer’s side of the model, which involves the viewer trying to make sense
of the representation. The viewer draws on perceptual and cognitive processing resources,
including their background knowledge, visuo-spatial abilities, and knowledge of visual
conventions in constructing a mental conception of the real system depicted in the diagram.
In thinking about the viewer’s task, it pays to consider the words of Ittelson: ‘The marking
stands as a single, limited, and completely defined source of visual information. There is no
opportunity for further exploration, although more detailed examination is usually possible,
and obtaining information from other sources can be an important part of the process’
(Ittelson 1996).
Perceptual processing
Much is made of the strength of the match between the properties of diagrams and the
processing capabilities of the human visual perception system (Sless 1981; Lowe 1994; Scaife
and Rogers 1996; Tversky et al. 2000). Scaife and Rogers (1996) mention object perception,
search, and pattern-matching as capabilities, while Lowe (1994) cites shape, orientation, and
spacing as generally applicable visuo-spatial relationships that are invoked when we look at
graphic displays.
Sless (1981), discussing diagrams similar to the OSI model, acknowledges the key role of
spatial configuration and the general tendency of the Gestalt laws to organize information in
space. The Gestalt laws, established in 1912 by Westheimer, Koffka, and Kohler, describe the
way we see patterns in visual displays (Ware 2000). The Gestalt laws reviewed in Ware
(2000) are summarized in Table 6.
Table 7. Gestalt laws as reviewed in Ware (2000)
Gestalt law Definition
proximity objects that are close together tend to be perceived as grouped together
similarity similar objects tend to be perceived as grouped together
continuity we are more likely to construct visual entities out of visual elements that are
smooth and continuous, rather than ones contain abrupt changes in direction
symmetry symmetrically arranged pairs of lines are perceived much more strongly as
forming a visual whole than a pair of parallel lines, and bilateral symmetry
produces an even stronger holistic figure
relative size smaller components of a pattern tend to be seen as objects
figure and ground a figure is something object-like that is perceived as being in the foreground,
while the ground is whatever lies behind the figure
According to Winn, this perceptual structuring is immediate. ‘Perceptual structure is
determined by the grouping of symbols by their appearance [which he calls discrimination]
and by their placement and interconnection [which he calls configuration]. Note that
discrimination and configuration occur without any knowledge of what the symbols in the
diagram mean, nor of why they are placed and connected in the way they are’ (Winn 1993).
24

30. Visual syntax
Richards (2002) holds that the viewer’s first task when approaching a diagram is to ‘work out
the visual syntax.’ Ware (2000) describes a visual syntax for what he calls node-link
diagrams. ‘The essential characteristic of [node-link] diagrams is that they consist of nodes,
representing various kinds of entities, and links, representing the relationships between the
entities’. He argues that node-link diagrams have a ‘visual grammar’ in that ‘The nodes are
almost always outline boxes or circles, usually representing the entities in the system’ and
‘The connecting lines generally represent different kinds of relationships, transitions, or
communication paths between the nodes’ (Ware 2000).
Table 8. The visual grammar of node-link diagram elements (after Ware 2000)
Graphical code Visual instantiation Semantics
closed contour an entity of some kind… It can be a part of a body
of software, or a person in an organization
shape of enclosed entity type (an attribute)
region
colour of enclosed entity type (an attribute)
region
size of enclosed magnitude of an entity (a scalar attribute)
region
partitioning lines can delineate subparts of an entity… may
within closed correspond to a real-world multipart object
region
attached shapes closed-contour regions may be aggregated by
overlapping them. The result is readily seen as a
composite entity
shapes enclosed by can represent conceptual containment
contour
spatially ordered can represent conceptual ordering of some kind
shapes
linking line represents some kind of relationship between
entities
linking-line quality effectively represents an attribute or type or
relationship
linking-line can be used to represent the magnitude of the
thickness relationship (a scalar attribute)
tab connector a contour can be shaped with tabs and sockets
that can indicate which components have
particular relationships
proximity proximity of components can represent groups
In the light of Ware’s grammar, the OSI model seems semantically impoverished,
consisting as it does mostly of boxes. Apparently this is not unusual: ‘While generic node-link
diagrams are very effective in conveying patterns of structural relationships among entities,
they are often poor at showing the types of entities and the types of relationships’ (Ware
2000). His visual grammar suggests ‘ways of extending this vocabulary that are perceptually
sound’ (Ware 2000).
25

31. Indeed others have (unwittingly, I would guess) put these principles to work in making
their own renditions of the model. For instance, Figure 21 uses changes in size of enclosed
region to distinguish the layers. This is a scalar attribute, and hence may not be appropriate
for this use, but it does serve to indicate that there are differences between layers. Figure 22
uses changes in colour of enclosed region, which is probably more appropriate.
Figure 21. Diagram showing changes in size of enclosed region (from Zacker et al. 1996)
Figure 22. Diagram showing changes in colour of enclosed region
(from Bitzenbytes.com 28 Aug 2003).
The work of Tversky and her colleagues aligns with Ware’s. Tversky is a proponent of the
‘cognitive naturalness’ of certain graphic elements and their arrangement in space (e.g.,
Tversky 2001; 2002). Tversky et al. (2000) hold that certain elements are apt to ‘readily
[convey] meaning’, and they call these elements ‘meaningful graphic forms’. She argues that
‘The choice of visual devices for discrete, categorical concepts and for ordinal or continuous
ones appears to be derived from physical devices that contain or connect’ (Tversky 2001).
For example, ‘Signs used for enclosure resemble physical structures that enclose actual
things, such as bowls or fences’ (Tversky 2001).
The meaningful graphic forms of relevance to the OSI model are closed figures, lines, and
arrows. While there is no line in the ‘official’ OSI model depicted in Figure 2, the line that
appears at the bottom of Figure 1, connecting the two columns, often appears in OSI-inspired
diagrams. Closed figures, such as boxes, ‘suggest two- or three-dimensional objects whose
26

32. actual shapes are irrelevant, thus schematized’ (Tversky et al 2000). Lines depict
connections among objects as well as order (Tversky 2002). ‘Arrows are a special kind of
line, with one end marked, inducing an asymmetry’ and ‘Arrows are frequently used to signal
directions in space. In diagrams, arrows are also commonly used to indicate direction in
time’ (Tversky 2001).
Spatial arrangement also communicates. Tversky holds proximity to be ‘the most basic
metaphor’, and offers that ‘In perception, things that are near by in space tend to be grouped
and separated from things that are distant. To use this for conveying abstract meanings
simply requires placing things that are related in close proximity and placing things that are
not related farther away in space’ (Tversky 2001).
Table 9. Meaningful graphic forms and arrangements relevant to the OSI model
(summarized from Tversky et. al. 2000, Tversky 2001, and Tversky 2002)
Meaningful graphic forms Meanings conveyed
lines connection
ordinality
arrows temporal sequence, direction in time
causality, direction in causality
direction in space
direction in motion
direction of power
direction of control
closed figures objects (whose actual shapes are irrelevant)
Spatial arrangement of graphic forms Meanings conveyed
inside closed figures belonging together
equivalence
clustered proximity in an abstract dimension, such as time or value
belonging together
the sharing of a common feature or features
equivalence
degree of relationship
separated differing values on the same underlying feature
The closed figures in the OSI model (see Figure 2) are all rectangular. It is true that their
shapes are irrelevant, since the layers of protocol do not have any inherent shape. Their
rectangularity, however, reflects the layered concept. Ellipses, for example (see Figure 5), do
not work as well in conveying the concept of a ‘layered stack’ since round objects cannot be
stacked in real life. The rectangles in each stack form a cluster, indicating that they ‘belong
together’, which is appropriate as each stack represents the software running on one
computer. The two stacks are separated, indicating that they are different, and in fact they do
represent the software running on two different computers.
The use of arrows in Figure 2 is curious, however. The arrows that run up the left side of
the diagram are simply callouts that link the labels to the rectangles. The labels could just as
well have been put inside the rectangles. The arrows that run horizontally between each pair
of layers intend to indicate their equivalence and are actually misleading, since the
communication flow does not go from side-to-side at each layer but ‘down, over, and up’
from the top, as shown in Figure 23.
27

33. Figure 23. A more accurate use of arrows in the OSI model (from Montes 2001)
Cognitive processing
Kim et al. (2000) outline the distinction between perceptual and conceptual (cognitive)
processing:
The perceptual process is a bottom-up activity of sensing something and knowing its
meaning and value (Bolles 1991), while the conceptual process is a top-down activity
of generating and refining hypotheses (Simon and Lea 1974). In other words, we
search and recognize relevant information through perceptual processes and reason
by inferring and deriving new information through conceptual processes….To fully
exploit the potential of a diagram, it must be effectively utilized in both the
perceptual and conceptual processes. (Kim et al. 2000)
Others agree that interpreting diagrams requires more than just perceptual processing
(e.g., Lowe 1994; Ittelson 1996; Tversky 2001). Tversky makes the fundamental point that
‘interpreting a graphic depends on understanding that it can represent something other than
itself’ (Tversky 2001). Ittelson argues: ‘Markings do not exist in the real world; they exist as
human expressive and communicative artifacts. The perception of markings must necessarily
be about that expressive and communicative content’ (Ittelson 1996). Lowe offers that for
‘learning tasks – such as committing the diagram to memory, understanding its meaning or
using it as an aid to problem solving – the data it provides explicitly (typically simple lines
and shapes) need to be interpreted not simply as a visuo-spatial array, but in terms of the
subject matter it depicts’ (Lowe 1994). Doing this requires background knowledge (Lowe
1993; Winn 1993; Lowe 1994).
28

34. Background knowledge
Lack of sufficient background knowledge of the system represented by a diagram has been
found to reduce the ability to construct meaning from the diagram (Lowe 1994), recall
unfamiliar material learned in the diagram (Winn 1993), and find information in the
diagram (Winn 1993).
Winn, examining how viewers search for information in diagrams, explains that viewers
first take in the elements of a diagram that ‘enjoy perceptual precedence’ (Winn 1993).
Where they look next, however, is ‘likely depend[ent] on their familiarity with the symbol
system of diagrams and on their knowledge of the material the diagram describes’ (Winn
1993). Winn writes that ‘important aspects of search in diagrams are…directed perceptually
and do not rely on subject matter for their successful execution. Other aspects of search in
diagrams are, of course, influenced by knowledge of content’ (Winn 1993).
Lowe (1993) distinguishes between two types of background knowledge: domain-general
and domain-specific. Domain-general knowledge gives the ability to ‘deal with a diagram’s
component markings on a visuo-spatial level’ (Lowe 1993). Domain-specific knowledge
‘enables the viewer to go beyond the visuo-spatial level in order to represent mentally the
meaning of the system depicted in the diagram’ (Lowe 1993). This is important because ‘A
visuo-spatial approach to a diagram…would be of little value in developing an understanding
of the depicted subject matter’ (Lowe 1994).
In Lowe’s view, background knowledge plays a key role in the development of a mental
representation of a system: ‘The nature of the mental representation constructed from a
display…can be characterized as a function of the interaction between the information
provided in the display and the person’s background knowledge’ (Lowe 1993).
Mental representations
Lowe ‘assume[s] that the successful processing of a visual display (such as a diagram)
involves the construction in working memory of an appropriate mental representation from
the display’ (Lowe 1994). The nature of the viewer’s mental representations (or ‘mental
models’ or ‘knowledge schemata’) are held by many to be structural (Glenberg and Langston
1992; Lowe 1993; Winn 1993). The structure of the mental representation must match the
structure of the real system in order to facilitate learning (Lowe 1993).
When diagrams match the structure of the real system, they can help the viewer to build
an accurate mental representation of the real system (Glenberg and Langston 1992).
According to Lowe (1993), diagrams that fail to ‘capture properly the aspects of the subject
matter which have a central semantic significance’ (Lowe 1993) may cause the viewer to
develop an inaccurate mental model that does not facilitate learning.
This line of reasoning is not without its detractors. Scaife and Rogers (1996) are opposed
to statements such as ‘Graphic forms encourage students to create mental images that, in
turn, make it easier for them to learn certain types of material (Winn 1987)’ because such
statements do not specify a mechanism and ‘seem to rest on intuition’ (Scaife and Rogers
1996). They conclude that ‘the case for an intimate relationship between graphical
representation and images may not be logically compelling and is currently heavily under-
specified’ (Scaife and Rogers 1996). Scaife and Rogers (1996) would prefer a focus on the
kinds of internal representations people form when interacting with external
representations.
29

35. Visuo-spatial ability
Vekiri (2002), citing Carrell, defines visuo-spatial ability as ‘the ability to mentally generate
and transform images of objects and to reason using these imagery transformations’. It
seems natural that this ability would play some part in the interpretation of diagrams. Winn
and Holliday (1982) report that ‘The correct interpretation of diagrams requires various
mental skills’ and that ‘students need to have attained a certain level of “diagram literacy” in
order to extract information from them’. Twenty years later, Vekiri concurs: ‘It appears that
diagrams may be more demanding to process, and thus less beneficial, when students do not
have high visuo-spatial ability’ (Vekiri 2002). She suggests design strategies to help viewers
with low visuo-spatial ability to process information in diagrams; these will be reviewed in a
later section.
Metaphor
Interpreting metaphor in diagrams involves both perceptual and conceptual processing (e.g.,
Richards 2000; Tversky 2001). Lakoff and Johnson (1980) examine metaphor in language
with the goal of understanding the human conceptual system. What Lakoff and Johnson
(1980) call ‘orientational’ or ‘spatialization’ metaphors are the ones most relevant to
analysing the OSI model. They argue that ‘orientational metaphors…arise from the fact that
we have bodies of the sort we have and that they function as they do in our physical
environment…Such metaphorical orientations are not arbitrary. They have a basis in both
our physical and cultural experience’ (Lakoff and Johnson 1980).
The orientational metaphors I found most worthy of examination are presented in
Table 10.
Table 10. Orientational metaphors relevant to analysis of the OSI model (from Lakoff and
Johnson 1980)
Direction Metaphor Language examples Physical/cultural basis
up consciousness ‘Get up. Wake up. He’s We sleep lying down and
down unconsciousness under hypnosis. He sank stand up when we awaken
into a coma’.
up having control or force ‘I am on top of the situation. Physical size typically
down being subject to control I have control over her. His correlates with physical
or force power is on the decline. He is strength, and the victor in
low man on the totem pole’. a fight is typically on top
up more ‘My income rose last year. If you add more of a
down less The number of errors he substance to a container or
made is incredibly low. If pile, the level goes up
you’re hot, turn the heat
down’.
up rational ‘The discussion fell to the In our culture people view
down emotional emotional level, but I raised themselves as being in
it back up to the rational control over animals,
plane. He couldn’t rise above plants, and their physical
his emotions’. environment, and it is
their unique ability to
reason that places humans
above other animals and
gives them control
30

36. The orientational metaphors Lakoff and Johnson discuss all involve verticality. In
addition to vertical metaphor, Tversky (2001; 2002) researches horizontal metaphor and
finds it to be neutral (Tversky 2001). Her explanation is based on the bilateral symmetry of
the human body and the arbitrariness of the horizontal arrangement of objects in the real
world (Tversky 2002). This is not the case for the vertical dimension: ‘What’s up defies
gravity, exhibits strength. People grow stronger as they grow taller. Larger piles, of goods or
money, are higher’ (Tversky 2002). While ‘The vertical axis of the world has a natural
asymmetry, the ground and the sky,…the horizontal axis of the world does not’ (Tversky
2001). De Sauzmarez, quoted in Sless (1981) as evidence of some designers’ over-concern
with the ‘internal dynamics’ of pictures, in this context helps to flesh out the concepts:
Horizontals and verticals operating together introduce the principle of balanced
oppositions of tensions. The vertical expresses a force which is of primary
significance – gravitational pull, the horizontal again contributes a primary
sensation – a supporting flatness; the two together produce a deeply satisfying
resolved feeling, perhaps because they symbolise the human experience of absolute
balance, standing erect on level ground. (de Sauzmarez 1964)
What kinds of metaphor are used in the OSI model? Vertical metaphor is primary. As one
examines a stack from bottom to top, the degree of abstraction increases and the tangibility
correspondingly decreases. At the lowest level, electromagnetic waveforms traverse a
medium. These are physical phenomena that, while not perceptible to humans, are ‘real’ and
can be detected using instruments (such as an oscilloscope) even without any concept of
what they mean. Just to go one step further and convert the waveforms to ones and zeroes
(binary digits) involves an abstraction that requires the computer to understand the ‘code’.
The best metaphor for up relative to the OSI model is probably consciousness. At the lowest
possible level, there is no meaning ascribed to the signal that arrives. After the networking
software running on the computer performs a series of transformations on the signal, it
presents an intelligible communication to an application (such as a web browser) that sits
above the highest layer.
It is interesting to trace the development of this verbal metaphor in parallel with the
development of visual depictions of the layered concept that formed the basis of the OSI
model. Carr et al. (1970) use the phrase ‘to send data over a link’, which implies a separation
between the physical connection below and the data that rides on top. But they use a
different sort of metaphor in the same paper: ‘The network is seen as a set of data entry and
exit points into which individual computers insert messages destined for another (or the
same) computer, and from which messages emerge’ (Carr et al. 1970). To me this recalls
perhaps a pneumatic tube system.
The paper that introduces what seems to be the earliest precursor to the OSI model (see
Figure 5), Crocker et al. (1972), is replete with metaphoric language: ‘operating just above
the communications subnet’; ‘when we have two computers facing each other across some
communications link’; ‘we speak of high or low level protocols’. Perhaps not surprisingly, the
paper that I use to illustrate that the layered concept took some time to take hold (Mills 1972)
contains no terms that suggest spatialization.
31

37. A highly appealing visual metaphor is sometimes applied to the network communication
process: the postal metaphor. If the ‘intelligible communication’ between two computers
were to be thought of as a letter, downward traversal through the stack would be akin to
putting the letter in one after another addressed envelopes and sent to the other computer,
which opens each one in turn until the letter can be read. Figure 24 shows a good example of
this metaphor.
Figure 24. Illustration of the postal metaphor (from Motorola Codex 1992)
◆
Now to the right (transformer’s) side of the model in Figure 20. The transformer sets about
to explain the real system diagrammatically, drawing on his or her own conception of the real
system, which is informed by access to expert knowledge and applied using visual
conventions and, it is hoped, some idea of the task the viewer is to accomplish.
The transformer and transformation
Macdonald-Ross and Waller (2000) define the transformer as ‘the skilled professional
communicator who mediates between the expert and the reader’. They acknowledge that
Otto Neurath coined the term previously.
32

38. ‘The transformer’s job is to put the message in a form the reader can understand’
(Macdonald-Ross and Waller 2000). The transformer does this by divining the ‘central
themes or organising principles’ that unify the ‘facts, arguments, theories, problems, and
procedures’ that ‘all subjects consist of’ (Macdonald-Ross and Waller 2000). Ittelson
emphasizes the role of creativity in the transformation process:
[The form] is the product of a continuous series of choices based on social practices,
individual experiences, and aesthetic judgments (Willats 1990).…Many of the
decisions along the way are ‘rational’. They are in principle ‘computable’ on the basis
of some hypothetical algorithm. But some, perhaps most, are not. They are based on
a feeling on the part of the creator of the marking that, of all possible paths, this one
is the ‘right’ way to go. (Ittelson 1996)
While the creative aspect of transformation is vital, the chances of achieving a successful
transformation can be greatly improved if the transformer is familiar with characteristics of
the viewers and the task or tasks they will be expected to perform, design guidelines for the
type of artefact and medium used, and, of course, the real system itself.
Even when armed with this knowledge, success is not guaranteed. As Ittelson reminds us,
‘We can construct a form, but we can never fully determine how that form will be perceived.
Each perceiver can, and indeed must, perceive it idiosyncratically to a greater or lesser
extent’ (Ittelson 1996). But despite these difficulties, it is possible to increase the chance of
success.
33

39. Achieving successful transformation
Macdonald-Ross and Waller stress that ‘a good communication is selected for a purpose and
has a sound logical structure’ (Macdonald-Ross and Waller 2000). This section discusses
these and other related goals and how they might be achieved when transforming abstract
technical material.
Addressing the viewer’s needs
As Kim et al. caution, ‘Simply providing a diagram does not guarantee good performance’
(Kim et al. 2000). The transformer must know something of the viewers’ background
knowledge, visuo-spatial abilities, and the tasks they are to perform using the diagram.
The viewers’ tasks
Concern for the viewers’ tasks is emphasized by Macdonald-Ross (1977; 1989) and Vekiri
(2002) in particular. Vekiri puts it bluntly: ‘Displays need to address the goal of the task –
displays must meet the demands of the learning tasks in order to be effective (Vekiri 2002).
Macdonald-Ross stresses that ‘To choose the best format for a particular occasion one must
decide: what kind of data is to be shown? What teaching point needs to be made? What will
the learner do with the data?… (Macdonald-Ross, 1977). He further draws a distinction
between the tasks of operation and conceptualization:
A reader interested in operational data will be taking off precise numerical or
structural information for some practical purpose. Here the graphic is used for
reference in the most literal manner. On the other hand, a reader interested in
conceptual relationships will be looking at trends and general structure with a view
to understanding the argument presented in the text. In general, a graphic device
which is optimal for one of these purposes will not be optimal for the other.
(Macdonald-Ross 1989)
Analysing the viewers’ tasks can lead the transformer to useful design solutions, but it is
not a formulaic technique that guarantees a satisfactory outcome: ‘It pays to remember that
graphic communication is an art, that is, a skill which results from knowledge and practice’
(Macdonald-Ross 1977).
The viewers’ visuo-spatial abilities
Vekiri notes that ‘diagrams may be more demanding to process, and thus less beneficial,
when students do not have high visuospatial ability’ (Vekiri 2002). Winn and Holliday
caution that ‘diagrams are not the best way for all students to learn. The correct
interpretation of diagrams requires various mental skills that designers should not take for
granted’ (Winn and Holliday 1982). They recommend not using ‘complex and redundant
diagrams and charts with low-ability students’ (Winn and Holliday 1982). As far as Vekiri
(2002) is concerned, how to design suitable materials for viewers with low visuo-spatial
ability is an open question.
34

40. The viewers’ background knowledge
Interpreting abstract technical diagrams is a cognitively demanding task (e.g., Lowe 1994;
Vekiri 2002). Without sufficient background knowledge about the real system, viewers are
likely to interpret a diagram in terms of its visuo-spatial properties (e.g., Lowe 1994;
Richards 2000).
To counter this Lowe suggests that ‘instructional interventions aimed at improving
students’ capabilities to deal with a particular diagram should address the development of
relevant contextual knowledge in a manner that emphasises high-level domain-specific
relation’ (Lowe 1994). Tversky (2001) and Vekiri (2002), however, argue for beginning with
concrete examples. Tversky offers that ‘research in cognition on basic level concepts and on
reasoning suggests that an effective entry into a complex system might be a thorough
understanding of a concrete example. Once an exemplary example has been mastered,
abstraction to generalities and inspection of details are anchored and supported (Tversky
2001).
Structuring the diagram appropriately
An appropriately structured diagram exhibits high fidelity with regard to the real system and
adheres to perceptual and conceptual conventions.
Relation between the representation and the real system
Another way of titling this section might be ‘relation between content and graphic’, which
Macdonald-Ross calls ‘one of the most profound and important questions in graphic
communication’. (Macdonald-Ross 1989). Winn and Holliday agree: ‘the first thing the
designer must be conscious of is the accuracy with which the diagram or charts captures [the
logical relationships among concepts]’ (Winn and Holliday 1982).
In these sorts of diagrams ‘neither the parts of the display nor their location correspond
to the parts and the locations of referents’ (Vekiri 2002), but Macdonald-Ross reassures us
that ‘The mapping between a class of graphic devices and a problem domain is rarely one-to-
one. A class of graphic devices can be used to represent any content that has the underlying
conceptual structure denoted by the graphic’ (Macdonald-Ross 1989). And Tversky issues a
reminder: ‘Diagrams…are not meant to reflect physical reality completely and veridically.
Rather they are meant to be schematized renditions of actual or abstract systems.…As such,
they are not meant to reflect conceptual reality. They portray an analysis of the parts of the
system and their interrelationships, structural, causal, or power’ (Tversky 2002).
The representation should be ‘selective’ (Lowe 1994) and ‘constrained’ (Scaife and Rogers
1996). ‘The issue…becomes one of determining which aspects of the represented world need
to be included and how they should be represented, what aspects should be omitted and
what additional information needs to be represented that is not visible in the real world but
would facilitate learning’ (Scaife and Rogers 1996).
The distances among concept labels should correspond to their positions in the real
system (when possible) and reflect the ‘semantic distance’ between concepts (Winn and
Holliday 1982). Sequences of concepts should match those in the real system, and should be
presented ‘so that they run left-to-right or top-to-bottom on the page’ (Winn and Holliday
1982). For teaching concept identification, Winn and Holliday found that ‘including small
drawings within diagrams can facilitate students’ understanding of commonly taught
35

41. concepts and principles’ (Winn and Holliday 1982). An example of how this can work is
shown in Figure 25.
Figure 25. How the inclusion of small drawings can be used to facilitate understanding
(from Freedman 1996)
Accompanying text
With abstract technical diagrams, there is often a need for accompanying text (e.g. Arnheim
1969; Scaife and Rogers 1996; Richards 2000). Vekiri argues that ‘[explanations that
accompany displays] work better when they cue learners to the important graphic elements
and details necessary to extract the message(s) that graphics communicate’ (Vekiri 2002).
The textual explanation should be presented near the diagram in space and time (Vekiri
2002).
Adherence to perceptual conventions
Generally, diagrams should follow the visual syntax of Tversky et al. (2000), Ware (2000),
and Tversky (2001; 2002) that is presented in the Perceptual processing section of this
dissertation. Ware argues that ‘it is important that a good diagram take advantage of basic
perceptual mechanisms evolved to perceive structure in the environment’ (Ware 2000). He
suggests that ‘there are ways of extending [the vocabulary of generic node-link diagrams]
36

42. that are perceptually sound…There is a range of possibilities between the rectangular box
and line diagram and fully rendered, colored, and textured 3D objects’ (Ware 2000).
Drawing inspiration from exemplars
Macdonald-Ross (1989) stresses the importance of examining the work of ‘master
performers’ to ‘stimulate and inform the creative design activities of the transformer’
Macdonald-Ross (1989). Even Scaife and Rogers, who call into question the idea that we can
assess adequately ‘the value of different graphical representations…from our intuitions’
(Scaife and Rogers 1996) believe that ‘we should recognize the importance of the canonical
forms of diagrams’ (Scaife and Rogers 1996).
I couldn’t agree more.
◆
37

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