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Perceptual and Interpretative Properties of Motion for Information Visualization.

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Visualizing information in user interfaces to complex, large-scale systems is difficult due to an enormous amount of dynamic data distributed across multiple displays. While graphical represen- tation techniques can reduce some of the cognitive overhead associated with comprehension, cur- rent interfaces suffer from the over-use of such representation techniques and exceed the human's perceptual capacity to efficiently interpret them. New display dimensions are required to support the user in information visualization. Three major issues which are problematic in complex sys- tem UI design are identified: representing the nature of change, supporting the cognitive integra- tion of data across disparate displays, and conveying the nature of relationships between data and/ or events. Advances in technology have made animation a viable alternative to static representations. Motion holds promise as a perceptually rich and efficient display dimension but little is known about its attributes for information display. This paper proposes that motion may prove useful in visualizing complex information because of its preattentive and interpretative perceptual proper- ties. A review of animation in current user interface and visualization design and research indi- cates that, while there is strong intuition about the "usefulness" of motion to communicate, there are few guidelines or empirical knowledge about how to employ it. This paper summarizes types of movement characterization from diverse disciplines and proposes an initial taxonomy of motion properties and application to serve as a framework for further empirical investigation into motion as a useful display dimension. Implementation issues are discussed with respect to real- time display requirements.
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Perceptual and Interpretative Properties of Motion for
Information Visualization
Lyn Bartram
School of Computing Science
SImon Fraser University
Technical Report CMPT-TR:1997-15
Visualizing information in user interfaces to complex, large-scale systems is difficult due to an
enormous amount of dynamic data distributed across multiple displays. While graphical represen-
tation techniques can reduce some of the cognitive overhead associated with comprehension, cur-
rent interfaces suffer from the over-use of such representation techniques and exceed the human’s
perceptual capacity to efficiently interpret them. New display dimensions are required to support
the user in information visualization. Three major issues which are problematic in complex sys-
tem UI design are identified: representing the nature of change, supporting the cognitive integra-
tion of data across disparate displays, and conveying the nature of relationships between data and/
or events.
Advances in technology have made animation a viable alternative to static representations.
Motion holds promise as a perceptually rich and efficient display dimension but little is known
about its attributes for information display. This paper proposes that motion may prove useful in
visualizing complex information because of its preattentive and interpretative perceptual proper-
ties. A review of animation in current user interface and visualization design and research indi-
cates that, while there is strong intuition about the “usefulness” of motion to communicate, there
are few guidelines or empirical knowledge about how to employ it. This paper summarizes types
of movement characterization from diverse disciplines and proposes an initial taxonomy of
motion properties and application to serve as a framework for further empirical investigation into
motion as a useful display dimension. Implementation issues are discussed with respect to real-
time display requirements.
Perceptual and Interpretative Properties of Motion for Information Visualization
2
Table of Contents
1Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.1 Organization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.2 Terminology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
2The User Interface Bandwidth Problem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
2.1 More Data, More Displays... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
2.2 ...Insufficient Information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
2.2.1 System Behaviour and Change . . . . . . . . . . . . . . . . . . . . . . . 7
2.2.2 Integration of data across displays . . . . . . . . . . . . . . . . . . . . . 8
2.2.3 Data relationships . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
3Issues in Display Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
3.1 Perceptual Principles for Visualization . . . . . . . . . . . . . . . . . . . . . . . . . 9
3.1.1 The Proximity Compatibility Principle . . . . . . . . . . . . . . . . . 9
3.1.2 Emergent Features . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
3.1.3 Directed Attention . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
3.2 An Ecological Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
3.3 Design Challenge . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
4Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
4.1 Low-level perceptual efficiency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
4.2 Interpretative scope . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
4.3 Availability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
5 Movement As Representation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
5.1 Animation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
5.1.1 Animation At the Interface . . . . . . . . . . . . . . . . . . . . . . . . . . 14
5.1.2 Animation as Illustration . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
5.1.3 Animation as Visualization . . . . . . . . . . . . . . . . . . . . . . . . . . 17
5.2 Motion as Meaning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
5.2.1 Basic Motion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
5.2.2 Interpretative Motion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
5.2.3 Compound Motion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
6Motion as a Display Dimension . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
6.1 Research Issues and Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
6.1.1 Basic Motion and Kinetic Primitives . . . . . . . . . . . . . . . . . . . 24
6.1.2 Interpretative Motion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
6.1.3 Compound Motion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
6.1.4 Properties and Types . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
Perceptual and Interpretative Properties of Motion for Information Visualization
3
7Potential Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
7.1 Annunciation and signalling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
7.2 Grouping and integration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
7.3 Communicating data relationships . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
7.4 Data display and coding. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
7.5 Representing change. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
7.6 General visibility concerns . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
8Implementation Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
8.1 Perceptual Artifacts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
8.2 Real-Time Display Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
9 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
10 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
Perceptual and Interpretative Properties of Motion for Information Visualization
4
1 Introduction
Complex systems such as those used in supervisory control and data acquisition (henceforth
SCADA) can be characterized by large volumes of dynamic information which cannot reasonably
fit into single displays or even a single computer screen. In such systems the interface must not
only represent the data in reasonable ways but should also signal the user effectively when impor-
tant changes take place and, increasingly important in environments with multiple screens or win-
dows, should provide clear indications when data are associated or related in some way. When
appropriately used, graphical representations such as shape, symbols, size, colour and position are
very effective in information visualization because they are mentally economical [Woo95b] - rap-
idly and efficiently processed by the preattentive visual system rather than cognitive effort. How-
ever, when human perceptual capacity to assimilate all the combinations of codes and dimensions
is exceeded interface comprehension increasingly demands cognitive activity and mental econ-
omy is lost.
Current SCADA interfaces rely heavily on static graphical dimensions for low-level data dis-
play but devote few resources to helping the user integrate information within and across a dispa-
rate set of displays and data representations. There is little “perceptual room” left in the standard
set of representations to support higher-order gestalt perceptions of system function and state.
This can be seen as a bandwidth problem: the graphical communication “channels” are cogni-
tively and perceptually overloaded at the user's end. As the amount of data continues to increase
and as the visual field in which it is represented expands across more screen space, additional
communication and representation dimensions are needed to improve information bandwidth.
One very promising candidate is motion. Advances in graphics technology increasingly sup-
port powerful animation capabilities in operator workstations and consoles.However, while there
are extensive guidelines on the use of perceptually efficient static graphical techniques in informa-
tion representation [Ber83] [Tuf90] [Cle93], there is little research on the corresponding uses of
motion. Animation is used in visualization and user interfaces in an ad hoc, sporadic manner. Yet
evidence from fields as diverse as perceptual science and the performing arts suggest that motion
has much richer communication potential. My thesis research is concerned with determining if
and how motion may be usefully applied to problems in information visualization. This paper
reviews the perceptual and interpretative properties of motion in the context of information dis-
play and proposes the basis for a framework of investigation into the usefulness of motion as a
display dimension based on a new taxonomy of movement attributes and uses.
1.1 Organization
The paper is organized as follows. Section 2 describes issues in current SCADA information
and interface design and identifies certain key problems of information representation which pres-
ently used display techniques are ill-equipped to solve. Section 3 discusses the basis of perceptual
efficiency in visualization and the approach of ecological design and investigation. The motiva-
tions for considering motion as a potentially useful display dimension are considered in Section 4.
Section 5 reviews the use of motion as communication in various environments. It begins by
describing current and proposed uses of animation in user interfaces and information visualization
and presents an overview of how movement is used to represent information in dance, conducting
and character animation. Section 6 proposes a taxonomy of motion properties. Section 7 suggests
potential areas of application in SCADA interfaces and information visualization. Section 8 dis-
cusses implementation issues to be addressed in implementing motion representation effectively
and reliably. Section 9 concludes the paper.
Perceptual and Interpretative Properties of Motion for Information Visualization
5
1.2 Terminology
I use the following terms in this paper. Visualization refers to both the way in which the data is
displayed and the “cognitive operation of forming the mental image of the data to facilitate
insight” into relationships and constraints [WML94]. A display technique is either digital or ana-
log. Digital representations are alphanumeric and portray the exact value of the data. Analog rep-
resentations use graphical coding. Analog coding dimensions include colour, size, position and
orientation. Dimensionality of size obviously depends on the viewing dimensionality (2D or 3D).
A coding dimension is also termed a display dimension. The coding granularity of a display
dimension refers to how many distinct meanings, or separate codes, can be efficiently perceived.
(See Section 3.1 for a more detailed discussion of perceptual efficiency.) A display is a data “con-
tainer” which may reside on a physical screen or in a window (virtual screen). A screen can con-
tain one or more displays. A display can be “attached” to one or more windows, or span one or
more pages (connected screenfuls of information): it may portray groups of devices, sensed or
derived data, state and/or events.
2 The User Interface Bandwidth Problem
As the data acquisition capabilities of control systems have increased, the operator’s role has
evolved from low-level manual control to high-level management and supervision. These comple-
mentary trends have resulted in a ballooning of the complexity of the underlying information
space and the volume of data used in the operator’s tasks[MS97]. The traditional approach has
been to add more hardware and software displays to accommodate the explosion of information.
The problem is bandwidth: while the display capacity of the system can be increased arbitrarily
information transfer is bottlenecked on the limits in the user’s perceptual capacity. We define user
interface bandwidth as the capacity for information communication/transfer between the user and
the system at the interface. We are concerned with the communication from system to user, in
which information is encoded into digital (alphanumeric) and analog (graphical) forms and the
user must interpret (decode) the information in a timely fashion.
The user’s cognitive “cost”, or effort, of decoding representations is a function of memory
access and the mental operations of search and computation. A perceptual operation is carried out
by the low-level, preattentive human information processing system (which, for the purposes of
this paper, is the human visual system). Perception is a highly efficient, “automatic” parallel proc-
ess. Cognitive operations involve higher-level, “conscious” effort and are serial in nature. The per-
ceptual coding granularity of a display dimension refers to how many distinct meanings, or
separate codes, can be retained in short-term memory, thus requiring no cognitive recall effort.
Digital representations are effective when exact values and quantitative computation are required,
but involve the serial, effortful tasks of “reading” and cognitive inference. Graphical representa-
tions are useful for qualitative assessment because they can invoke perceptual rather than cogni-
tive inferences [Cas91] and exploit the human capacity to perceive separate discriminable features
of objects in parallel (search) and to recognize patterns (computation)[Cle93] [Tuf90] [WC95].
There is, however, a substantial gulf between the knowledge of these basic perceptual building
blocks and effective display design in complex information systems. The first problem is one of
appropriate display design and over-use of perceptual coding. Information visualization and
design literature has addressed issues of graphical perception and appropriate data representation
with respect to useful graphic design [Ber83] [Tuf90] [Mac86] and for specific types of informa-
tion extraction [Cle93]. The guidelines are useful for improving the clarity and usability of visual
presentation, but as Casner points out [Cas91] they offer little empirical insight into the funda-
Perceptual and Interpretative Properties of Motion for Information Visualization
6
mental reasons of why a particular technique or practice is useful, and they are information- rather
than task-centric (concerned with representing information structure as opposed to supporting the
user’s task-specific needs). Moreover, the proposed techniques exist in a singular context: that is,
there is an implicit assumption that all the perceptual and coding resources can be devoted to that
representation. However, as will be shown in Section 2.1, users of complex systems are increas-
ingly dividing their resources between a multiplicity of representations and perceptual codes.
When the discriminability of a code is exceeded, understanding the representation is reduced to an
effortful, serial process of mapping each code to long-term memory and decoding the value.
The second problem relates to the process of distilling information from data. Substantial cog-
nitive effort is required to recognize, retrieve and integrate information from different data in dif-
ferent representations and displays. The fall-out from the over-use of perceptual coding discussed
above is that there is no “extra” coding granularity in the currently used display dimensions to off-
load these effortful cognitive operations to the perceptual system.
2.1 More Data, More Displays...
Control system user interfaces typically still reflect an elemental design approach [Woo95b]
(“one sensor, one display”). Users often work with dozens of displays and thousands of data
points. In control rooms where space is not limited (such as those used in telecommunications and
power distribution [Byb92] [DBB91]) it is not uncommon to see interfaces physically distributed
across banks of CRT stations (on which users “page through” windows or displays), large wall-
mounted shared displays, static maps/mechanical status boards, shared message boards and video
screens from remote camera feeds. In one typical power distribution system (TransAlta Utili-
ties[DBB91]) the CRT-based system comprises 2507 possible pages and users routinely manage a
few hundred. Even in space-constrained environments like the cockpit, the interface is spread
across six to eight screens, some dedicated to particular displays and some which can be config-
ured by the pilots [CCMG97]. Thus users are constantly “flipping through” displays in space and
time to build up a mental image of the system state and behaviour [Byb92] [Bai91].
Displays tend to be densely populated with data to optimize the use of screen real-estate and
reduce the number of sequential accesses a user makes. Digital (alphanumeric) displays, which
force operators to read information in a serial, cognitively effortful fashion, are used when exact
values need to be known, but are increasingly augmented by graphical displays. Graphical repre-
sentations include charts, graphs, diagrammatic displays (such as maps and schematics) and the
depictive mimic displays [GGB89] [Bai91] which reflect the physical appearance and organiza-
tion of system components. Most graphical displays are still two-dimensional, although there is
increasing interest in exploring 3D as a more effective use of visual space [WAS86] [Alv93]
[WML94] [WMT96] [MOW97]. Symbols and icons are heavily used. The most common display
dimensions for coding value and state are colour, position and size (where position refers to spa-
tial proximity and alignment, and size is the height or width of an element.). The most common
indication of fault, or alarm, conditions is blinking or flashing the relevant display element
[GGB89] [DBB91] [Woo95a].
The efficacy of these representations is constrained by screen space and perceptual resources.
There is some debate on the number of symbols which can be perceptually decoded (Gilmore sug-
gests a limit of 15 to a “symbol alphabet” [GGB89] while Bainbridge gives evidence to show
competence up to 33 [Bai97]). However, process and network displays typically use significantly
Perceptual and Interpretative Properties of Motion for Information Visualization
7
larger symbol sets, consisting of the symbols associated with the underlying physical system (e.g.
[oA86]), the symbols which refer to the control system itself, and finally the icons which are
related to the user interface (such as iconified windows, display identifiers and cursors).
Factors which limit perceptual effectiveness of a display dimension to which data values are
assigned include its coding granularity and visual acuity. In particular, colour is over-used in most
systems [WAS86] [Bai91] with fully saturated hue as the dominant code. Yet only 7-10 hues can
be usefully distinguished [Hea96] in the narrow foveal range of vision. Moreover, certain colours
(such as red and orange) appear much brighter than others of equal luminance and thus attract
attention, distracting from the decoding operation. Hue changes in the periphery are not well per-
ceived. Relative position and size are decodable only within a common frame of reference (i.e.,
plotted against similar axes and scales), and are difficult to assess when the representations are not
close to each other [Cle93]. Thus, for example, it is difficult to determine whether two tank levels
displayed on separate screens (or non-aligned displays) are equivalent without calculating each
value separately and comparing them (a cognitive operation) as opposed to more efficient percep-
tual inferences that can be made by comparing two adjacent heights. Shape, position and size are
difficult to decode in conditions of visual noise: that is, when the displays are too cluttered and the
resolution of the representation poor [Bai91]. Gilmore suggests a general guideline of 50% den-
sity for SCADA displays [GGB89]; it is not clear, however, how density is measured. What is
apparent is that most displays are too densely populated and the subscribed display dimensions
over-used, complicating rather than facilitating user comprehension and causing a sense of data
overload [WAS86] [Byb92] [Woo95b].
Flashing or blinking is a particular example of data overload. An abrupt change of luminance
or onset of motion automatically attracts visual attention to the area [STK81]. This effect is
negated and in fact interferes with search when multiple elements on the displays begin flashing.
As one NASA Mission Control operator stated, after the Apollo 12 spaceship was hit by lightning.
“...all the lights came on. So instead of being able to tell you what went wrong, the lights were
absolutely no help at all” [Woo95a].
2.2 ...Insufficient Information
In practice, SCADA interfaces often suffer from “too much of a good thing”: too many col-
ours, shapes and visual cues are combined injudiciously in an effort to represent increasing vol-
umes of data, resulting in interfaces which are more rather than less effortful to use. We believe
the bandwidth problem is exacerbated by too much direct data and not enough information.
Woods defines information as a link between the data (referent), the symbol (representation) and
the user (knowledge, context and expectations) [Woo95b].
Current SCADA interfaces are information-deficient in three areas.
2.2.1 System Behaviour and Change
Increases in magnitude and complexity emphasize the need for higher-order system behaviour
information.Key examples are summary views (integration of system functions over many varia-
bles) [DBB91], meta-information and representations of change (nature, rate and history).
Performance and predictive summaries are important because the lack of explicit indication of
high-order system function and state forces users to expend significant cognitive effort and time in
assembling a mental image of how well or poorly the system is doing (and has done) from a mul-
titude of lower-level data views. What few summary views exist tend to be separate displays
which are heavily used but which impose the mental burden of spatial and temporal information
integration with the more detailed data displays [BODH94]. In particular, case studies of network
Perceptual and Interpretative Properties of Motion for Information Visualization
8
managers in telecommunications and power distribution operators emphasized that users want
more effective alarm grouping, prioritizing, sorting and summary mechanisms without paying the
extra overhead of more displays to manage and to relate to their detailed views [DBB91] [Byb92].
Meta-information is directly concerned with situation awareness, especially where automated
operation is involved [ATP95] [SW95]. New levels of automation in complex systems have
resulted in a proliferation of modes or operational contexts. This places new cognitive demands on
the human controller, who must track the automation processes and carry out different actions
depending on system mode [SW95]. Modal information is often presented to the human as simply
a small flag or textual field in one part of the display which is often missed or ignored [CCMG97].
When several operators are working on a shared part of the system they need to explicitly warn
each other about potential overlapping actions. Often this is done by voice [Byb92] but in high-
tempo workloads this adds to situation confusion and overload.
Perhaps the most crucial requirement to understanding a dynamic system is effective represen-
tation of how the system changes. Users rely on temporal reasoning to understand dynamic system
behaviour. Decortis et. al. describe control system operators reasoning about time as an explicit
variable (duration, time of occurrence) and implicitly (how the state of the system at time trelates
to the state of the system at time t+1) [DdKCV91]. Current representations of change are either
direct and immediate (i.e., the event simply causes a change in the value displayed) or indirect and
persistent, in which time is explicitly represented (e.g., trends). Trend graphs, which plot time as
an explicit variable along an axis, are extremely useful as process histories but require substantial
screen space and thus are typically used as separate displays with limited groups of devices or val-
ues [DBB91].
Not only must the event of change itself be obvious but the magnitude and the rate of change
must be immediately apparent. Consider the example of the Apollo 13 accident which was caused
by an explosion in one of the oxygen tanks. Mission controllers monitored a screen of digital
numbers in which the catastrophic change in tank pressure showed up only as a sequence of three
values for one tank over four seconds (996 psi., 1,008 psi, and then 19 psi). As a result the event
was missed and it took 54 minutes of investigation into subsequent system failures and explored
hypotheses before the problem was detected [Woo95b]. An explicit indication of the rate and
magnitude of this change would have immediately alerted the controller to the explosion in the
tank.
2.2.2 Integration of data across displays
Our particular concern is with representation congruence and coherence across the whole user
interface. Display proliferation has led to the keyhole or lost in space phenomenon [Woo84] and
imposes significant burdens in mental integration and the assembling of information for problem-
solving across space (disparate displays and surfaces) and/or time (sequential views) [Bai91]
[DBB91] [Byb92]. Our previous work with a multi-screen interface [BHD95] identified the need
for integrative cues to perceptually connect data in disparate displays. It is common for users to
inspect various views of data in different contexts as part of monitoring and problem-solving. For
example, a power distribution operator investigating a line overload problem may need a sche-
matic of the relevant switches, a trend of the line loads and an alarm history. The relevant data typ-
ically reside in various separate displays and the user has to visually “collect” the appropriate
items1. Given the dynamic nature of the system, this visual collection involves not only obtaining
1One BC Tel network manager referred to this task as “inviting all the right pieces of information to the party”.
Perceptual and Interpretative Properties of Motion for Information Visualization
9
a particular set of static values but also continual attention to those areas on the display: in effect,
the user is maintaining a set of “visual pointers” [PBF+93]. Woods defines the information space
as a virtual perceptual field over which we have limited viewpoints and emphasis the needs for
mentally economical (perceptually efficient) orienting cues to alert the user to the fact that some-
thing interesting is going on another part of the perceptual field [Woo84].
2.2.3 Data relationships
Improving interface bandwidth implies that information visualization needs to be considered
as an integrated whole - displaying not only data but also the relations between data in perceptu-
ally efficient ways. Traditional display design concentrates on data organization to convey certain
qualitative relationships between the data (e.g. “same as”, “higher than”, “earlier than”, “part of”).
There are no well-established techniques of displaying the semantically richer dynamic relations
between elements both within and across displays of association,dependencies,sequence/order
and causality. Association can include user- or system-defined grouping (all alarms of a certain
type, all devices under maintenance). Dependency illustrates how processes and data rely on each
other in system functions (especially useful in “what if” scenarios and contingency analysis).
Order may refer to temporal or hierarchical ranking. Perhaps the most pressing need is for effec-
tive representation of causal information. Causal data is increasingly available from diagnostic
sub-systems but is delivered to the user in textual form, requiring a mapping to other state displays
as opposed to an intuitive comprehension in place.
3 Issues in Display Design
3.1 Perceptual Principles for Visualization
3.1.1 The Proximity Compatibility Principle
Wickens and Carswell [WC95] suggest that displays relevant to a common task should be per-
ceptually “close”. Their proximity compatibility principle (PCP) depends on two dimensions of
similarity: perceptual proximity and processing proximity. It proposes that close task proximity is
best supported by close perceptual proximity; conversely, independent processing requires distant
perceptual proximity. Perceptual (display) proximity defines how close together two display chan-
nels are in the user’s perceptual space (i.e., how similar they are). For example, two sources will
be perceived as more similar (in closer proximity) if they share colour, physical dimensions, code
(analog or digital) or are spatially near. Processing (mental) proximity defines the extent to which
sources are used as part of the same task. Integrative tasks, in which two or more data must be
computed or compared to arrive at the needed information, have high mental proximity. Noninte-
grative processing of similar tasks has lower proximity. Similarity depends on the sharing of cer-
tain features: e.g, metric (information portrayed in same units); functional (same operational or
device group); processing (same computational routine on different sources); or temporal (dissim-
ilar sources processed concurrently involving frequent visual transitions and contributing to the
same goal). Finally, nonintegrative processing of dissimilar tasks, in which the user is switching
attention between disparate tasks with no common goal, has the lowest mental proximity.
The authors suggest several display manipulations to decrease information access by increas-
ing perceptual proximity: put the objects close together; group them visually (perhaps by enclo-
sure); use the same display source (colour, texture, orientation) to associate information source
(e.g., all tank gauges are bar charts); use the same display property to indicate value (height of the
bar); and object integration. Object integration arranges information sources so they appear to be
part of a single object and exploits the perceptual processing mechanism that decodes the “separa-
Perceptual and Interpretative Properties of Motion for Information Visualization
10
ble” features of objects in parallel [KT92]. Examples are connecting a series of dots with a con-
tour, or the common dimensional integrality of a point in an (x,y) graph rather than parallel
measures of extent.
3.1.2 Emergent Features
Wickens and Carswell [WC95] emphasize that Information integration (as opposed to access)
is well supported by emergent features: properties inherent in the relations between raw data
encoding which serve as a direct cue for a an integration task which would otherwise require com-
putation or comparison of the individual data values. An example is alignment of bar charts of
similar value, which is not a property of any of the individual bars in isolation, or volume of a rec-
tangle whose height and width are mapped to separate sources. They caution that emergent fea-
tures, while effective for integrative tasks, can interfere with focused attention on decoding
individual values, especially in noisy environments where adjacent or overlapping images will
lead to decreased discriminability.
3.1.3 Directed Attention
Focusing attention in a visually noisy field with many data channels whose values are con-
stantly changing (for example, in fault management situations) requires the user to maintain con-
trol of where she is attending at the same time as being aware of potentially interesting areas as
conditions change. Woods has defined the need for a set of cognitive tools to support control of
attention in fault management situations where the user must sort through an overload of raw data
[Woo95a] which should exploit preattentive reference. He identifies several criteria for such atten-
tion-directing signals:
accessibility (i.e., the user should be capable of picking them up without losing track of cur-
rent activities;
partial information: the signal should carry enough partial information for the user to pick
up whether to shift attention to the signalled area; and
mental economy: the representation should be processed without cognitive effort.
3.2 An Ecological Approach
Woods [Woo95b], Wickens [WC95] and Casner [Cas91], among others, emphasize that data
representation which is not relevant to the greater task environment is inevitably ineffective.
Woods calls this the “decoding” problem [Woo95b]: domain data can be cleverly mapped into vis-
ual attributes, but unless the user can decode the representation in the actual task (under condi-
tions of attention switching, risk and time pressure) the representation fails. This it is not
sufficient to design a display with emergent features which are not mapped to variables of impor-
tance to the current task [WC95]; we need representations which are ecologically valid, a concept
which draws from Gibson’s principles of ecological perception [Gib76].
Gibson theorized that we perceive our environment directly as ecological entities and move-
ment rather than as abstractions of light and shadow which must then be internally computed into
meaningful components. The composition and layout of objects in the environment constitute
what they can afford the observer. Affordances can be thought of as the possibilities, opportunities
and indeed meaning of objects in the environment: since affordances can be directly perceived, it
follows that meaning and value can also be directly perceived (rather than computed).
Gaver [Gav93] has employed this approach in determining salient properties of sound to con-
vey information about events and meaning in the environment, which he characterizes as the
study of ecological listening as opposed to that of audio perception. Similarly, the ecological
Perceptual and Interpretative Properties of Motion for Information Visualization
11
interface design (EID) approach of Vicente and Rasmussen [VCP95] emphasizes the representa-
tion of higher-order function, state and behaviour information as task-relevant variables integrated
over lower-level system data. Ecological design can exploit the perception of emergent features.
The power of this approach is that the act of integrating the values into knowledge of the system’s
functional performance becomes a perceptual rather than a computational operation.
3.3 Design Challenge
There are two complementary directions which must be addressed in ameliorating information
overload in the user interfaces to complex systems:
1. explore new perceptually effective ecological representations which may increase informa-
tion dimensionality and thus interface bandwidth; and
2. determine whether these new coding dimensions can extend the integrative effect across dis-
plays and representations separated by space (and possibly by time). An important property
must be explicit support for visual momentum, the user’s ability to effectively extract informa-
tion across displays [Woo84].
4 Motivation
We believe motion to have great potential as an display dimension for three reasons:
4.1 Low-level perceptual efficiency.
Motion perception is a preattentive process: motion can elicit “pop-out” effects in which mov-
ing objects can be searched in parallel by the visual system [WS91]. Ware reports studies that
show moving objects can be searched in parallel for targets with different direction and different
rates of rotary motion[JH70] [WL94]. Psychologists believe that motion, like colour and form, is
handled by a dedicated visual processing mechanism [Cut86] [PBF+93], indicating that it is a
“separable” feature of an object [KT92]. (The reader is directed to [WS91] for a more detailed
description of motion perception.) In his extensive review of temporal factors affecting informa-
tion transfer from visual displays, Sekuler [STK81] reports motion detection times as low as 50
msec. Like all visual functions, the periphery is less sensitive than the centre of the visual field to
motion perception. However, motion response degrades less than spatial acuity or colour percep-
tion in the periphery. Movement is reported as improving the visibility of targets embedded in
“random or cluttered” fields, especially away from the centre, where detection time is considera-
bly reduced. Thus, unlike hue or shape discrimination which require the visual acuity of the foveal
range, movement is suited to extracting information from “noisy” environments across the entire
visual field. This is important in interfaces in which operators are not guaranteed to be looking
straight ahead at a display all the time.
The human visual system is very good not only at perceiving but also at tracking and predict-
ing movement. Recent research has shown we can track multiple motions in parallel [PBF+93]
without effortful context-switching. Eilan et. al. state there is “compelling evidence for the inter-
nalization and semi-automatic use of quite specific physical principles that generally yield very
accurate [mental] representations of object trajectories” [EMB93]. They suggest that humans
employ a low-level “intuitive physics” which correlates geometrical properties of distance and
size with the physical properties of velocity, mass and acceleration. Subjects are able to interpo-
late and judge trajectory points when shown “interrupted” motions, manifesting an inherent abil-
ity to predict the current and continuing motion of objects in space. Studies reported by Cooper
and Munger suggest this is done by internalized kinematic rather than dynamic principles. Kine-
Perceptual and Interpretative Properties of Motion for Information Visualization
12
matic principles link position, velocity and acceleration without regard to mass; dynamic princi-
ples, on the other hand, employ concepts of forces and mass to explain changes in rest and
movement states [CM93].
In addition, we use motion to derive structure and animacy from very sparse cues. In his semi-
nal work on biological motion, Johannson [Joh73] found that subjects could identify characteris-
tics and structure of human figures from only 10 moving “dots” (lights attached to the bodies).
Subjects could not identify any meaningful structure from static presentations of the dot group-
ings. However, even sparse movement gave instantaneous rise to the recognition of a moving
body. Subjects not only identified the full body from as few as 10 lights (and the legs from only
5); they also identified the gaits and the quality of the gait characteristics from the motion (walk-
ing, walking with an injury, running, etc.) When the motion was rigid it was identified as mech-
anistic: non-rigid motion gave the sense of animacy.
Subjects in experiments conducted by Bassili [Bas78] identified facial structure and emotion
from similarly sparsely placed lights when motion was present but were unable to extract any
information when the stimulus did not move.
Finally, motion has the effect of grouping. Things that move together are seen as grouped or
associated. Cutting showed that rotating disconnected objects around a common axis led to the
perception that they were connected into a rigid structure by invisible “rods” [Cut86]. Gibson
looked at moving “patches” or closely bunched textures of dots: differences in their speed resulted
in a perception of “twoness” [Gib76]. Realistic simulations of herd and flock behaviour have been
produced by ensuring some communality between the movements of the individual actors (see
[Rey87] for an early example]).
4.2 Interpretative scope.
Motion is cognitively and ecologically rich. Gibson defined motions as ecological events to
do with the changes in the layout and formation of objects and surfaces around us. In his approach
all perception is motion perception: the flow of such information through the optic array is what
gives us the information about the 3D world [Gib76] [Joh75]. It is obvious motion can convey
information that static representations cannot: it is difficult to imagine an intuitive static display of
causality, for example. Decortis found that spatio-kinematic representations helped users reason
more effectively about temporal data in continuous processes [DdKCV91]. In Gibson’s terms,
motion affords behaviour and change. In our real virtual field things are constantly moving. Evi-
dence from perceptual psychology indicates that the onset or change in movement in our visual
field grabs our attention involuntarily, suggesting that multiple, constant and irregular movement
should be highly disorienting. Yet obviously as functioning actors within our environment we are
able to somehow manage and selectively attend to the visual information without constant con-
scious effort.
At the other end of the cognitive spectrum, we derive very rich meaning from movement. Rel-
atively simple combinations of motions can be interpreted as highly sophisticated behaviour. The
arts of drama, dance and music map very complex emotions and motivations on to gestures and
movement. Moreover, we tend to anthropomorphize movement sequences in which there are sev-
eral “actors”, no matter how abstract the representation. Jetha’s thesis project, which investigated
how people carry out complex design tasks, had subjects generating dance sequences from an ini-
tial “abstract” motion sequence involving a cube, pyramid and a sphere in which all but one sub-
ject mapped the object simple movements onto articulated human figures with many more degrees
of freedom [Jet93].
Perceptual and Interpretative Properties of Motion for Information Visualization
13
Character animation relies on the exaggeration of movement to deepen our understanding of
behaviour and motivation [TJ81]. Moreover, basic spatiotemporal properties of movement elicit
impressions of intention and actor [Kas81]. Very simple actions which are computationally inex-
pensive to animate can produce complex psychological impressions [LW90]. (This is discussed
more in Section 5.2.3.) People construct complex emotional interpretations of behaviour and
intentionality from different patterns of motion. This contribution of motion to social perception
has been investigated by Heider and Simmel [HS44], Kassin [Kas81] and Berry and Springer
[BS93a].
Heider and Simmel [HS44] investigated the perception of attribution using an animated film
technique to show people a cartoon in which a large triangle, a small triangle and a circle moved
around a rectangle with a “door”. Subjects anthropomorphized their impressions and attributed
complex behavioural states, motives and personalities to the objects, such as timidity, aggression,
protection and affection. Berry and Springer [BS93a] conducted a study with preschool-age chil-
dren in which they replayed three versions of the Heider film: one in which the structural object
information was intact but the movement was disrupted; one with intact movement but structural
distortions; and one in which both the structural and movement properties were disrupted. Their
findings confirm that attribution and causality perception was based on the patterns of motion
rather than structural information. Kassin further showed that this informing of social perception
holds across diverse populations [Kas81].
Michotte reported extensively on the contribution of motion to the direct perception of causal-
ity [Mic63]. He found solid objects were unnecessary for creating a causal impression: rather, it
arises from specific combinations of motion which our perception unifies into a single, compound
“causal” movement. “Pure” causality was perceived when the causal object A was totally respon-
sible for the subsequent movement of the passive B (launching and entraining). “Weaker” effects
(i.e., in which the effecting object generated some latent behaviour in the effected object B, such
that B’s behaviour was autonomous without being spontaneous) were identified as triggering,
attraction (such as iron filings to a magnet) and transporting.
4.3 Availability
Motion is under-used and therefore available as a “channel” of carrying information, as will be
described in the following section. Increases in computing power have made the production of
seemingly sophisticated motion relatively inexpensive. For example, Reynolds’ 1987 “flocking”
simulation [Rey87] has since been rendered in real-time. Basic computer animation techniques
like colour table animation and simple forward kinematics [FvDFH90] are accessible to even
moderately-configured desktop machines.
We anticipate that a major advantage of motion coding will be its compact use of screen real
estate, freeing up spatial display dimensions for other use.
5 Movement As Representation
5.1 Animation
The arrival of animation capabilities at the desktop has provoked interest in the use of known
animation techniques for computer-human communication. A common thread to the proposal and
inclusion of animation capabilities in user interfaces is a strong intuition that motion and making
information objects move should make the interface environment more credible, more “real”, less
cognitively foreign to users. Baecker and Small [BS90] discussed the potential of user interface
Perceptual and Interpretative Properties of Motion for Information Visualization
14
animation to reveal process and structure (by moving the viewpoint) and introduced the following
taxonomy of eight uses of animating function to make the interface more engaging and compre-
hensible.
Identification associates the symbol with its function (“What is this?”);
Transition carries the user smoothly between states (“Where did I come from and where
have I gone?”);
Choice shows possible actions (“What can I do now?”);
Demonstration illustrates the capabilities of the tool or service (“What can I do with
this?”);
Explanation shows how to employ it (“How can I do this?”);
Feedback provides information on process dynamics and state (“What is happening?”);
History replays previous actions and effects (“What have I done?”); and
Guidance suggests suitable next steps (“What should I do now?”).
Stasko [Sta93] adds four design guidelines drawn from the principles of traditional animation.
Appropriateness dictates that the operation or process should be represented according to
the user’s mental model and system entities.
Smoothness is essential since jerky, wildly varying animations are difficult to follow.
Duration and control vary with the type of animation. Demonstrations of unit operations
such as selection should be short (not more than a few seconds). Animating continuous
processes with a clocktime correspondence should be kept faithful to the clocktime. When
animation is used as explanation, the user should be allowed to control the rate and replay.
Moderation prescribes judicious application of animation: too much is overdone and too
cute.
5.1.1 Animation At the Interface
Motion in its most basic form has long been used in interfaces: much use is made of blinking
as a human interrupt to attract and direct visual attention. In many supervisory control systems it
is the primary visual cue for alarm conditions. There is some evidence to suggest a limited coding
granularity of 4 [GGB89] or 5 [WBKC92] flashing frequencies. Anecdotal evidence indicates that
people find blinking excessively annoying and visually ineffective when too many items are flash-
ing (who has not cursed the WWW HTML blink function?) In large-scale systems where alarms
tend to propagate rapidly, over-flashing not only reduces effective alarm information but also
renders the displays visually disturbing, distracting users from effectively perceiving the needed
information from other representations [Woo95a].
Schlueter exploited this visual dissonance property of motion to enhance perceptual differ-
ences in crowded display environments with overlapping windows: to avoid the effect of window
contents seeming to continue, or “bleed”, across borders he “jostled” the windows to enforce per-
ceptual differentiation [Sch89].
Animation is increasingly used as visual momentum to provide smooth transitions between
views. The Macintosh [ACem] interface uses “tracers” to draw lines between states when expand-
ing and iconifying windows. The Sun OpenWindows [SM] system uses a similar “telescoping”
technique. Later distortion visualization techniques s directly animated the changes in the objects
themselves. The Perspective Wall [MRC91] allows the user to smoothly horizontally scroll a lin-
Perceptual and Interpretative Properties of Motion for Information Visualization
15
ear “sheet” across a magnifying view. In the Continuous Zoom [BODH94] [BHDH95] objects
expand and shrink at a minimum rate of 12 frames/sec in response to user controls which magnify
certain objects and concomitantly shrink and displace others. The resulting transitions were
deemed to greatly reduce the mental integration of continuously shifting display configurations.
Cone Trees [RMC91] is a 3D technique for visualizing large sets of hierarchical information in
which the user can quickly rotate “cones” to find the appropriate node and follow subsequent
links to child cones. Observations of Cone Tree use and of expert users’ problem solving in the
Intelligent Zoom [BHD95] suggest that animating a path through a visualization of an informa-
tion structure aids in information retrieval and navigation.
Ware and Franck’s investigations into motion cues in 3D visualization [WF96] confirmed the
intuition from Cone Trees that simple rotation about an axis is effective in interpreting 3D infor-
mation structures. They considered three kinds of rotation cues in both stereo and mono viewing
conditions: passive (i.e., automatic, no user control); hand guided, and movement coupled to
observer head position. They found that all three types of motion improved performance in using
3D graphs and all were more significant than the stereo cues alone.
Chang and Ungar [CU93] use techniques from film editing and cartoon animation in the Self
user interface with the goal of enhancing cognitive comprehension and user engagement. Motion
blur reduces temporal aliasing (this effect of an object “blinking out of existence” in one location
and “blinking into existence” at another arises from large movements in a short interval and is due
to the persistence of vision.) Filmic dissolves makes objects appear and disappear smoothly from
view. More subtle exaggeration effects highlight the realism or credibility of the action. Anticipa-
tory action is a small movement which occurs in the opposite direction of the subsequent anima-
tion and highlights the effect by subliminal prediction. Slow-in-slow-out,follow-through and arc
rather than linear paths contribute to the perception of the animated objects as being “real”, that is,
as having solidity and mass. The authors hypothesize that believable object motion makes the
interface more enjoyable and offloads the burden of deciphering interface behaviour from “higher
cognitive centers” to the perceptual system. Hudson and Stasko [HS94] have implemented sup-
port for similar character-animation based techniques in the ArtKit user interface toolkit.
Bharat and Sukiviriya propose an animation server architecture [BS93b] to emulate user inter-
action with a system with the goal of supporting script-driven animations for tutorial and group-
ware purposes.
Most recently Ware is experimenting with the use of deictic motion for narrative illustration
[WFF97] by animating soft lines which persist for a while and then disappear. Deictic functions
are communicative identification actions which directly show or point out referents, such as nam-
ing or describing the object, or specifying the target location [DAPG96]. In language, the words
“this” and “that” have a deictic function. Physically referring to objects in space involvesdeictic
gesture. Ware et. al. use linear stroking (“underlining”) movements for emphasis and highlight-
ing; smooth, enclosing “ribbon” motions to introduce and encapsulate regions; and continuous,
elongated motions to effect transitions to new areas.
5.1.2 Animation as Illustration
The most mature application of motion in displays is the animation of process behaviour over
time for illustrative, analytical and explanatory purposes, e.g. in scientific, algorithm and program
visualization.
Perceptual and Interpretative Properties of Motion for Information Visualization
16
Baecker and Small animated icons to identify and explain their function [BSM91]. The advan-
tages of animation were particularly noticeable when the small size of icons meant a low resolu-
tion of information (i.e., intricate depiction was impossible). Ambiguity was reduced and users
remembered the function of the particular icon better. Many operating systems animate process
indicators. The process indicators can either require their own sub-displays (such as percent-
done boxes [Mye85]) or overload the representation of other user interface symbols such as cur-
sors [DFAB93]. Icons are sometimes used: the printer icon in the HP VUE [HP] user interface
shows paper feeding through it when a print request is submitted and the desktop printer icon in
the Macintosh [ACem] continually shows the degree of completion of the print job. Trend graphs,
bar charts and other such analog displays in use in complex systems are instances of process indi-
cators. A key feature of process indicators is that they must be true to the explicit clock time of the
process; i.e., the representation must closely track the current state of the process and cannot flag
behind nor surge ahead.
In contrast, animation used in algorithm, program and scientific visualization does not need to
adhere to explicit clock time but rather to relative time: it can be replayed, slowed down or sped
up, as long as the relative speeds of the changing elements remain constant with respect to each
other (so that ways in which the changes occur are still meaningfully and faithfully represented.)
Animation is a popular component of visual programming for prototyping and understanding (see
[IJK90] for a discussion of visual programming and applications.) Bridgeland points out, how-
ever, that visual programming needs ways of expressing behaviour that implies an extension of
the objects and their relationships rather than “just an arrangement” of the objects through time
[Bri90]. Scientific visualization systems which rely on animation to explore complex events
include meteorological, medical, geophysical and fluid flow dynamics (an NCSA CD-ROM sam-
pler contains animations created in a multitude of scientific applications [NSC96]). Animation
was first used in algorithm visualization in Baecker’s well-known video of “Sorting out Sorting”
[Bae81], which illustrates in parallel how different sorting algorithms re-arrange data and elicits
an immediate perception of algorithm performance. Many algorithm visualization systems rely on
animation to characterize the intended purpose and meaning of programs: examples include
BALSA [Bro88], ACTION [HM90] and TANGO [Sta91]. The latter two enable users to design
and implement animations by interactively specifying graphs of data and process structures. In the
TANGO system [Sta91], users further specify the animation by laying out the path along which
the objects will travel and defining the types of transitions they will undergo: for example, move,
resize,colour,fill,raise and alter visibility. Limited control over rate of replay is supported by a
delay transition.
The supposition by the creators of algorithm animation systems is that animation is beneficial
to the learning and comprehension of how processes and systems work, since the viewer does not
have to build up a mental image of the changes from static images and descriptions to understand
the events [Won94], but there is some empirical evidence to shed doubt on this intuition. Palmiter
and Elkerton [PE91] compared animated demonstrations, procedural textual instructions, and a
combination of both in the tasks of learning and retaining interface procedures. They found that
while the demonstration group was faster and more accurate in learning the tasks the text group
had better retention, so that seven days later the text group was faster and as accurate as the dem-
onstration group in performing the tasks. They propose that animation may in some cases hinder
“deep” procedural learning since the simplicity of using demonstrations, even when text is pro-
vided, may encourage simple mimicry and discourage the use of the text. Wong [Won94] evalu-
ated sets of animations in teaching abstract statistical concepts. She found some evidence that
Perceptual and Interpretative Properties of Motion for Information Visualization
17
animations were more useful to students with low spatial ability. In general, while good anima-
tions had no positive effect on learning, poor animations were a hindrance. Students however,
were more motivated to use animations in learning since they enjoyed them more. Wong con-
cludes that the primary strengths of animation are in information synthesis and that static graphics
are still preferable for information analysis.
5.1.3 Animation as Visualization
While the above systems use animation to illustrate the changes in simulated or abstract data
objects over time, some effort has been directed to using animation as a direct representation of
otherwise unrepresented system variables. Gronquist et. al. [GSAL96] and Alvarado [Alv93]
model power system phenomena using a system of animated mass, spring and force vectors to
show load flow, transmission capacity and transient stability. Vectors accelerate and decelerate in
radial distance, width and angular displacement. Faults add to the kinetic energy of the concerned
mass vectors, with the effect that as overall kinetic energy increases the system loses synchronism
and goes out of balance. The authors state that “islanding” and coherency are particularly easy to
visualize, even in large systems, since the diagram animation clearly shows groups of machines
“swinging together”.
Gobrecht and Ware [GWB96] use animated arrows travelling along links in a graph to show
message passing activity in a multiprocessor system. Bursts and lulls in overall traffic can clearly
be seen without extra representation or user computation. Fleet and Ware [FW96] use simple
sinusoidal motion to show traffic on a link. A report on full graphical display design from CIGRE
(Conférence Internationale des Grands Réseaux Electriques) proposes that power flow can be
similarly represented by movement along a link, with the speed indicating proximity to threshold
[CIG92].
5.2 Motion as Meaning
The previously reported work focuses on the use of animation as a technique to engage the user
or to highlight certain semantic properties of objects without systematically investigating the sali-
ent properties of the motion itself. More interesting approaches consider which perceptual and
interpretative characteristics of movement may convey meaning. We may roughly classify these
as providing insight into basic motion (relating to perceptual properties); interpretative motion
(the semantics assigned to different movement types); and compound motion (how the movement
of objects relative to one another informs the perception of the relationships between them and of
the object properties themselves.)
5.2.1 Basic Motion
Ware et. al. examined the basic motion parameters of velocity, amplitude, phase and frequency
in both signalling [WBKC92] and data correlation tasks [WL94]. He used smooth linear motion
as a “human interrupt” signal in the interests of seeing whether this would evoke the same direct
pull of attention as blinking or flashing without causing the anecdotally reported associated irrita-
tion [Woo95a]. Subjects performed a primary task and were told to respond by hitting a key when
they noticed movement of one of two small icons on either side of the top of the display. The icon
was a small bar which grew and shrank vertically in an smooth, oscillatory fashion. Amplitude,
side and velocity of the movement were varied. There was no effect for amplitude or side, but
increases in velocity led to an increase in the number of quick responses and a decrease in the
number of long ones. The good average response times (1.96 sec in the condition with the fastest
velocities) indicated that subjects had no trouble noticing the interruption without any reported
Perceptual and Interpretative Properties of Motion for Information Visualization
18
irritation factor. Even the slowest times were acceptable, suggesting that motion of this kind is a
reasonable “attention getter”. The experimenters posit that velocity in this case intuitively indi-
cates urgency (value).
Relative phase proved an effective parameter for visually associating data (integration)
[WL94]. Sinusoidal motion of data in a multidimensional scatter plot was compared with the
static display dimensions of grayscale value, point size and position in a data correlation task. The
three motion parameters were frequency, phase and amplitude, but only two were available simul-
taneously, since varying the relative phase is only meaningful if the objects are oscillating at the
same frequency. The conventional scatter plot (x,y position) proved to be the most effective dis-
play technique, but the next most efficient was plotting vertical phase against X position, and it
was “not significantly worse” than the scatter plot, and actually better than point size or grayscale
value, two common techniques. Ware suggests an ecological basis for the percept of grouping
objects in phase since natural phenomena such as schools and flocks move in similar phase. He
expresses some doubt whether phase is effective with two or three groups moving simultaneously
in different phases [War97]. Michotte found that kinematic integration took place with groups of
objects moving simultaneously at the same speed and in parallel directions; i.e., the multiple
movements were perceived as a single perceptual event [Mic63]. Bassili reports a similar result
that elements are perceived to form a group when their motions share vector components [Bas76].
5.2.2 Interpretative Motion
Johannson [Joh73] and Bassili [Bas78] found that basic biological motion perception appears
to differentiate between rigid (mechanical) and non-rigid (animate) movement. Bassili considered
at a “moving lights” display of facial motion and established a relation between the rate of change
in the facial motion and the degree of surprise. The duration of the motion indicated secondary
emotional conditions (e.g., “fleeting disgust”) [Bas78]. Lethbridge and Ware add two further con-
ditions for the perception of animacy (from Marion et.al.): intentionality and a certain degree of
randomness, in the sense of lack of repetition [LW90]. Thus, mechanical motion is perceived to
be repetitive, automatic and constrained (in the sense that the pattern of motion does not deviate
from a predictable path). Animacy is perceived from fluid, spontaneous, responsive, intentional
and “free” (i.e., a certain erraticness and deviation from a strict pattern).
Kassin [Kas81] reports on studies by Tagiuiri who had subjects observe animated dots varying
movement angle. He found that straight, linear paths gave the impression that the objects were
“alert, well-reasoned, persevering, logical and ambitious”; erratic paths elicited the perception of
“drunk, confused, immature, emotional, undependable and careless”; arched paths were “noncha-
lant, leisurely, relaxed and complacent”. Michotte [Mic63] found that movement speed was
important. Rapidity gave an impression of violence, slow movement an impression of gentleness,
sudden reduction in speed was interpreted as hesitation and sudden, repeated variations in speed
elicited impressions of nervousness and agitation.
Amaya et. al. [ABC96] used signal processing techniques to analyse emotion in motion. They
captured movements from subjects performing two types of human activity, drinking from a cup
and knocking on a door, in three “emotional contexts” (angry, sad and neutral). They identified
two attributes which varied considerably over the different emotional movements: speed (fre-
quency) and spatial amplitude (the range, or size of the motion). They divided the movements
into “basic periods” (e.g “hand to cup”, “cup to mouth”, “cup down”, “hand back”); determined
the speed of the end effector along its trajectory in both the angry and neutral movements., and
calculated speed transforms for both the neutral and angry movement by integrating the longest
Perceptual and Interpretative Properties of Motion for Information Visualization
19
period along the trajectory and dividing it into frame “templates”. Then the transform can be
applied to a new, neutral movement by time-warping the frame distribution, interpolating between
frames where needed. The spatial amplitude intensity for each joint is calculated for each move-
ment period and nonlinear signal amplification is used to apply the amplitude transform to gener-
ate new joint positions from the new, neutral movement. They tested the approach by deriving
angry and sad tranforms from the cup-drinking data. Then they applied the transforms to the neu-
tral knocking data, and found a close match between the generated and the “real” (motion-cap-
tured) angry knocking motion data.
Traditional character animators have long relied on movement to convey the personalities and
intentions of their characters. Techniques like squash-and-stretch effects, exaggerated object
deformation and motion blur model the effects of forces. Anticipatory action, which as previously
discussed is a small movement in the counter-direction of the “real” action, subliminally predicts
intention and highlights the characters’s subsequent move. Movement preparation and diminution
(slow-in, slow-out), acceleration and deceleration fix the impression of the object’s physical prop-
erties - weight, mass, and power. The smoothness of the movement (implemented by animators as
transitions, or “inbetweens” to traditional animators and “keyframes” in the computer field
[Las87]) affects how it is interpreted. Disney animators Thomas and Johnston give an example of
this in describing head movement: a quick transition (no inbetweens) is seen as an abrupt hit to
the head (even where no projectile is drawn); a few inbetweens portray a “nervous” subject, dodg-
ing something,; more inbetweens indicate a crisp nodding gesture (becoming “friendlier” as more
transitions are added; and finally seven inbetweens give an impression of the subject easily cran-
ing his head to look at something, with no sense of urgency [TJ81].
Trajectory is also important in character animation. As [Las87] points out, in nature arcs are
the most efficient paths by which a form can move from one place to another. Therefore, slightly
arc’ed trajectories in animation are seen as more “natural” and less disconcerting. Our intuition is
that purely “straight” paths are seen as abrupt spatial transitions, perhaps intensifying an impres-
sion of urgency but in the execution losing the essence of the action [Las87].
Carlson Vaughan’s investigation into how people interpret emotion from movement in [Vau97]
revealed four distinguishing characteristics: path (line the movement creates), area (use of space
by the object), direction (direction of movement/animation) and speed (speed and tempo of
object). Erect, open, slow movement was considered “beautiful”; narrow, cramped and jerky
motion was considered “ugly” and mechanistic.
Laban and Lawrence [LL74] use a 4D space to classify human movement based on effort in
which the axes are exertion (light - strong), control (fluent - bound), effort (flexible - direct) and
duration (sustained - quick). Exertion is concerned with strength or weight (W); control with
space (S), effort with flow (F) and duration with time (T). The eight basic (W,S,T) exertions are
“slashing, gliding, pressing, flicking, wringing, dabbing, punching and floating”. Figure 1 plots
this space, where each corner represents a basic effort. Those connected by lines share two ele-
ments and differ in one element only. (Thus punching, for example, shares space and weight
attributes with pressing and differs in its time signature.) The fourth observable phenomenon of
effort is flow, in which one either “struggles against” or “indulges in” the effort.
They characterize the interpretation of movement as one of understanding and integrating
combinations of these four factors. Thus, intense, emotional movement (such as punching) is a
combination of strong, bound, direct, and fast; relaxed, calm, exploratory movement maps to
light, fluid, flexible and sustained. We note that the Laban characterization of movement concen-
trates on the forces involved: so, for example, movements can be considered “direct” (controlled
Perceptual and Interpretative Properties of Motion for Information Visualization
20
use of space) and still differ in absolute amplitude (e.g. an angry knocking and a wagging finger).
However, they may not differ in relative amplitude: that is, the extent to which they occupy the
possible movement space.
An interesting aspect of Laban’s taxonomy is that one-sided exaggerations of effort may be
perceived as having character or behavioural overtones. The authors give examples of laziness
(exaggerated sustainment with little influence from other factors), hastiness (exaggerated quick-
ness) and obstinacy (directness).However, Laban and Lawrence do not identify types of commu-
nicative motions per se; instead, they assess the effort characteristics of a person’s movement and
use it to postulate character traits of the individual. They suggest people who move easily and rap-
idly seem to be freer as opposed to those who are “struggling against” time. Movements which
demand less force or strength suggest relaxation and contentment. Flexibility and twisting in the
movement space suggest happy exploration and security in the mover’s sense of space, where
direct, constrained movements suggest stress. Controlling flow occurs when an individual tightly
controls the progression of movement and indicates reticence. Having laid an initial groundwork
for some truly sweeping psychological generations, the authors then conclude than the richness of
combining these four factors is so complicated as to be unworkable and suggest abandoning any
kind of psychological terms!
Finally, the authors make the point that efforts, and effort-rhythms, can be “transmitted more
easily than thoughts”, so that in a dialogue between humans, movements which are independent
of the content and object of the communication are still observed and internalized very quickly
and powerfully.
Musical conducting is another field in which expression and direction are conveyed through
movement. In this domain, the movement tempo is constrained to reflect the desired tempo of the
music, and the physical area (where the hand is located when the motion takes place) is related to
the organization and direction of the orchestra members and sometimes to signalling change in
the dynamics and progression of the piece. In the grammar of musical conducting [Rud80], it
appears that movement amplitude,shape (smooth and curved vs. straight and sharp-edged) and
temporal continuity are the expressive dimensions. Small, straight movements are considered
Flexible
Direct
Light
Bound
Strong
Fluent
Sustained Quick
W
F
T
S
a. 4D “effort space”
Pressing Wringing
Slashing
Punching
Floating
Flicking
Dabbing
Gliding
0a.
Figure 1. The Laban Movement Space
ST
S
T
WW
WW
S
ST
T
Perceptual and Interpretative Properties of Motion for Information Visualization
21
“neutral”; quick, slightly curved motions which stop at the end of each iteration are “bouncy”,
“energetic” and positive; and large, curved, swooping movements convey emotion and passion.
The dynamics of the music and the volume of sound are expressed by the size (i.e, the spatial
amplitude) of the gesture. A conducting pattern is a set of movements, the number of which cor-
responds to the number of beats in the music signature. Motions need not be symmetric in shape
a. Nonespressivo b. Espressivo
c. Marcato
d. Tenuto
Figure 2. Examples of Conducting Movements [Rud80]
Perceptual and Interpretative Properties of Motion for Information Visualization
22
but the degree of curvature, spatial continuity (the extent to which the gestures are “sharp” with
abrupt changes in trajectory) and temporal continuity (whether there are momentary stops in
between beats) are important cues.
Figure 2 shows examples of several different conducting patterns. Figure 2a shows a nones-
pressivo pattern, which is described as a “plain, continuous, neutral” motion, which uses mainly
straight lines and has no intensity information. Contrast this with the espressivo gesture in Figure
2b, which is curved and continuous, and whose intensity and extent of curvature increases with
the “emotional quality” of the music. The staccato pattern (not shown) is quick and slightly
curved with a stop on each count and bounce on the downbeat, and is characterized as “snappy”,
“energetic” and “bouncy”: all terms which imply positive and enthusiastic feeling. The marcato
pattern, in contrast, (Figure 2c) uses a heavy motion with a stop on each count and is interpreted
as “forceful” and “aggressive”. The tenuto pattern in (2d) is related to the marcato in forcefulness
but lacks its aggression. As the musical passion and dynamics intensify so would the curvature
of the marcato and tenuto patterns.
5.2.3 Compound Motion
If we recall that our visual systems have motion-sensitive mechanisms for establishing group-
ing (section 4.1) then it would seem natural that we have some preattentive capabilities for assess-
ing interactions and relationships between entities from their movement. Bassili [Bas76] and
Berry [BS93a] studies of social perception and Michotte’s earlier work on causal attribution
[Mic63] have found that simple existence of a temporal contingency is enough to indicate some
interaction. i.e., as long as there was some perception of a temporal association, with object
actions appearing to occur in some sequence within a small time interval (in the case of the Bassili
experiments this was set at 7 frames in a film of 24 frames/sec, or ~290 msec.[Bas76].)
Michotte’s experiments suggest that causality is perceived rather than interpreted: that is, a move-
ment of object A (the motor) can be seen to cause the subsequent movement of B (the projectile)
as a direct percept [Mic63]. Causality is perceived under appropriate conditions of time, space
and speed of the two moving objects. The temporal interval must be small enough for the move-
ments to be seen as a”whole”. If object speed is fast enough, there can be a fairly wide gap
between the objects (50-70 mm). However, the objects must be seen to exist in the same plane.
Relative speed acts as an integrating factor, determining, for example, whether A launched B
(descending ratio of speed before and after impact) or A triggered B (ascending ratio). The key
factor to causal perception is movement ampliation, where the movement of the motor object (A)
extends into that of the projectile (B). To verify this Michotte considered the perceived effect of
A’s movement on a qualitative change (appearance, disappearance, change in form or colour) of
object B. When there was no opportunity for movement ampliation, no causality was remarked.
Thus merely causing objects to appear to appear and disappear in temporal and spatial contiguity
is insufficient for the impression of causality (as in flashing them on and off the screen in close
coincidence); some form of kinematic integration must occur. Bassili [Bas76] further investi-
gated temporal and spatial contingencies in social perception, and found that the simple existence
of a temporal contingency is enough to indicate an interaction. However, the animations in which
there was a spatial contingency, i.e., in which the objects were constrained to remain within cer-
tain relative distances, were perceived as more meaningful: subjects reported relationships such as
chasing, following and hitting. Bassili speculates that the fact that animations in which the vector
components of motion were similar were reported as most meaningful suggests that grouping per-
cepts are important in specifying the nature of social interactions [Bas76].
Perceptual and Interpretative Properties of Motion for Information Visualization
23
Gibson established that when relative velocity is varied before and after an interaction observ-
ers perceive both causality and surface properties of the “objects” (e.g., hardness or softness)
[Gib76].
While many social psychologists profess a profound belief that motion plays a fundamental
role in social perception, (see [Kas81] for a review) the empirical evidence of which properties of
motion are the effective information carriers has not yet been established. In their experiment with
the animated triangles and the circle, Heider and Simmel were interested in how factors such as
temporal and spatial proximity, range, velocity and direction of movement contributed to impres-
sions about behaviour and its causes, but their experiment design was unsystematic and as a result
the data were intractable [Kas81]. Nonetheless, the most interesting findings were a) that move-
ment causes a perception of causality, later substantially explored and verified by Michotte, and b)
subjects readily anthropomorphized the objects and movements, “attributing all kinds of emo-
tional states, attitudes, motives and personality traits” to the objects [HS44]. Similar anthropo-
morphic interpretation was shown by Jetha’s experiment in which subjects mapped the motion of
individual abstract objects onto human dance sequences [Jet93].
Later, Braitenberg [Bra84] proposed that virtual “vehicles” directed by combinations of simple
stimulus-response excitation-inhibition functions could manifest psychologically credible animis-
tic behaviour. In an approach evocative of Braitenberg’s “synthetic psychology”, Lethbridge and
Ware [LW90] used simple behaviour functions based on distance, velocity and direction to give
the impression of complicated actions and interactions such as chasing, escaping, repulsion, colli-
sion and anticipation. They were concerned with achieving the impressions of intentionality and
“randomness” to the extent required for the perception of animacy without incurring the computa-
tional cost of stochastic parameters. They modelled seemingly random and intentional behaviour
of actors in an environment with stimulus-response functions calculating the velocity of an object
i at time t as a function of the positions of all the objects in the environment at times t-1 and t-2.
T1 functions determined object behaviour based only on positions of all objects at time t-1. The
only time-dependent variables used in T1 responses are distance and inter-object direction; a mul-
tiplicative parameter is used to control speed. These simple (linear) functions can model situations
where one object gravitates towards another, including collision, clinging, pushing, pulling, chas-
ing, escaping, attraction and repulsion. T2 behaviours consider t-1 and t-2 states, and can model
characteristic velocity, delay, momentum and anticipatory action.
Distance, velocity, inter-object direction, and temporal dependencies appear to be the major
contributing factors to perception of the nature of the interaction. When velocity is too slow, “all
impression of animacy is lost”. All compound motions and interactions were reported in anthro-
pomorphic, social terms, even when the motion itself exhibited “unnatural” behaviour (such as
abrupt changes in velocity) [LW90].
Psychologists, then, give us evidence for the low-level perceptual capabilities to identify
groups and certain interactions and relations; intuition and experience from these reported investi-
gations, simulations and the long history of movement in the performing arts as communication
confirm that movement, even of abstract entities, evokes powerful impressions of behaviour. What
remains to be established is whether these impressions and perceptions can be usefully manipu-
lated in a display environment to convey meaning about the information space.
Perceptual and Interpretative Properties of Motion for Information Visualization
24
6 Motion as a Display Dimension
6.1 Research Issues and Directions
My research is concerned with a principled approach to determining whether motion can be a
useful “channel” in information visualization and generally in user interfaces in complex systems.
To that end, I ask the following questions:
1. What are the salient perceptual features of motion? What are the emergent and behavioural
properties? Can they be “tuned” to influence/alter its meaning?
2. What do motions “mean”? Is there any inherent tendency to assign any semantic association
to types of motion? Can motion semantics be divorced from those of the moving object?
3. What is the coding granularity of motion? How many different motions can be used together
for coding without interfering with each other? What other modalities reinforce/countermand
the effects of motion?
Since we believe that effective decoding of a representation depends not only on mental econ-
omy but also its ecological validity we need to ask the additional question:
4. What can motion afford in the virtual ecology of the complex system interface, and how can
we best exploit these affordances?
It seems reasonable that both the perceptual and the interpretative properties of motion need to
be investigated together to understand what parameters relate to “meaningful” motion. We find it
useful to taxonomize motion’s potential as a dimension for communication according to the three
categories discussed in the previous sections: basic motion, interpretative motion and compound
motion. Under basic motion we are interested in evaluating which basic parameters (or kinetic
primitives) can be used to code information into simple motions. Interpretative motion studies
should lead to a categorization of possible qualitative types and which types are most meaningful
(can carry most information) under which conditions. Perhaps the most interesting area of inves-
tigation is that of compound motion to communicate the nature of relationships and linkages
between data elements which are visually separated. My research will address whether we can
derive useful constructs within this framework i.e., whether we can ascertain which basic charac-
teristics are salient to which types of motion, and how such types of motion may be useful in
ameliorating problems discussed earlier in this paper.
6.1.1 Basic Motion and Kinetic Primitives
Evidence from the reported areas indicates that the following may be considered as basic prop-
erties of motion: phase, velocity/frequency/rate/speed, periodicity (regular/ random?), trajectory
(oscillatory vs. directional, curved vs. linear), position (anchored vs. floating), continuity/smooth-
ness, size/spatial amplitude, transformation (rotation, translation, scale) and sustain/decay (the
persistence of the motion’s visual presence along its path). Little is known about the proximity
and similarity attributes of these properties. It will be fundamental to examine these to determine
the emergent features of motion and moving objects: two possible such effects are grouping and
causation.
6.1.2 Interpretative Motion
The type of motion pertains to its behaviour and affordances. (We note that in fact a complex
motion may consist of a combination of several types.) Interesting types include autonomic, nar-
rative/illustrative, expressive / intentional, inclusive, autonomous (the degree of autonomy such as
Perceptual and Interpretative Properties of Motion for Information Visualization
25
passive, caused, active, reactive), locomotive, signal/alert, viewing (manipulating viewpoint),
transitive/intransitive (i.e., having a direct or indirect effect on other objects), exertion (‘working”)
and “jostling”.
6.1.3 Compound Motion
Compound motion involves a combination of two or more movement sequences which elicits
the effect of a single perceptual and interpretative event, unlike simultaneous, similar motions
which may have the emergent features of grouping (see above). The key issues in compound
motion arise from both the characteristics of the individual movements and temporal and spatial
constraints (i.e. how far apart can they be in both space and time before the effect is lost?)
6.1.4 Properties and Types
Table 1 suggests potentially interesting features of basic, interpretative and compoundcom-
pound motion motion discussed earlier to be investigated in the context of this framework. One
key aspect of investigation must be combination/exclusion contingencies: to what extent can
properties of movement be used in more than one context: e.g., phase for both establishing groups
(observer-related) and for identifying aspects of the grouping relationship (object-related).
Table 1: Motion Properties and Types
Basic Interpretative Compound
Single object
Basic
phase
frequency/speed
transformation/direction
trajectory
smoothness/ continuity
duration / sustain
position
amplitude
velocity
shape/periodicity
temporal continuity
signal
active
viewing
“jostling”
autonomy
locomotive
expressive
exertion
Groups of Objects Basic
phase
frequency/velocity/speed
direction
duration
position
continuity
trajectory
size/amplitude
locomotive
exertion
expressive
autonomy
urgent
signal
relative velocity
relative trajectory
sequence
transition
filmic techniques
causation
attraction
repulsion
Perceptual and Interpretative Properties of Motion for Information Visualization
26
7 Potential Applications
Two great advantages of motion in a large and crowded display environment are its perceptual
efficiency across a wide area and its compact use of screen real-estate and resources: it does not
necessarily increase the density of the display. While extensive studies are required to establish
the conditions of appropriate usage, we believe that motion holds great promise for improving
visualization and user interface comprehension in the following six areas: most importantly, in
annunciation, grouping and integration, and visualizing data relationships.
7.1 Annunciation and signalling
A key issue in supervisory control system interfaces is annunciation: how to ensure that users
notice, comprehend and respond appropriately to alarms and system messages in a reasonable
response time. In a dense display environment where multiple alarms and signals are concurrently
active the user’s visual system becomes overloaded and alarms are often missed. We have previ-
ously discussed what Woods calls cognitive tools [[woods84]] for selectively directing attention
(see Section 2.2.1). We anticipate that motion will prove effective as such a cognitive tool. Since it
appears that velocity and amplitude map somewhat intuitively to “urgency”, we anticipate that
motion can be tuned to represent alarm priority. Because smooth motion is much less disruptive
than blinking (see [WBKC92]) the potential exists to gracefully draw the users’ eyes to more
important areas without disturbing the focus of attention on less important elements by coding the
more important alarms with higher frequency motion.
7.2 Grouping and integration
Psychological evidence indicates that the perception of groups is a natural emergent feature of
multiple similar motions. We predict that this use of motion may prove invaluable in fostering the
immediate recognition of associated elements which may be widely scattered across the visual
field. Other display dimensions such as colour and labelling are ineffective in such a broad area
and tend to be already over-used.
7.3 Communicating data relationships
Current static graphical visualization techniques are ill-equipped to display dynamically shift-
ing relationships between data elements. There is, for example, no seemingly intuitive way to rep-
resent causality, dependencies or even simple sequences without creating new, separate
representations with additional abstractions and descriptions. The results from the Michotte
[Mic63], Kassin [Kas81] and Heider et. al. [HS44] studies suggest that compound motion holds
great promise for meaningfully and efficiently portraying certain relationships “in place”; that is,
combining the movements of separate elements in their existing displays and representations in a
way that elicits the immediate perception of how the data are related.
7.4 Data display and coding.
There is some evidence that aspects of motion such as phase can be used in a limited fashion to
map data values in the same way that point size and colour saturation are used [WBKC92]. How-
ever, the obvious application is representing dynamic data such as traffic on a link or flow through
a system. Examples include communications traffic in telecommunications, rate of production
and flow in mining and petrochemical conduits and line load in power distribution.
Perceptual and Interpretative Properties of Motion for Information Visualization
27
7.5 Representing change.
It is important to convey not only the fact that change has occurred in a timely fashion but also
the nature and rate of that change, Our visual sensitivity to the continuity, or “smoothness”, of
movement and to changes in its frequency and amplitude suggest that we can efficiently and intu-
itively communicate change by simply varying these parameters, thereby changing the qualitative
nature of the motion. For example, we could animate a data representation such as a text element
to convey that it had recently changed and change the nature of the movement to indicate to what
degree it had done so.
7.6 General visibility concerns
Consider for data that there are two levels of “representational state”: one to do with meaning
and direct content (qualitative, quantitative value or state, relative to other data), and one to do
with the “display” or “mediated” state of the information. For example, is it currently visible? Is it
occluded, or outside the screen “portal”? Is it currently undisplayed but available (i.e., not explic-
itly excluded by the user) or has it been filtered out? Display state is a combination of size, colour,
location, neighbourhood density/display density, and shape/form.
We believe that motion may prove useful in manipulating the display configuration (viewpoint)
to draw attention or at least perception to the desired area. In the ecological sense, the user is
“walked around” to see information of note. Motion which is used to disambiguate 3D structures,
smooth transitions and perceptually group data is related to the display state rather than to basic
meaning. “Jostling” windows or otherwise animating icons to indicate where information may
be hidden is one potential example.
8 Implementation Issues
8.1 Perceptual Artifacts
Sekuler [STK81] identifies two confusing and contradictory artifacts of motion perception
which must be avoided in temporal displays.
The Motion After-Effect (MAE) occurs after constant observation of a moving pattern for 15
seconds or more. If the motion suddenly stops, the pattern will seem to move slowly in the
opposite direction. The MAE arises only if the stationary pattern is on the same part of the
retina as was the moving pattern; an eccentrically viewed MAE appears faster and lasts
longer than one in the center of the visual field. It can be cancelled by a small counter-
movement prior to the “real” cessation of motion.
Induced motion is the effect which one set of moving objects exerts on the perceived veloc-
ity of another set of moving objects (e.g., a standing train which appears to be moving
when the train beside it moves). The perceived speed of an object is reduced if surrounded
by faster moving ones and increased if surrounded by more slowly moving ones. A moving
frame containing a stationary dot gives the impression of the dot moving. In cases where
the relative velocity of objects is a meaningful dimension mechanisms must be investigated
to annul this effect.
Braunstein reports on the related effect of motion parallax in which objects which move faster
appear to be closer, even in a two-dimensional display [Bra90].
Perceptual and Interpretative Properties of Motion for Information Visualization
28
8.2 Real-Time Display Requirements
Apparent motion is the illusion of continuous motion resulting from the momentary presenta-
tion of objects in orderly locations on the visual field, which is, of course, how discrete frames are
perceived to link into movement sequences. The key issue is the required temporal resolution.
Differences of 200 msec or more cancel apparent motion [STK81]. “Smooth” motion, however,
requires 12-14 frames a second, which we will use as our base requirement of “real-time” per-
formance. (Video resolution is 30 frames/sec: film, 24/sec). Most computer workstations have 60
Mhz interleaved displays: alternating halves of a frame, or “fields”, are refreshed every 16.67
msec. The challenge in using motion as a display dimension is to guarantee that sufficient tempo-
ral resolution can be maintained to reliably elicit the desired perceptual impression, and to ensure
the correct synchronization of movements. Operating systems such as UNIX and NT offer only
weak support for real-time programming but we anticipate that the combination of current graph-
ics display capabilities and proper use of multitasking will satisfy the temporal resolution require-
ment. Of potential interest is the approach taken in the ArtKit animation toolkit [HS94], which
uses an animation dispatch agent to synchronize animation steps with the redraw cycles.
Animation research has concentrated on veridical motion: realistic, believable simulations of
the motion of complex articulated figures which are based on either dynamics, motion capture or
procedural models of movement. (The reader is directed to [FvDFH90] for a discussion of com-
puter animation.) Dynamics are based on the physical principles of forces and mass, and while the
motion produced reliably creates physically credible sequences, the calculation is extremely com-
putationally expensive, involving numerical solutions of large sets of equations which cannot be
executed in real time. Forward kinematics, on the other hand, in which only the geometric and
movement properties are specified, can be solved in real-time. The evidence that humans employ
kinematic rather than dynamic principles in perceptual operations [CM93] encourages the feasi-
bility of this approach.
Lethbridge and Ware’s experience with their system of behaviour functions is an effective
example of how believable motion and interactions between sets of objects can be simulated using
simple sets of partial response equations. They report that calculating the state of the environment
at each time step is of complexity where n is the number of objects in the environment.
Real-time performance with simple geometrical objects is easily obtainable, although they do not
know whether the approach is extensible to animating articulated figures with many more degrees
of freedom.
Film techniques such as dissolves, motion blur and slow-in, slow-out involve 2nd and 3rd order
continuity of motion [Las87]. Chang and Ungar [CU93] achieve these effects in real time using
colour table animation, in which the colour space is divided into separate colour maps which can
be used to cycle through representations. The resulting reduction in available colours was not a
drawback to display resolution since they were portraying user interface objects rather than con-
tinuously varying data values. In systems where continuously varying colour is used as a display
dimension, colour table animation may not be a reasonable technique, and we must consider other
options.
9 Conclusion
We believe that motion holds great promise as a dimension for displaying information in user
interfaces to complex systems because it is perceptually efficient, interpretatively powerful and
currently under-used. Of great interest is its potential to intuitively represent data relationships
and higher-order system behaviour which static graphical methods cannot. However, little knowl-
On
2
()
Perceptual and Interpretative Properties of Motion for Information Visualization
29
edge exists to guide its application in information display. This paper summarizes types of move-
ment characterization from diverse disciplines and proposes an initial taxonomy of motion
properties and application to serve as a framework for further empirical investigation into motion
as a useful display dimension. Potentially “codable” properties of motion are identified from per-
ception research. A higher-level categorization of motion types is drawn from a review of inter-
pretative movement. There is evidence of qualitative differences in the motion of a single object
as opposed to the combined motions of several objects. An ecological perspective is used to antic-
ipate the applicability of different motion types to different uses Finally, implementation issues
are discussed with respect to perceptual artifacts which must be avoided and to minimum require-
ments for temporal resolution, perceptual synchronization and animation techniques.
Perceptual and Interpretative Properties of Motion for Information Visualization
30
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... Motion is also useful in scientific visualization [35], as the processes visualized often involve the dimension of time [22]. Very early, Bartram started investigating motion as an "abstractly codable dimension in its own right" [3], a direction explored in other projects [4,5,39,40], and in which we situate our own work. ...
... Animated versions of the examples shown here are available in the companion video and Website. 3 For the sake of clarity, we selected very small data subsets, which lend themselves better to static representations for inclusion in the paper. As stated earlier, motion variables should not be seen as systematic replacements for other visual variables such as color and stroke width, but rather as alternative visual variables that widen the space of possibilities and have their own strengths and weaknesses. ...
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... However, this is not so. In her doctoral thesis, Bartram (2001) collects and expands on the subjects presented in her technical report (Bartram, 1997a). She starts from Baecker and Small (1990) to consider motion as an information display modality in its although little information was offered to justify this incorporation. ...
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... if they move together. Bartram et al. [6], [7], [8] characterized motion as a unique display dimension with substantial potential for its perceptual efficiency and interpretative richness. She performed several studies to better understand effective motion coding for information-rich interfaces, showing that motion coding can be used as a visual coding attribute, and that it does not interfere with existing color and form coding. ...
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... in its own right" [15], a direction explored in other projects [16,17,98,99], and in which we situate our own work. ...
Thesis
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... While techniques such as Gapminder are popular, the value of animated displays compared to static one (such as small multiples) is still unclear [Rob+08]. In fact, because of its strong perceptual draw [Bar97b], animation might prevent users from perceiving other elements of the display. However, it also offers unique opportunities to encode complex and subjective information such as convey musical impressions or Human moods and feelings. ...
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