Information Interaction: Providing a Framework for
Information Architecture
Elaine G. Toms
Faculty of Information Studies, University of Toronto, Toronto, Ontario, Canada. E-mail: [email protected]
Information interaction is the process that people use in
interacting with the content of an information system.
Information architecture is a blueprint and navigational
aid to the content of information-rich systems. As such
information architecture performs an important supporting role in information interactivity. This article elaborates on a model of information interactivity that crosses
the “no-man’s land” between user and computer articulating a model that includes user, content and system,
illustrating the context for information architecture.
Introduction
How people interact with information-rich digital environments is directly influenced by the environment’s information architecture. The quest for information is carried out
through querying and browsing, but also represents situated
action and reflects the experiences that one has in interacting with an information system. This integrated process is
information interaction.
Information architecture, on the other hand, is a map of
the underlying information structures. It was defined somewhat simplistically by Davenport (1997) as “simply a set of
aids that match user needs with information resources.”
Rosenfeld and Morville (1998) popularized and operationalized the concept, and use it to denote a blueprint for
information organization and access for Web sites. In its
most abstract sense, information architecture provides “a
structure or map of information which allows others to find
their personal paths to knowledge” (Wurman, 1996). In
essence, it enables access to content by providing a systematic and primarily a visual approach to the organization of
content and thus facilitates the quest for information.
This article articulates a theory of information interaction
illustrating how information architecture along with other
components contributes to the information interactivity in
an additive way. The emphasis, however, is on relationship
between the information architecture and information interaction.
© 2002 Wiley Periodicals, Inc. ● Published online 14 May 2002 in Wiley
InterScience (www.interscience.wiley.com). DOI: 10.1002/asi.10094
Understanding Information Interaction
Information Interaction’s Roots
Traditionally, the quest for stored information centered
around scanning tables of contents, back of the book indexes, and various types of bibliography. With the advent of
the computer the process became query-driven; commandline systems demanded complex sometimes obsequious
syntax, intended for execution and manipulation only by an
expert intermediary. Graphical user interfaces simplified the
process by making visible many of the options buried in
command and code. CD-ROM encyclopaedias, in particular, with their rich content supplied resourceful indexes,
providing users with several pathways to the content—
novel (at that time) options to a formal query. It is the Web,
however, that turned the quest for information into an “experience” and into a richer process than that previously
entertained for information tasks. Today, people do not
simply search for information; they immerse themselves in
a body of information.
Information Tasks
An information task is “the manifestation of an information seeker’s problem and is what drives information seeking actions” (Marchionini, 1995, p. 36). Marchionini deconstructs the quest for information into a series of procedural
subtasks, such as define problem, select topic or source,
investigate the topic, and so on, and includes as well the
human behaviors of interacting with an information system.
Traditionally, the user starts an information task by specifying a set of search terms (querying) or recognizing in a
list something that is directly or indirectly associated with
the goal (browsing). An information task is generally perceived as goal-driven (e.g., Kulthau, 1991; Wilson, 1981)
with an assessment of relevance as a termination or as an
interim feedback mechanism. This problem-solving process, whether it is stimulated by the need to reach a goal or
the recognition of an anomalous state of knowledge (Belkin,
1984), is a traditional work-oriented perspective that is
JOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE AND TECHNOLOGY, 53(10):855– 862, 2002
imposed on information tasks. It ignores the concept of
chance encounters (Toms, 2000b), information encounters
(Erdelez, 1997), or serendipitous retrieval (Toms, 2000a), or
the range of Web user behaviors observed by Choo, Detlor,
and Turnbull (2000).
The Impact of the Web on the Information Task
User behavior on the Web is influenced by the functionality of the Web browser software (Choo, Detlor, & Turnbull, 2000). Thus, while the nature of information tasks may
not vary significantly (at least in higher order tasks) from
pre-Web to Web environments, the architecture of the Web
enables multiple iterative types of interaction that were
previously impossible or awkward or tedious. Prior to the
Web, many of the techniques used to complete a task were
not integrated within the same system, and required different user abilities and skills. For example, compare, pre-Web
and Web, how a book was and is identified and located,
whether from a bookstore, a publisher, an author’s preprint
or a library.
Information tasks can be classed according to Hoppe and
Shiele’s (1992) two groups: device-independent tasks and
device-dependent tasks. Information tasks of the first type
are conceptual and analytical, while the latter are those that
need information appliances to resolve the problem. At one
time the range of microtasks needed to solve a single
information problem varied sometimes quite significantly
from device to device; today, the Web has evened the
playing field. Now (speculatively), it is the individual differences of the user and the quality of the information
architecture (among other features) that determines the success of the information interaction. The Web has made the
quest for information nearly device-independent.
Information Task as User Experience
Laurel (1986) argues that “the interface is a form of
artistic imitation: a mimesis.” She compared the interface to
a play: the purpose of a play is to induce the emotional and
rational engagement of the audience and similarly, the interface must rationally and emotionally engage the user for
satisfactory resolution of the goal. The form of an object
engages the user and enables the end; content alone is not
sufficient. Laurel further posits for the primacy of the experience and of the action as the object of representation.
Typically, we define the computer as tool or intermediary,
and the interface objects as surrogates for programming
code. The task in this interpretation, thus, becomes subservient to the technology and the user is robbed of the experience. Laurel’s now 15-year-old perspective is evident in
interaction on the Web.
Nardi and O’Day (1999) likewise attest to the need for
engagement and participation within an information ecology—“a system of people, practices, values, and technologies in a particular local environment.” They, too, focus not
on the computer as a tool, but on the relationships among
856
the elements of the system. The parts must be complementary and understood in terms of social values and polices
and not just as tools and tasks.
The notion of user experience as discussed by Laurel
(1986) and Nardi and O’Day (1999) as a driving force for
interface design emerged as a popular concept in development for the Web, primarily from the business and marketing development sector who were long used to providing
customer experiences in shops. User experience defines how
user choices and actions are incorporated into the system,
and how the activities of the system are represented and
presented to the user. Laurel (1986) calls this “personness”
and suggests that it includes both the systematic and aesthetic approaches to create representations that support task
completion. The Web has metamorphosed from the preWeb text-based Gopher-structures and from the videotext
systems of the 1970s into a montage of rich visual and
semantic cues that sets the stage for user experiences. It is
within this rich environment that information architecture
has an essential supporting role in the information interaction. The Web is not just a single one-way channel of
controlled content but a tapestry of rich experience in multiple ecologies (Nardi & O’Day, 1999).
Foundation of Information Interaction
Information interaction is a complex process that integrates aspects of the user, the content, and the system that
delivers the content to the user. There are many theories that
could be applied to information interaction. Many are
clearly single object models (Nielsen, 1990). Most describe
only the affective or behavioural characteristics of the user
(e.g., Ellis, 1989; Kuhlthau, 1991) or only the conceptual or
procedural processing of the system (e.g., Tague, Salminen,
& McClellan, 1991; van Rijsbergen, 1979). Many are limited to query-driven information systems (e.g., Marchionini,
1989). None of these focus on the interaction (Saracevic,
Mokros, & Su, 1990), and few acknowledge the presence of
the user within this process (Beaulieu, 2000).
The ideas generated by Bush (1945) in his concept of the
memex seem to be lacking in formal paradigms of today.
Perhaps new approaches to the information quest may generate innovative conceptual frameworks such as Pirolli and
Card (1999)’s foraging theory, yet even it assumes user as
an automaton. In cognitive psychology, there has been a
shift from viewing people as “general-purpose computational systems” to viewing them as “adaptive and adapted
organisms whose whole computational mechanisms are specialized and contextualized” to a particular environment
(Medin, Lynch, & Solomon, 2000). Current models have
not embraced this notion. Although one might speculate that
typical models of human– computer interaction (e.g., Norman, 1986) have direct application, these models are not a
perfect fit.
First, the complexity of information interaction is not
well expressed in typical models of human– computer interaction. The range of tasks in general supported by computer
JOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE AND TECHNOLOGY—August 2002
systems extend from routine tasks to problem-solving tasks
that require extensive backtracking and digressions (Simon
& Young, 1988). In predictable task-driven systems the user
interacts with the system’s implementation of the task.
Examples include making cash transactions, monitoring a
power plant’s operations, and playing computer games. In
systems that support information seeking, each action taken
is the result of a set of intricate decision points (Simon &
Young, 1988). As suggested by Simon and Young (1988)
and Toms (1997), such an unstructured, complex problemsolving task takes place in an interactive, user-controlled
environment, and cannot be reduced in a predictable way to
a set of routine Goals, Operators, Methods, and Selections
(GOMS), which is based on a model human information
processor (see Card, Moran, & Newell, 1983, or Olson &
Olson, 1990, for an explanation of GOMS). Although
GOMS has been applied to the information task by Carmel,
Crawford, and Chen (1992), GOMS best represents routine
tasks with highly predictive behavioural patterns (Carroll,
1997; Simon & Young, 1988)—a pattern that the typical
information seeker does not have.
Second, the information representation—the information
architecture and the information it represents—is subsumed
by the system within models of human– computer interaction (McKendree, Reader, & Hammon, 1995). This is a
serious omission for the model of a process characterized by
users immersing themselves with information. Belkin
(1993) and Toms (1997) are among the very few who
recognize the importance of user–text interaction in the
information retrieval process, and to suggest that a user’s
interaction with the information representation is, in fact,
the central phenomenon. Human– computer interaction
models have a long history of application in transactionbased systems, and have yet to be adapted to informationrich systems.
Modeling Information Interaction
The interpretation of the process of information interaction in Figure 1 is derived from Toms (1997) model of
browsing, which is turn, is a variation of Guthrie’s information location model (Guthrie, 1988; Guthrie &
Mosenthal, 1987), a model with its roots in analogical
reasoning (e.g., Gentner & Rattermann, 1993), and in models of human problem solving (Newell & Simon, 1972;
Simon, 1978). Although the information interaction model
could be described according to either of the threads that are
physically represented by the layers in Figure 1, the view
described here is from the perspective of the user (rather
than the content or the system).
In information interaction, users are likely to perform
several iterations of the process before terminating the session. They either initiate the process by formulating a goal,
i.e., the traditional information seeking process, or simply
by making a decision to examine a body of information. In
either case, a category such as a menu, is selected. The user
scans the text, although it may be graphical as well. When
FIG. 1.
Model of information interaction.
a cue is noted, the user stops to examine the text, and may
or may not extract and integrate the information. The user
may recycle in multiple, nonlinear ways through category
selection, cues, and extraction. This process can be viewed
as a series of state transitions in which each state represents
the interests of the user at that particular moment in time
(Kok, 1991). Thus, the same set of items could be presented
to the user, but different choices might be selected at different times. The state of the user changes with time; a
single instance is unlikely ever to be the same for the same
person or for different people. Each of these stages are
briefly described in the following subsections.
Formulate Goal
A goal is defined as the object or purpose of the quest. It
is the user’s intention and may range from a precise, welldefined purpose to an imprecise, or ill-defined purpose.
There are many theories that explain why a person seeks
information such as Dervin and Nilan’s (1986) sensemaking
approach, Belkin’s (1984) anomalous state of knowledge,
and Bates’ (1989) berry-picking approach. However, a decision to initiate a quest for information need not be goalbased (Toms, 1997) as evidenced by, among other processes, Web surfing. Users do not always have explicit goals
such as “look for information about . . .” or “learn something about . . .” Tague-Sutcliffe (1995) suggests that “[i]nformation has become like the air we breathe, so pervasive
JOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE AND TECHNOLOGY—August 2002
857
that we scarcely notice its existence and yet so essential that
we cannot live without it.” Like the basic physiologic need
for food and shelter, users seem to be driven by a need to
know— by a natural curiosity about their environment and
the world in which they live— but not necessarily because
of a conscious admission of a void. Thus, as illustrated, an
explicit goal may not always be present.
Select Category
The user selects a category (or a search term) that is one
of two items: an object of meta-information (Belkin, Marchetti, & Cool, 1993) such as a menu or index, and/or a term
from that meta-information. Guthrie and his colleagues consider category selection equivalent to choosing from the
structure of the text, for example, selecting the appropriate
page, chapter, or subsection that contains the needed information (Guthrie, 1988; Guthrie & Mosenthal, 1987). In
more recent work, category selection was defined in two
ways: the method of accessing the system, i.e., deciding
how to approach the problem, and selecting a term or
concept (Dreher & Guthrie, 1990; Guthrie, Weber, & Kimmerly, 1993). Guthrie (personal communication, June 28,
1995) elaborated that for users to properly select a category,
they must: (a) know the organizational structure of the
document; (b) know what the category of information is
called; and (c) know something about the category’s contents. The first one is defined as procedural knowledge and
the last two as conceptual knowledge (Byrnes & Guthrie,
1992). Thus, a user may choose a type of meta-information,
if more than one is available, and/or choose more narrowly
within that meta-information. How people interpret concepts and categories is a rich area of inquiry (see, e.g.,
Medin, Lynch, & Solomon, 2000) that impacts how those
underlying categories are presented to people.
Note Cues
Cues play a key role in information location (Toms,
1997), an aspect not identified by Guthrie. These cues serve
as landmarks that influence the direction a user takes in
scanning information. Selected words or phrases embedded
in the text cause a searcher to examine a segment of text.
This is an extension of the definition used by Heffron,
Dillon, and Mostafa (1996) and suggests the existence of
“affordances” (Gibson, 1977) in the text (Toms, 1997,
2000b).
The concept of cue as landmark is derived from the
retrieval cues used to access information in long-term memory (Collins & Loftus, 1975), the signalling devices of text
(Lorch, 1989), the structure of hypertext documents
(Nielsen, 1990; Simpson, 1989), the links in hypertext documents (Happ & Stanners, 1991; Vora, Helander, & Shalin,
1994), and the cues used by indexers and abstracters (Farrow, 1991; Jones, 1976, 1983). For example, Kwasnik
(1992) noted transitions, movements (e.g., shifts of focus),
and pauses in her study of browsing. There is some evidence
858
to suggest that signalling devices are used in information
searching (Hartley, 1983). In particular, Valdez, Chignell,
and Glenn (1988) assessed the relationships between 30
terms for their “landmark quality,” a combination of connectedness and memorability. Textual cues tend to draw the
user’s attention to a section of information.
More recently, the concept of information as shape has
been explored (Dillon & Schaap, 1996; Dillon & Vaughan,
1997) and the way that user exploit shape in the recognition
of document form (Toms, Campbell, & Blades, 1999).
Shape too serves as a powerful cue in influencing how users
access, interpret, and use that information.
Extract Information
When a change in the system state is identified by the
user, the user observes two items: a change in the node of
information displayed, and an adjustment (if applicable) in
the state of the interface. The user may navigate within the
information node almost without direct attention to interface
objects. In this case, the user distinguishes between interesting or pertinent information and irrelevant or uninteresting information and extracts only the relevant details (Dreher & Guthrie, 1990). If nothing is relevant in a particular
section, the user must reject the section expeditiously and
move on (Guthrie, 1988).
Integrate Information
Information that has been extracted is integrated with
information previously known (Guthrie, 1988). The more
specific the search goal, the less extraction and integration
will be required (Armbruster & Armstrong, 1993). This
component is instrumental in assessing a user’s confusion
and disorientation (Guthrie, 1988). If a user returns to the
same section of information, it means that the user failed to
integrate all the information initially, or alternately that the
system failed to provide adequate support. Sometimes the
visual cues might be over-riding the textual cues for example.
Evaluate
In essence, users are constantly questioning: is this content, menu and so on useful? Guthrie (1988) maintains that
users recycle through the components until the goal is met,
a result he describes as a “best fit” rather than a perfect
match, a view that is diametrically opposed to standard
information retrieval evaluation, i.e., the quest for perfect
precision. Yet, clearly, users have subgoals and continue to
make evaluative decisions throughout the process (Belkin et
al., 1993; Kulthau, 1991; Marchionini, 1995).
Evaluation is too often inextricably linked with classic
information retrieval metrics—precision, recall, fallout, and
so on (e.g., Tague-Sutcliffe, 1995). Paradoxically, the fact
that a system delivers what has been requested of it does not
JOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE AND TECHNOLOGY—August 2002
TABLE 1.
Research theories that inform information interaction.
Object/Interaction
Theory
Source
User
Schema theory
Memory Models
Rumelhart & Norman, 1988; Alba & Hasher, 1983
System
Database theory
Information retrieval models
Ullman, 1988; Date, 1990 among others; Salton & McGill, 1983; van Rijsbergen, 1979
Content
Classification
Categorization
Text production
Text signalling devices
Shera, 1965; Ranganthan, 1937; Foskett, 1996; Lakoff, 1987; Rosch, 1975; Roth &
Shoben, 1983; Medin, 1989; Kintsch & van Dijk, 1978; Lorch, 1989
User-System
Human-computer interaction
Norman, 1986, 1991
Content-System
Menu design
Hypertext
Electronic Text
Norman, 1991; Dillon, 1994; Kerr, 1986; Woodhead, 1991; McKnight, Dillon, &
Richardson, 1991
User-Content
Text comprehension
Information Search
Skimming
Colley, 1987; Meyer, 1984; Guthrie & Kirsch, 1987; Guthrie, 1988; Masson, 1982,
1985; Rothkopf, 1971
necessarily mean that the results meet the user’s needs and
are able to satisfy the requirements of the task.
The Role of Information Architecture in
Information Interaction
Three objects serve as the foundation for the model of
information interaction: User, System, and Content. Users
bring to the process their human information processing
capabilities that aid them in translating intention into actions, and in interpreting both system output and informational displays. The system, a set of dynamic computer
processes, contributes its artificial information processing
capabilities that parse and interpret keyboard commands,
perform operations, and respond to input. The content or
knowledge representation is a blueprint that contains a
series of words, phrases, sentences, or paragraphs, hierarchically organized, and contained within a logical superstructure.
In information interaction, a user interacts with a system
to examine an information blueprint, analogous to traditional reader–text interaction established in a printed-paper
world. This is impacted by the system’s management of the
content and the system’s ability to communicate with the
user. The system, user, and content interact synergistically.
In addition, user, system, and content are also viewed as
a series of two-way interactions:
(1) user–system interaction in which the user communicates with the system via a two-way connecting information flow that spans the “gulf of execution” and the
“gulf of evaluation” (Norman, 1986), separating user
from system;
(2) system– content interaction, which is in essence the
result of applying a set of computer processes to the
microstructure and macrostructure of the text to provide
access, storage, and update facilities; and
(3) user-content interaction, i.e., reader–text interaction, oc-
curs between the visually processed text and the activation of existing user knowledge.
This abstraction is derived from and informed by multiple theoretical constructs as indicated in Table 1. Information interaction takes place at the confluence of these objects
and interactions (see Fig. 2). It is influenced by the user’s
cognitive functions, the semantics and structure of the content, and the characteristics of the system. Users work with
the content, users manipulate the system, or are manipulated
by it, and the system facilitates access to the content. The
object of primary interest to this document is Content,
which includes two structures: information architecture, and
information design (the latter is not discussed here).
FIG. 2.
An instance of information interaction.
JOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE AND TECHNOLOGY—August 2002
859
Information Architecture
Information architecture includes a system of classification, labeling of concepts within that classificatory structure,
navigation, and search/access systems for a defined body of
information. It has its roots in theories of classification and
the organization of knowledge (Foskett, 1996; Ranganthan,1937; Shera, 1965), in categorization (Lakoff, 1987;
Medin, 1989; Rosch, 1975; Roth & Shoben, 1983), and, in
menu design research (Norman, 1991; Paap & Cooke, 1997)
and hypertext navigation (McKnight et al., 1991; Woodhead, 1991).
At its base is a classificatory scheme that specifies
classes and subclasses, each of which are hierarchically
ordered so that each class shares the same/similar attributes
and characteristics. In an ideal world, each class represents
a distinct concept with discriminating and unambiguous
labels and with controlled lexical relations: synonymy,
homonymy, polysemy, metonymy, hyponymy/hypernymy,
meronymy, and antonymy. Fundamentally, this is typical
menu design for information retrieval systems (Giroux &
Belleau, 1986; MacGregor & Lee, 1987), but with roots in
the traditional organization of knowledge, cognitive psychology, and human– computer interaction.
Information retrieval menus tend to represent the key
topics or categories of information. But, a body of information may be organized in many different ways: by formal
organizational structure, by function, by individual interest/
need, by task, by expertise, by chronology, by frequency of
use, or by spatial orientation. Each of these reflects a different pathway to the underlying content. In addition, the
framework may be physically represented as hierarchical or
tree structures; or as cyclic/acyclic networks that provide
multiple and pseudoparallel pathways to the same content.
These lists may be presented in a textual and/or graphicenhanced list, as an abstract visual representation of the
structure, for example, a sitemap, or as a map of the organization (Shneiderman, 1998).
An information architecture specifies navigation: how
course (how the structure is navigated) and position (location within that structure) are indicated. In addition, it
determines other types of access tools such as site maps,
FAQs (frequently asked questions), search tools, and indices (Rosenfeld & Morville, 1998).
Mapping Information Architecture to Information
Interaction
The confluence of the objects illustrated in Figure 2
represents, abstractly, information interaction. The bottom
portion of Figure 2, a subset of the model in Figure 1,
identifies the components that are directly affected by the
information architecture. The generation/evolution of goals
(when applicable) is a cognitive process that initially might
not be affected by the information system. Similarly, integration and evaluation are outcomes of information interaction and are also cognitive processes—solely characteristic
860
of the user and not of the complex interaction of user,
content, and system. The success of the remaining three
components depends on the effectiveness of the information
architecture.
The identification of a “category” may be the selection of
a tool such as a menu (Dreher & Guthrie, 1990), a keyword
or concept from an index, a title from a list, and so on. The
“textual cue” is a word, phrase, or concept identified within
that “category selection” that acts as a stimulus influencing
the user’s focus (Toms, 1997). This is primarily a perceptual
activity, but is dependent on the structure of the information
architecture. “Text extraction,” a conceptual activity, is the
extraction of a pertinent piece of information from the
current object in focus. This may be the extraction of a
useful word, phrase, article headline, component of a piece
of text, but in essence is the processing of the microstructure
(Guthrie & Kirsch, 1987). Each of these three components
are stimulated by and result from the information architecture, which establishes the categories at both the macro- and
microlevel, and which creates a structure the enables the
recognition of cues. If all work synergistically, then the user
can extract useful information. Thus, if the information
architecture is effective, the user should easily recognize the
connection between the text extracted and user’s selfknowledge (otherwise, there is a poor usability problem
associated with the information architecture).
Conclusions
Information architecture is a blueprint for the information system content in Web sites or other information-rich
systems. As such, it contributes significantly to the information interaction—the way that a user interacts with the
content of a Web site. This article has articulated a model of
information interaction that, for the information task,
bridges the divide between human and computer coined by
Norman (1986), and the split between information behavior
and information retrieval highlighted by Saracevic (1999).
The model illustrates how the process of information interaction is affected by three objects: the user, the system, and
the content. Information architecture, which provides a
blueprint to the content, plays a significant role in effective,
efficient, and satisfying information interactivity.
Acknowledgments
This work was funded in part by the Natural Sciences
and Engineering Research Council Canada. The author
thanks the anonymous reviewers for their insightful comments.
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