Trends in Human-Computer Interaction in Information Seeking

White Papers Trends in Human-Computer Interaction for Information Seeking

Trends in Human-Computer Interaction for Information Seeking:
What’s Next?
Rich Miller, Research Scientist, LexisNexis

Abstract
This paper describes a conceptual foundation for integrating new technologies into the next
generation of user interfaces for information seeking. The conceptual foundation consists of
three primary components that may be used to identify opportunities for using new
technology to enhance Human-Computer Interaction: 1) a framework for thinking about
information seeking behavior, 2) a vision of information access and organization, and 3) a
set of the most significant trends and technologies expected to shape future user
interfaces. Taken together, this information can be used to create effective next-generation
user interfaces.

Introduction
The world of human-computer interfaces is on the verge of significant change. Many
consider current user interfaces obsolete, and a swarm of new technologies and computing
trends have matured to become significant factors in Human-Computer Interaction (HCI).
The challenge for product designers and developers is to integrate the most useful
technologies in a way that allows users to take advantage of their power while maintaining
a high level of usability. This paper focuses on HCI as it relates to online information
seeking.

When the now-predominant WIMP (windows, icon, mouse, pointer) interface was
introduced in the early 1980s, it was revolutionary. Today’s user interfaces as a whole are
not significantly different from those in the beginning of the WIMP era, but there is a
growing need for new, more effective interfaces. The main reason cited for this is the
tremendous increase in the volume of the information and tools that users are required to
manage. For example, the first Macintosh (which represented the WIMP interface entering
the mainstream) had no hard drive and was not likely to be networked. Now it is common
for a new computer to come with a 60G hard drive and be networked to a world full of an
endless supply of data. In addition, there is a plethora of emerging technologies that can be
applied to user interface solutions.

A Framework For User Behavior
Before considering how a given new technology or trend can enhance information seeking,
it is useful to have a framework containing the critical components of user behavior that
may be used to map user behavior and needs to potential solutions.

Process-oriented model: A great deal of research has addressed information seeking.
The process-oriented model based on an electronic information seeking process defined by
Marchionini (1995) and shown in Figure 1 will be used as the foundation for the information
seeking model. Marchionini’s model has been adapted here to include the concept of
organizing information, expected to be important in the future of increasingly more available
information.

2002 Interactive Media Forum 1

Trends in Human-Computer Interaction for Information Seeking White Papers

Figure 1—Process-oriented model of information seeking.

Activity-based model: The LexisNexis Human Factors group (1997) defined six separate
information seeking activities that address user goals. The appendix lists the six activities
and related user goals (Bayer, 2000). Figure 2 shows the relationship between these
activities and the process model introduced earlier. While some activities involve the entire
process, others deal with a subset of the steps.

Thorough/exhaustive research

Quick & dirty research

Get a specific document

Validate/Verify specific information

Continuously track specific topic/issue

Keep current on general topic of interest

1. Recognize and 2. Define and 3. Choose a 4. Formulate a 5. Execute a 6. Examine results 7. Extract and 8. Check for
accept and understand the search system, query search integrate completion and
information problem problem source information deploy information

Figure 2—Process+Activity-oriented models of information seeking.

Previous research in information seeking behavior can be mapped to this framework. The
information seeking strategies and tactics shown in Figure 3 were collected from studies on
information seeking behavior (Marchionini, 1995; Kuhlthau, 1988, 1991; Ellis, 1989; Bates,
1990; Chun Wei Choo et al., 2000). This integrated view of user behavior can be used to
identify opportunities for enhancing information seeking products. The framework can help
determine how to enhance HCI by considering to what extent a given technology affects
various steps and activities. For example, speech recognition may be more appropriate for
behaviors that involve simple query formulation (Step 3), but not for activities associated
with Step 6 (Examine Results) that tend to be more visual in nature. This model may also
be used to identify what is still unknown about user behavior.

2 2002 Interactive Media Forum


Thorough/exhaustive research

Quick & dirty research

Get a specific document

Validate/Verify specific information

Continuously track specific topic/issue

Keep current on general topic of interest

1. Recognize and 2. Define and 3. Choose a 4. Formulate a 5. Execute a 6. Examine results 7. Extract and 8. Check for
accept and understand the search system, query search integrate completion and
information problem problem source information deploy information

- Scanning
- Navigational - Collecting Nuggets

- Web search engines
- Successive fractions
- Differentiating - Building Blocks
- Networking
- Chaining
- Citation Chasing
- Choose subscription service - Pearl Growing - Narrow v. Broaden
- Supplement v. Replace Results

Figure 3—Mapping strategies and tactics to the process- and activity-based models.

Visions of the HCI Future
Also useful in planning for and creating the next generation of user interfaces is a review of
visions of the HCI future from various experts in the computing field. Together, the visions
provide boundaries on what is considered reasonably likely. Table 1 summarizes a sample
of visions.

Name Vision summary
Vannevar Bush In remarkably prescient 1945 paper, proposed a “memex” device that shares
attributes with the world wide web and personal digital assistants.
David Gelernter As part of a manifesto on computing, called for the overhaul of the WIMP interface
and proposed a primarily time-based solution, reasoning that humans organize
around life events.
Jaron Lanier, Freeman Part of a group asked to respond to Gelernter’s manifesto. Lanier said Gelernter
Dyson, Lee Smolin, was too much of an idealist and pointed out “software can be counted on to drag
Nathan Mhyrvold the whole thing down,” calling it a reverse Moore’s Law for increasingly less
efficient software. Dyson felt that tools should be the focus of an evolving
cyberspace. Smolin and Mhyrvold pointed out that the future of computing could
be very much like the present, and use the unchanging general interface for the
automobile as an example.
Michael Dertouzos In The Unfinished Revolution, argued that real progress will only be achieved by a
human-centered computing approach, aided by the confluence of five emerging
technologies: natural interaction, automation, individual information access,
collaboration, and customization.
Joe Clabby In Visualize This, perhaps too optimistically predicted a revolution in computing
within the next 3 or so years (i.e., by circa 2004). The result is the “Sensory Virtual
Internet” driven by the evolution and confluence of five types of technological
improvement: computer-to-human sensory output, human-to-computer
communication (e.g. speech recognition), network and computer infrastructures,
applications development, and collaborative applications.



George Colony Proposed the “X Internet” in which X represents executable and extended, a new
software category that allows for two-way conversation delivered (or extended) via
the Internet to many more devices, such as handhelds and cell phones.
Jakob Nielsen A recognized “guru” of HCI, calls simply for easier to use applications/sites,
achieved through simple changes such as much larger (and ultimately
portable/foldable) displays.

Table 1—Visions of future human-computer interaction.

The Personal Knowledge Base Vision
One way to understand how user-technology integration should evolve is to construct a
vision of the ideal information-seeking system within a reasonable reality to strive for. The
following vision employs a data-centric perspective, given this paper’s focus on information
access and organization.

A Personal Knowledge Base (PKB) is a unique, highly organized and connected repository
of information for and about a user. The purpose of the PKB is to support all the information
needs of its owner by organizing collected “information objects,” relating information to
personal goals, and connecting personal data to the outside world. When such a system
exists in a complete and reliable form depends on the rate of continued integration among
the current set of disparate data sources that users rely on and interface with today, such
as email folders, local and enterprise network folders, workgroup/organization/enterprise
portals, Internet browsers, third-party data repositories, handhelds, cell phones, and
hardcopy documents, folders, etc. The current, evolving system is tolerated by most users
but leaves much room for improvement, considering all the time and effort users spend
accessing and organizing information.

Although a system like the PKB may not be perfected within the next few years, it is useful
to consider its characteristics and implications, and then plan how best to make information
seeking products and services fit with such a system. A conceptual picture of the PKB is
depicted in Figure 4. The human accesses data from the world of information through his
PKB, which is connected to a larger workgroup KB, which in turn is connected to an even
larger organization KB. The inner layer in the figure surrounding the core data represents
metadata (e.g., author, publication, and date of an article) used to organize and present
data through the outer layer, which represents a virtually unlimited amount of flexible user
interfaces or “views.” The PKB is centrally located, secure, and accessible from anywhere
using any device. The PKB is c
onstantly evolving and self-optimizing, and may use “agents” designed to look for useful
information objects and fit into the PKB it in a meaningful way.



Figure 4—The Personal Knowledge Base.

Figure 5 shows an example of what type of data may comprise a PKB. This view of a PKB
is based on the various roles that the user plays, such as homeowner, family member,
community member, employee, etc. Figure 6 shows an exploded view of the employee role
information, divided into type or purpose of information, such as projects, financial and
benefits, and communications. In addition to this type of information, a complete PKB might
also have information about a user’s identification for authentication, a “digital wallet” with
secure information for automated financial transactions, custom settings for tools and
applications, user goals and preferences, and some form of personal “agents.” Benefits of
a PKB include less time spent finding and organizing information, more work done for a
user through automation, more relevant information presented to a user as it is available,
and increased collaboration effectiveness due to links between KBs based on the nature of
the relationship between KB owners. The better organized the PKB, the easier it is to create
interfaces or views that serve the user for a particular task in a particular context. Thinking
about the various ways in which data should be organized for a given user can shed light
on the best tools or applications to create.



Figure 5—The composition of a Personal Knowledge Base.

Figure 6—The composition of the “Employee” section of a Personal Knowledge Base.

Trends and Technologies
Listed below are ten changes expected to occur in the user experience as a result of the
introduction of new technology. Many of these changes are well underway.



1) Access to increasing amounts of more diverse data.
2) Data available to the user will be much more organized.
3) Personal data stores will be more integrated with external data sources.
4) More will be done automatically for the user, with an increasing reliance on agents.
5) Users will interact using a greater breadth of their perceptual/motor apparatus.
6) Computing will occur at more places.
7) Users will interact with many more devices.
8) Users are more likely to collaborate as collaboration tools are increasingly
integrated into applications.
9) Users will interact more with pictures, and user interfaces will be more visual in
general.
10) The human attention resource will become more and more precious as the workday
becomes more fragmented.

Tables 3 and 4 list the trends and technologies most likely to affect future user interfaces.
Table 3 lists those directly affecting HCI (divided into those related to input vs. output) and
Table 4 lists more general trends and technologies that are expected to have more indirect
effects.
Input
Speech recognition  Digitization and interpretation of human speech for dictation or “command and
control” input as part of a “natural dialog” between human and computer.
Handwriting recognition  Transferring written input from a user into a form that matches keyboard input.
 Closely tied to pen computing.
Input–further out
Gesture/gaze  Sense of touch, now primarily for games controls and virtual reality.
Haptics  Recognizes hand gestures or eye movements as commands.
Biometrics  Bio-based authentication–fingerprint ID, retinal scan, etc.
 Applications should appear within the next two years and enter the
mainstream later.
Thought/direct-brain  Interpretation of distinctive brain patterns generated voluntarily by the user as
commands.
 Typically limited to less than five distinct commands.
Prosthetics  In the future, prosthetics will move from filling a void to augmentation (e.g., a
third arm).
Output
Display evolution  Continued evolution toward larger, smaller, and higher resolution displays.
 Large displays for co-located collaboration, s
 mall displays for mobile computing.
Visualization  Graphical representation of information designed to optimize review and
analysis, and uncover hidden patterns. Visualization spans a broad range of
complexity from simple bar, pie charts to 3D representations of thousands of
data points.
Electronic ink  “Smart” ink used to create “electronic paper” or digital displays as thin and
flexible as paper, yet cheap enough to be sold in volume or integrated together
as a notebook.
Virtual reality  3-D immersive environment responding to user actions in a natural way.
 Often associated with avatars.

Table 3—Technologies directly related to HCI.



General UI evolution  Evolution of graphical interfaces for desktops, browsers, etc.
 Includes factors such as software development tools and user acceptance.
Data explosion  The creation of increasingly more data available for consumption.
 The diversification of data beyond text into rich media, such as images, audio,
and video.
Data organization  The proliferation and use of metadata to make data collections more intelligent
and organized.
 Improve users’ ability to access information in a more efficient and context-
laden manner.
 Includes concepts such as metadata, XML, portals, topic maps, knowledge
management, and the Semantic Web.
Pervasive computing  The confluence of many forces (e.g. wireless access, mobile workforce and
devices) resulting in the spreading of computing away from the desktop and
into the general environment.
 Perhaps the most significant current HCI trend.
Collaboration  Evolution of tools enabling collaboration and communication between co-
workers, customers, etc.
 Includes e-learning, instant messaging, and workplace evolution
Agents  Dynamic software entities that are self-contained and perform tasks
proactively on behalf of a user or user-initiated process. Includes synthetic
characters.
Customization  Customizing the content of interfaces for user types or personalizing for
specific users.
Globalization  The worldwide production and consumption of online information.
 Subsumes internationalization (common) and localization (specialized).
Other forces  A collection of forces that include copyright/legal issues, digital rights
management, security and privacy, standards battles, the increase in the
computing/cost ratio (Moore’s law), profit-making forces, basic human
behavior (e.g., laziness, self-interest), and geopolitical forces.

Table 4—General trends and technologies



The Hype Curve
The hype curve concept developed by the Gartner Group is a very useful tool for tracking
the maturation of a new technology as it approaches adoption. As Figure 7 depicts, the
curve begins when a “Trigger” (event or cause) gives birth to a technology, leading to a
buildup of hype as the technology approaches the “Peak of Inflated Expectations” before
falling downward toward the “Trough of Disillusionment” as the hype yields to concerns
about the viability of the technology. As issues are worked out and problems are solved, the
technology ascends the “Slope of Enlightenment,” ultimately reaching the “Plateau of
Productivity” when enough problems are solved that the technology has entered the
mainstream. Certainly not all technologies make it to the “Plateau” and the speed with
which a technology passes through the curve can vary greatly.

Figure 7—Hype Curve for HCI-related technologies.

The hype curve in Figure 7 includes technologies that are expected to either directly or
indirectly have effects on HCI and user interfaces. Many of these technologies are
subsumed under technologies or trends listed in the previous section. For example,
Pervasive Computing includes PDA phones and Wireless Web, while Data Organization
includes Topic Maps, Agents, DRM (Digital Rights Management), Digital Wallets, Portals,
and XML. As the legend shows, the color of a circle representing a technology indicates
how many years to expect it to fully mature. The position and color of technologies are
based on a review of the literature including predictions from analysts and the author’s
analysis of how the technologies may affect user interfaces for information access and
organization.



Discussion
Now that all the components of the conceptual foundation for designing information seeking
user interfaces have been described, we can consider strategies for integrating appropriate
technologies into user interfaces, as well as the implications for the evolution of information
seeking products. An effective strategy for new technology integration should include
developing and maintaining an understanding of both 1) the user behavior and associated
needs within a given domain, and 2) a realistic expectation of how various technologies
map to user needs and how rapidly those technologies will reach maturation and general
adoption. Large gaps in knowledge of these areas can result in wasting time and money on
integrating immature or inappropriate technologies. Leveraging the right technology for the
right user activities can result in the next “killer” application.

The contents of this paper have many implications for educating and training the next
generation of interface designers. Academic institutions should anticipate changes in
computing technology and include in programs a consideration of HCI environments at
least 2 to 4 years out (when students will be entering HCI-related jobs). Universities should
also seek opportunities for collaboration between industry and academia so that there is a
clear path between research and implementation. The foundation of any HCI evolution
effort must be a deep understanding of human behavior and needs, the most valuable
knowledge in determining the usefulness of a given new technology

The concept of applying new technology to the next generation of user interfaces raises
many questions to ponder. Listed below is a sample to feed discussion:
 What will be state of user interfaces 2, 5, 10 years from now?
 What are the effects of the interaction of various trends and technologies? How are
the effects of various new technologies dependent on one another?
 Independent of the technology available, how will users really want to interact with
computers? Related to this question, what are the social implications of interacting
with computers using keyboard/mouse vs. speech vs. handwriting input?
 To what extent is the Personal Knowledge Base concept realized in today’s
computing world? What are the biggest hurdles in realizing the PKB?
 What factors affect the speed with which a given technology travels through the
hype curve?
 What rate of change is healthy and acceptable for users and their organizations?
What forces throttle the rate at which new technology is integrated into products?
 How should the education and training of HCI–related professionals change over
time?



Appendix
Six primary information seeking activities (Bayer, 2000)

Activity Goal Example Tasks
Thorough/ Gather all documents and Investigate company for acquisition
Exhaustive research information Research a story for publication
Quick & dirty research Find “the” answer for a Find simple facts that answer a business
business problem question
Find overview information that covers an issue
Get a specific document Get the single document Get article from a publication
needed for a work product Get a company’s annual report
Find a country report
Find a bill or floor vote
Validate/Verify specific Confirm accuracy or relevance Check company address/location
information of known information Check a person’s name/title
Review government statistics
Continuously track Have the most recent Track a company or industry
specific topic/issue information available for a Follow a competitor in the news
critical business need
Keep current on general Follow a trend or topic related Review today's headlines
topic of interest to my job Follow the latest technology trends



References
Bates, M.J. “Where Should the Person Stop and the Information Search Interface Start?” Information
Processing and Management. 26 (3). 575-591. 1990.

Bayer. Target tasks for nexis.com users. LexisNexis memo. 2000.

Bush, Vannevar. “As We May Think.” The Atlantic Monthly. 176(1):101-8. July, 1945.

Chun Wei Choo, C., Detlor, B. and Turnbull, D. “Information Seeking on the Web: An Integrated Model
of Browsing and Searching,” First Monday. 5(2). February, 2000.

Clabby, J. Visualize This. New Jersey: Prentice Hall. 2002.

Dertouzos, M. The Unfinished Revolution. New York: Harper-Collins. 2001.

Ellis, D. “A Behavioural Approach to Information Retrieval System Design.” The Journal of
Documentation. 45(3):171-212. 1989.

Fenn, J. and Deighton. “Emerging Technologies for Human-Computer Interaction.” Gartner Group
Report T-14-0298. October 1, 2001.

Gelernter, D. “The Second Coming—A Manifesto.” The Edge. 70. June 15-19, 2000.
http://www.edge.org/documents/archive/edge70.html

Gilmour, K. “The Future's Bright!” Internet Magazine. August 1, 2001.

Kuhlthau, C.C. “Developing a Model of the Library Search Process: Cognitive and Affective Aspects.”
Reference Quarterl.. 28(2): 232-42. 1988.

Marchionini, G. Information Seeking in Electronic Environments. Cambridge: Cambridge University
Press. 1995.


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