A GRAPHICAL WORKBENCH FOR KNOWLEDGE WORKERS

Heiko Haller, Andreas Abecker and Max V

olkel

FZI Research Center for Information Technology, Haid-und-Neu-Str. 10-14, D-76131 Karlsruhe, Germany

Keywords:

Zooming user interface, Diagrammatic knowledge representation, HCI design, Knowledge worker.

Abstract:

We present iMapping, a novel approach for visually structuring information objects on the desktop. iMapping

is developed on top of semantic desktop technologies and particularly supports personal knowledge man-

agement of knowledge workers. iMapping has been designed to combine the advantages of the three most

important visual mapping approaches, Mind-Mapping, Concept Maps and Spatial Hypertext. We describe

the design and prototypical implementation of iMapping—which is fundamentally based on deep zooming

and nesting. iMapping bridges the gap between unstructured content (like informal text notes) and semantic

models by allowing to easily create on-the-ﬂy annotations with the whole range of content links, from vague

associations to formal relationships. Our ﬁrst experimental evaluations indicate a favorable user experience

and functionality, compared with state-of-the-art, commercial Mind-Mapping software.

1 INTRODUCTION

1.1 Motivation

While practically all enterprise information systems,

as well as most knowledge management (KM) ini-

tiatives, address the level of inter-personal knowl-

edge storage and exchange, recent efforts also address

the level of the individual knowledge worker who—

though being embedded in organisational processes

and communities—nevertheless is in many respects

a relatively autonomous “knowledge processing unit”

with many personal notes, ideas, and artifacts which

shall not and need not to be shared within a bigger

organizational context. The knowledge worker has

not only to be embedded and aligned with community

and organisational information streams and processes,

he or she also needs personal knowledge manage-

ment (Abecker et al., 2009) methods and tools which

support individual task and time management, indi-

vidual creativity, individual lifelong learning, as well

as personal information management in the widest

sense. If one wants to simply use organizational KM

systems and approaches for personal KM, this often

falls short; especially those approaches which rely on

highly-structured information and meta data to be en-

tered and maintained by the user, fail because nobody

wants to make such additional effort with immediate,

visible beneﬁt. For instance, this may be one of the

reasons why semantic technologies have not found

very widespread use, so far, although semantic meta

data would undoubtedly improve ﬁndability, interop-

erability and, in general, automated processing of in-

formation and knowledge items.

With our approach, we pursue the hypothesis that

(1) the expected immediate, visible beneﬁt might

be experienced when users manage their everyday

knowledge resources like personal notes, ﬁles, book-

marks etc. (like in the setting of a semantic desktop

environment; cp. (Sauermann et al., 2009)), but that

(2) it is also crucial to leave it to the user, how much

effort she wants to put into formalizing content and

meta data.

So, we aim at building an environment that (a) is

able to cover the full range from informal note-taking

over more structured graphical representations up to

formal semantic knowledge models, but that (b) pro-

vides semantic functionalities without restricting the

user’s modeling freedom that is offered in informal

(‘non-semantic’) tools.

When formal semantic knowledge structures are

used, content is typically ﬁne grained and highly

structured. Such content structures are typically more

complex than plain text or classical hypertext struc-

tures. Even with the relatively simple structures

in classical hypermedia, where we just have inter-

linked information objects on the granularity level

of whole pages or documents, hypertext research has

shown that users often get “lost in hyperspace” when

browsing without additional navigational help (Ter-

180

Haller H., Abecker A. and Völkel M. (2010).

A GRAPHICAL WORKBENCH FOR KNOWLEDGE WORKERS.

In Proceedings of the 12th International Conference on Enterprise Information Systems - Human-Computer Interaction, pages 180-185

DOI: 10.5220/0002968601800185

 SciTePress

gan, 2002). This stresses the need for user interfaces

that facilitate navigation and authoring of such struc-

tures without losing orientation.

Using graphical environments for structuring ex-

ternalized knowledge enables the users to employ

their highly efﬁcient sense of spatial orientation on

their personal knowledge and information space, and

it enhances the link between their mental and exter-

nal models—because it enables the use of diagram-

matic depictions whose obvious structure corresponds

more closely to the structure of the content because

(unlike text) diagrammatic knowledge representations

carry a structural analogy to the content they represent

(Schnotz and Bannert, 2003).

So, we developed iMapping as a new visual map-

ping approach that unites the strengths of established

mapping techniques and combines them with seman-

tic technologies and modern HCI approaches like

deep zooming. iMapping supports the whole range

from easy informal note-taking to formalized knowl-

edge engineering in the same powerful, yet easy-to-

use, environment. The basic metaphor of an iMap

is that of a large pin-board where information items

can be spatially arranged, enabling users to gain a vi-

sual overview over collections of items at once. These

items can represent bits of text as well as (in the near

future) any kind of external resources like ﬁles, Web

pages, pictures or other maps. They can also be nested

into each other and interlinked in various ways. Be-

sides browsing by links, users can navigate an iMap

by zooming through it.

In this article, we provide a list of requirements

for a next generation visual knowledge mapping ap-

proach which was created from literature studies,

state-of-the-art analysis, and use case requirements

elucidation (Section 1.2). After that, the design of

iMapping is discussed in Sections 2. Section 3 illus-

trates our ongoing evaluation efforts and ﬁrst promis-

ing results. Finally, we conclude with Section 4 which

contains a summary and some plans for future work.

1.2 Requirements

Based on the analysis of existing tools and approaches

in (Haller, 2003) and literature from the areas of de-

sign and cognitive science, we have identiﬁed a set of

functional requirements to be met by diagrammatic

knowledge mapping techniques and tools in order to

be cognitively adequate for extensive personal knowl-

edge management. This collection of requirements

and its rationale is published in (Haller and Abecker,

2009) and will here only be listed in brief:

Requirements for Diagrammatic Knowledge Map-

ping Approaches.

• Free Placing (Items should be freely placeable

anywhere and should maintain their positions—at

least relative to their surrounding.)

• Free Relations: Interlinking items in different lev-

els of formality:

– Formalized / semantic links (Like in ontology

editors)

– Informal labeled links (like in concept maps)

– Unlabeled links (e.g. just of plain arrows or

lines)

– Free nodes, that do not have any explicit rela-

tion to others.

• Annotations: optionally hideable additional notes

or highlights

• Overview / Abstraction through clustering and hi-

erarchical sub-maps

• Scalability (Ability to visually deal with large

amounts of items)

Requirements for Diagrammatic Knowledge Map-

ping Software.

• Simple Editing: Adding or modifying items with-

out additional interaction needed.

• Connecting External Content (e.g. local ﬁles or

remote web pages)

• Focus / Filter: deliberately narrowing down visi-

bility to the essential

• Integration of Detail and Context through smooth

and steady zooming, overview functions, levels of

detial.

• Interoperability with other related tools

2 DESIGN

2.1 Visual Knowledge Mapping

In the design of the iMapping approach and software

tool, we aimed at combining the advantages of the

classical mapping approaches and simultaneously ful-

ﬁlling to the greatest possible extent the requirements

both listed above.

We began with the requirement of free placing.

Items can be freely created at or they can be moved

to any position in the map. An iMap can be seen as

a virtually inﬁnite pin board. Usually (e.g., for per-

sonal note-taking or idea management), these items

A GRAPHICAL WORKBENCH FOR KNOWLEDGE WORKERS

181

will be short text passages. The size can vary from

just a keyword to a short note or whole paragraphs in-

cluding rich text marked up by using a Wiki syntax

provided by the back end.

These items can contain other items such that one

can use microcontent rather than long, unstructured

text passages. Longer texts are then a sub-map con-

taining a sequence of smaller text-items. The iMap

hierarchy goes down into deeply nested nodes which

can be zoomed into (see Fig. 1) such that a basic hi-

erarchy of information items is created.

The hierarchical structure is represented by visual

inclusion: nested items are shown inside one another.

Compared to a classical tree view like it is used, e.g.,

in Mind-Maps, this has the following beneﬁts:

• It leaves more freedom to place items according

to gestalt principles (Metzger, 1953) (e.g., group-

ing).

• Node-and-link representations (like in classical

concept maps and many other visual languages)

are still possible without interfering with the hier-

archical structure.

• The layout principle stays the same on all levels of

the hierarchy (in concentric trees like Mind-Maps,

all sub-branches point in one direction). Like that,

each part of the map can be treated like a self-

contained sub-map which largely helps clustering

and modularization.

• Nesting by inclusion (which is also widespread,

e.g., in the use of parentheses, Venn diagrams,

tree-maps), is closer to natural orientation where

details are parts of their surrounding. In real life,

when we want to see the big picture, we take a step

back to see the surrounding context of something.

Of course, this kind of nesting is not new in itself.

However, traditional, paper-and-pencil based map-

ping techniques can not cover many levels of hierar-

chy like this. Today, however, with computer-based

mapping approaches, very deep nesting and zooming

is possible which opens up a virtually inﬁnite amount

of space for iMaps to grow over time when used, e.g.,

as personal knowledge repositories.

Adding and creating content to an iMap is done by

clicking anywhere in the map and typing some text.

It is always possible to add vague and unstructured

content. Although allowing for semantic knowledge

management, it has been a fundamental design deci-

sion to never force the user to specify any semantics.

Content can later be reﬁned and formalised incremen-

tally.

There can be multiple visual instances of one and

the same information object, because it may be rele-

vant in different contexts.

For establishing link structures, we distinguish

several different ways of interrelating items which can

be used in an iMap:

1. explicit linking on an item level (stating a rela-

tion between two objects); each of these can be

mere navigational links or carry formal semantics

if speciﬁed; in particular, we can distinguish four

kinds of links and ways of establishing them:

(a) labeled links: If no pre-existing relation type is

suitable, the user can always just enter the full

label of the link to be displayed, e.g., along the

arrow. By that, in the back-end a new relation

type with that name is automatically created;

(b) unlabeled links: Links do not have to be labeled

at all;

with the QuiKey tool explained below: When

relating two items, the user gets a choice of

existing relation types selectable by an incre-

mental text search over their names, support-

ing reuse of existing relation types and avoiding

misspellings;

(d) hyperlinks: Links do not have to be drawn as

arrows; hyperlinks go from within the text con-

tent of an item to any other item.

2. implicit linking: Following the principle of Spa-

tial Hypertext, items can also be loosely placed in

spatial relations to one another without explicitly

linking them at all. These spatial relations can be

parsed to extract implicit relations, like sequence,

grouping or hierarchy. Currently, the only actu-

ally implemented way of implicit linking is that

of nesting items into another (i.e. placing the link

target inside at a speciﬁed position) in order to in-

dicate their hierarchical ordering.

In classic graph-based approaches, nodes usually

have to be arranged in a layout that minimizes edge-

crossings in order to reduce visual complexity. But

even then, maps with large amounts of nodes and

links often suffer from tangled links (aka “spaghetti

syndrome”). To avoid that, unless selected otherwise,

links are only shown on demand. Like that, the links

of current interest are more salient and easier to visu-

ally integrate with the nodes they connect. Depending

on user settings, links can, for instance, become visi-

ble on an mouse-over event (see Fig. 1).

While iMaps can be freely navigated by panning

(scrolling) and zooming like it is known, e.g., from

Google maps, our user tests have shown that users

much prefer navigation guided by content structure

like directly zooming to speciﬁc items by point-and-

click or following links. Additional to that, a search

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182

Figure 1: Screen shot with part of an iMap (about iMapping). Only links from and to one item are visible.

function lets users jump to any item directly. How-

ever, any transition to another place in the iMap is car-

ried out by smooth panning and zooming to maintain

a sense of spatial orientation while moving through

the map.

While iMapping focuses on overview and intu-

itive use through a visual approach, this can also

be a burden because every item needs to be deliber-

ately positioned. Hence, it is desirable to complement

such a visual tool by techniques that provide map-

independent access to the same structured informa-

tion. iMapping is complemented by QuiKey, a kind

of smart semantic command-line that focuses on high-

est interaction-efﬁciency to browse, query and author

semantic knowledge bases in a step-by-step manner.

Among other things, QuiKey allows to jump to any

item in an iMap with just a few keystrokes through a

incremental search function. QuiKey is explained in

more detail in (Haller, 2008); for further information,

see http://quikey.info/.

3 EVALUATION

We carried out a comparative evaluation study to

speciﬁcally test the suitability of the nesting and

zooming approach for personal knowledge manage-

ment tasks on a larger scale, because this seems to

be the biggest difference to the classical approaches

discussed in (Haller, 2003) For that purpose, we com-

pared the iMapping prototype with MindManager 7,

the most wide-spread state-of-the-art Mind-Mapping

application. The details of this evaluation are de-

scribed in (Haller and Abecker, 2010).

Test users were presented with pre-ﬁlled maps

in both applications: A small biological taxonomy.

Both maps contained the same content in the same

structure—once as a classical Mind-Map and once as

a nested iMap.

The sample of testers consisted of 12 rather het-

erogenous individuals (6 male and 6 female), aged

23 – 64. Their primary occupations were: painter,

journalist, interactive media engineer, photo model,

students (english and biology, computer science,

psychology, economical engineering), PhD students

(healthcare, economics, logistics, semantic web).

The average time each user needed for the dif-

ferent kinds of tasks and the ratings given by the

users were compared between the two tools and tested

for statistical signiﬁcance with a dependent t-test for

paired samples.

3.1 Results and Discussion

There was no statistically signiﬁcant difference in the

interaction times measured. However, as Table 1

shows, there was a clear tendency of all editing tasks

(adding, rearranging and interlinking of content) be-

ing carried out slightly faster in the iMapping appli-

cation. This could be explained by users’ comments

that in the iMap, the topology was clearer and eas-

ier to grasp, which is also reﬂected in the ratings (see

Table 2).

The exact mean times and percentages in compar-

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183

Table 1: Mean times and percentages for groups of tasks in comparison (rounded values)—None of them are signiﬁcant at the

5% level.

Mind Manager iMapping difference

practice time 5,8 min 8,6 min 2,8 min

adding content 28,0 sec 23,6 sec -4,4 sec

rearranging content 25,5 sec 21,8 sec -3,7 sec

drawing links 27,4 sec 25,7 sec -1,7 sec

visually ﬁnding and reading 25,9 sec 33,0 sec 7,1 sec

remembering number without map 33,3% 62,5% 29,2%

remembering content without map 30,8% 37,1% 6,3%

Table 2: Mean ratings given as german school grades for both tools: iMapping is rated better en every category surveyed

(1=“very good”, 2=“good”, 3=“satisfactory”, 4=“sufﬁcient”, 5=“insufﬁcient”).

Mind Manager iMapping difference sig. (p)

navigation 2.4 2.1 0.3 .275

overview 3.0 1.9 1.1

∗∗

.003

structure / interrelations 2.7 2.1 0.6 .270

aesthetics 3.3 2.2 1.1

∗

.038

look and feel 2.5 2.0 0.5 .065

suitability for brainstorming 2.5 2.0 0.5 .137

suitability for note-taking 3.0 1.9 1.1

∗∗∗

.001

suitability for personal KM 3.3 2.0 1.3

∗∗∗

.000

overall rating 3.0 2.0 1.0

∗∗∗

.000

average 2.9 2.0 0.9

∗∗∗

.001

ison can bee seen in table 1. The average subjective

ratings that were given as german school grades for

both tools are listed in table 2. iMapping was rated

better in every surveyed aspect and almost one full

grade better in average. Most of these ﬁndings were

statistically signiﬁcant—in particular: overview and

aesthetics were rated better in iMapping, which was

also perceived to be more suitable for note taking and

personal knowledge management in general. Espe-

cially in the overall rating, iMapping was rated ‘good’

in average as opposed to only ‘satisfactory’ Mind-

Manager.

The good rating for overview is also backed by

many spontaneous comments made during testing, in

the direction of iMapping providing an easier way to

get an overview over especially the coarse structure—

through the general approach of nested items, the pos-

sibility to arrange them freely and through the facility

to zoom all the way out and back in a gain with only

two keystrokes.

The good rating for aesthetics came somewhat as

a surprise, since three of the female testers had vehe-

mently complained about the lack of color in the pre-

dominantly grey iMapping prototype. But even so,

the current visual design of the iMapping application

seems to be quite well-received.

We proudly note that the best rating and highest

advantage has been given for the aspect suitability

personal knowledge management in general. How-

ever this is not surprising, since MindManager is not

designed for very large maps whereas it was a core

requirement for iMapping to be able to scale up to ex-

tremely large maps as they can evolve over years of

personal knowledge management.

All in all we are satisﬁed with the result that iMap-

ping is in objective measures of time needed for inter-

action for typical tasks comparabe and in subjective

measures even superior to MindManager, which can

be regarded as state of the art, has millions of users

and is on the market since 1994.

Since the intended usage scenarios for iMap-

ping exceed those overlapping with MindManager,

some hypothesized advantages could not be tested in

this setting and are subject to ongoing investigation.

Namely: Longterm use for personal knowledge man-

agement, the use of much larger maps with thousands

of items, the use of QuiKey and using semantic links

and queries.

4 SUMMARY AND OUTLOOK

Semantic knowledge management technologies

might in the future be able to signiﬁcantly increase

interoperability between applications even across

context boundaries and they might leverage the

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184

creative and productive power of knowledge work-

ers. However, if knowledge management does not

start at the personal level, and starts with provid-

ing immediate beneﬁt to the individual knowledge

worker, it is questionable whether semantic knowl-

edge management systems will ever spread very

far. Focusing on user interaction and cognitive er-

gonomics is obviously an important issue there, es-

pecially because in knowledge-intensive tasks, a user

can barely afford to sacriﬁce much of his limited cog-

nitive capacity (Miller, 1956) to dealing with the tool

instead of dealing with the content itself. Especially

for large knowledge repositories with highly inter-

linked information items of different levels of for-

malization, iMapping-based user interfaces can make

knowledge management more intuitive, on one hand,

and more powerful, on the other hand, because it pro-

vides a medium that fosters the use of visual orienta-

tion in a ﬂexible and easy way and yet supports more

structured knowledge modeling in just the desired de-

gree of formalization.

While we continue improving our ﬁrst iMapping

tool, we hope the general approach will ﬁnd more

widespread application. Its ﬂexible, zooming-based

approach, e.g., also makes iMapping a candidate for

mobile use on rather small displays. Of course, a cen-

tral focus of our immediate next working steps is on a

broader and deeper qualitative and quantitative evalu-

ation of the approach and its implementation.

ACKNOWLEDGEMENTS

This work has been partially funded by the Euro-

pean Commission in the projects NEPOMUK, MA-

TURE and myUI, by the German Federal Ministry for

Economy BMWi within the THESEUS research pro-

gramme, and by the German Federal State of Baden-

urttemberg. Special thanks go to Henning Sperr for

the implementation work of iMapping.

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