ORGANIZATIONAL KNOWLEDGE PATTERNS

Definition and Characteristics

Kurt Sandkuhl

1,2

Institute of Computer Science, Rostock University, Ulmenstr. 69, Rostock, Germany

School of Engineering, Jönköping University, Box 1026, Jönköping, Sweden

Keywords: Organisational knowledge, Pattern, Enterprise Modelling, Knowledge pattern.

Abstract: The importance of managing organizational knowledge for enterprises has been recognized since decades.

Enterprise knowledge modeling contributes to this subject by offering methods, tools and approaches for

capturing knowledge in formalized models supporting the lifecycle of organizational knowledge

management. The paper focuses on reuse of organizational knowledge in different organizational contexts

by using patterns. We argue that organizational knowledge patterns have to combine technical and cognitive

qualities in order to support organizational knowledge creation and IT-supported knowledge reuse. The

contributions of the paper are (1) to define of the term organizational knowledge pattern in relation to other

pattern types, (2) to identify characteristics of such patterns, and (3) to examine two established pattern

types from knowledge engineering to expose the key features of organizational knowledge patterns.

1 INTRODUCTION

The importance of managing organizational

knowledge for enterprises has been recognized since

decades. The expectation is that systematic

development and reuse of organizational knowledge

will help to improve the competitiveness of the

enterprise under consideration. Enterprise

knowledge modelling contributes to this purpose by

offering methods, tools and approaches for capturing

knowledge about processes and products in

formalized models in order to support the entire

lifecycle of organizational knowledge management.

The paper focuses on a specific aspect of

enterprise knowledge management: organizational

knowledge prepared for reuse in different

organizational contexts by using patterns. The use of

patterns in computer science has some tradition (see

Section 2.1); in knowledge management and

knowledge engineering patterns commonly provide

reusable components or methods for well-defined

problems in specific knowledge engineering

contexts. However, such patterns focus more on

technical characteristics than on cognitive qualities

required for supporting organizational aspects of

knowledge creation and management. We argue that

organizational knowledge patterns have to combine

technical and cognitive qualities in order to support

organizational knowledge creation and IT-supported

knowledge reuse.

If we consider information or knowledge-

intensive industry or service sectors as an

application context for such reusable organizational

knowledge, the time to deployment and the required

efforts become an issue. With time to deployment

we denote the time from selecting a knowledge

pattern to an operative use of this knowledge.

Operational use usually does not only require a

transfer of the knowledge captured in the knowledge

pattern to the individuals in the organization

supposed to use this very knowledge, but also the

implementation of supporting IT systems, like work

flow or information management support, by

configuring existing platforms, executing the model

as such or implementing new software systems. In

the light of the ever increasing pressure for more

efficiency and shorter time-to-market, the ideal

organizational knowledge pattern would be easy-to-

understand and easy-to-deploy. But what features

should organizational knowledge patterns have in

order to meet these requirements of being easy-to-

understand and easy-to-deploy? How close are the

many existing pattern types to this vision of “ideal”

ones and how could they be enhanced? As initial

contributions to these questions, the paper offers (1)

the definition of the term organizational knowledge

pattern in relation to other pattern types, (2) the

230

Sandkuhl K..

ORGANIZATIONAL KNOWLEDGE PATTERNS - Deﬁnition and Characteristics.

DOI: 10.5220/0003667702300235

In Proceedings of the International Conference on Knowledge Management and Information Sharing (KMIS-2011), pages 230-235

ISBN: 978-989-8425-81-2

 2011 SCITEPRESS (Science and Technology Publications, Lda.)

identification of characteristics of such patterns, and

(3) the examination of two established pattern types

from knowledge engineering in order to expose the

key features of organizational knowledge patterns.

The research approach used is exploratory.

Grounded in relevant related work, we propose a

new concept and discuss its validity.

After an introduction to the background of this

work (Section 2), the term of organizational

knowledge pattern is defined and discussed (Section

3). In Section 4, the paper presents two different

kinds of patterns: enterprise model patterns and

ontology design patterns. Section 5 discusses the

given definition and briefly compares the pattern

types. A short summary concludes the work in

section 6.

2 BACKGROUND

Two areas forming the background for work

presented in this paper will be briefly introduced in

this section: pattern use in computer science and

enterprise knowledge modelling.

For more than a decade, patterns have been

popular in computer science and were introduced for

numerous areas. The seminal book on patterns was

published by the “Gang of Four” (Gamma et al.,

1995) and focuses on software design patterns.

Many other books followed, basically offering

patterns for all phases of the software development

process, including analysis patterns (Fowler, 1997)

and software architecture patterns (Buschmann et

al., 2000). The pattern idea was adapted in other

areas of computer science, like workflow patterns

(van der Aalst et al., 2003) or ontology patterns

(Blomqvist, 2005). Despite the many different fields

addressed by these different pattern types, they share

some characteristics:

• They are based on experiences and deeply

rooted in the practice of the field.

• They are not meant to be used blindly as they

are. You have to understand the core idea and

adjust or apply it for the problem at hand.

• They do not only help to build software,

processes or models, but also to communicate

approaches within a team.

Enterprise modelling, in general terms, is

addressing the systematic analysis and modelling of

processes, organization structures, products

structures, IT-systems or any other perspective

relevant for the modelling purpose (Vernadat, 1996).

Enterprise models can be applied for various

purposes, such as visualization of current processes

and structures in an enterprise, process improvement

and optimization, introduction of new IT solutions

or analysis purposes. Frameworks like GERAM and

CIMOSA or the results of FP6-IP-ATHENA

(Ruggaber, 2006) aim at supporting enterprise

engineering in the large by providing reusable

enterprise models for administrative and

manufacturing functions commonly found in

enterprises of a specific domain.

Enterprise knowledge modelling combines and

extends approaches and techniques from enterprise

modelling. The knowledge needed for performing a

certain task in an enterprise or for acting in a certain

role has to include the context of the individual,

which requires including all relevant perspectives in

the same model. Thus, an essential characteristic of

knowledge models are “mutually reflective views of

the different perspectives included in the model”

(Lillehagen and Krogstie, 2009). Enterprise

knowledge modelling aims at capturing reusable

knowledge of processes and products in knowledge

architectures supporting work execution.

Enterprise knowledge modelling has a tradition

of using visual models, which basically allow for

adapting the language extension (i.e. the graphemes,

vocabulary and syntax of the modelling language) to

the application domain. This contributes to

increasing social pragmatic quality, i.e. to what

extent the stakeholders understand and can apply the

models. Enterprise domains often are socially

constructed and intersubjectively agreed upon, and

enterprise knowledge models usually created as part

of a dialogue among the participants involved in

modelling.

3 ORGANISATIONAL

KNOWLEDGE PATTERNS

This section introduces and defines the term

“organizational knowledge pattern” in the context of

relevant work from knowledge engineering (3.1) and

from organizational knowledge management (3.2).

We decided to contrast the requirements from

organizational knowledge management, expressed as

features of reusable knowledge which we chose to

call organizational knowledge patterns, with

characteristics of contemporary approaches for

reusing knowledge which commonly are referred to

as knowledge patterns.

3.1 Knowledge Patterns

The term knowledge pattern has been explicitly

ORGANIZATIONAL KNOWLEDGE PATTERNS - Definition and Characteristics

231

defined by Clark, Thomson and Porter in the context

of knowledge representation (Clark et al., 2000).

They define “a pattern as a first-order theory whose

axioms are not part of the target knowledge-base,

but can be incorporated via a renaming of the non-

logical symbols” (Clark et al., 2000, p.6). The

intention is to help construct formal ontologies by

explicitly representing recurring patterns of

knowledge, so called theory schemata, and by

mapping these patterns on domain-specific concepts.

Staab (Staab et al., 2001) investigated the use of

so called “semantic patterns” for enabling reuse

across languages when engineering machine-

processable knowledge. Semantic patterns consist in

this approach of one description of the core elements

independent from the actual implementation and for

each target language a description that allows for

translating the core elements into the target

language. Compared to knowledge patterns,

semantic patterns try to separate engineering

knowledge from language-specific implementations

instead of theories from domains they are applied in.

Knowledge formalization patterns have been

proposed by Puppe as rather simple templates

proven in practice for the (mass) formalization of

knowledge (Puppe, 2000). Puppe puts a lot of

emphasis on proven problem solving methods,

which uncover implicit knowledge of experts.

3.2 Organisational Knowledge

In organization theory and management science

different views on knowledge from an

organizational perspective have been published and

discussed. One important dimension often discussed

is the distinction between two types of knowledge,

which is based on the work of Polanyi (Polanyi,

1958): explicit knowledge and tacit knowledge.

Explicit knowledge refers to knowledge that is

codified, i.e. transmittable in a formal representation

or language. Tacit knowledge is hard to formalize

due to its personal quality of “simply knowing how

to do something” in a specific context.

Organizational knowledge includes both, tacit and

explicit knowledge.

In this context, the paper follows the opinion of

Nonaka that an organization cannot create

knowledge without individuals, i.e. at a fundamental

level, knowledge is created by individuals (Nonaka,

1994). The organization supports individuals and

provides a context for knowledge creation.

Organizational knowledge creation includes

processes that organizationally amplify the

knowledge created by the individuals and

crystallizes it as part of the knowledge network of

the organization.

Spender (Spender, 1996) discusses the term

organizational knowledge from a perspective of

organizational science and management science. The

article comes to the conclusion of two parallel views

on organizational knowledge. The first one

separating the notion of knowledge from learning

and memory, which essentially leads to a perception

of knowledge as an asset of the organization, with its

implicit conservation or constancy in quantity. The

second view perceives knowledge as public good

whose quantity and value is not diminished by

sharing it and as a subject to extension and reshaping

rather than conservation. Spender states that “Assets,

as resources, are compounded with knowledge about

their use, knowledge of a different type.”

3.3 Organisational Knowledge Patterns

As motivated in the introduction, organizational

knowledge patterns should combine technical

features and cognitive quality and in an ideal case be

easy-to-understand and easy-to-deploy. With easy-

to-understand we address the challenge of providing

knowledge to individuals in a way which for their

context of use has the appropriate presentation and

quality and thus eases the internalization of

knowledge. With easy-to-deploy we target a

representation of the knowledge which is adaptable

to a specific organizational context and formalized

or specified in a way that eases the provision of IT

solutions supporting the knowledge use. As a

contribution to promote these features, we propose

to extend by Clark’s knowledge patterns by

supporting more explicitly the focus on providing

characteristics for organizational knowledge. In this

context, we define the term organizational

knowledge pattern as follows:

An organizational knowledge pattern is a

formalization of knowledge for a recurring

organizational task abstracting from organization-

specific aspects, which is of value for an

organizational actor and an asset for an

organization.

In the context of this definition, the following

characteristics of organizational knowledge patterns

(OKP) have to be emphasized:

• OKP need to represent organizational

knowledge, not individual knowledge, i.e.

support the organizational knowledge creation

process, the organizational context for use of

knowledge by individuals as opposed to

supporting knowledge creation of an individual.

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• OKP address recurring organizational tasks and

at the same time abstracting from a specific

organization, i.e. like most other kinds of

patterns in computer science is the description

of the core elements independent from the actual

solution for an organization.

• OKP are expressed in a formalized way, which

requires a formal language or at least a

structured representation. Thus, OKP are

explicit knowledge.

• OKP are an asset of the organization, i.e. are not

only a resource as such but capture knowledge

about the resource’s use. This means they do not

only capture how to use the pattern (as for many

computer science patterns) but how to use the

resource.

• An OKP is of value for an organizational actor

in its original form and / or its adaptation for a

specific organization.

• The cognitive and technical quality of an OKP is

adequate for the stakeholders, i.e. the OKP are

developed and described for a defined context of

usage with identified stakeholders.

We propose to use the term organizational

knowledge pattern in order to emphasize that

explicit organizational knowledge is represented and

on the other side the technical quality of knowledge

patterns is reached. Furthermore, the intention is to

expose from an organizational perspective the

weakness of today’s knowledge pattern types and

the discussion in the knowledge representation

community. At the same time the value and the

suitability of today’s knowledge pattern

developments as a basis for considerations from an

organizational perspective.

4 REUSABLE

ORGANISATIONAL

KNOWLEDGE

Reusing organizational knowledge has been subject

of research activities for many years. Two

approaches for capturing organisational knowledge

were selected for further discussion in this paper and

shall be presented in this section: task patterns

(section 4.1) and ontology design patterns (4.2.).

These developments were selected since they use

different perspectives on organisational knowledge,

and since they have already been used outside

academia in an organisational context.

4.1 Task Patterns

The concept of task pattern is a result of the EU-FP6

project MAPPER. In this project, collaborative

engineering was supported by adaptable models

capturing best practices for reoccurring tasks in

networked enterprises. These best practices were

represented as active knowledge models using the

POPS* perspectives. Active knowledge models are

visual models of selected aspects of an enterprise,

which cannot only be viewed and analyzed, but also

executed and adapted during execution. The POPS*

perspectives include the enterprise’s processes (P),

the organization structure (O), the product developed

(P), the IT system used (S) and other aspects deemed

relevant when modelling (*).

The term “task patterns” was introduced for

these adaptable visual models, as they are not only

applicable in a specific company, but are also

considered relevant for other enterprises in the

application domain under consideration. Task

pattern in this context is defined as “self-contained

model template with well-defined connectors to

application environments capturing knowledge

about best practices for a clearly defined task”

(Sandkuhl, 2010). In this context, self-contained

means that a task pattern includes all POPS*

perspectives, model elements and relationships

between the model elements required for capturing

the knowledge reflecting a best practice. Model

template indicates the use of a well-defined

modelling language and that no instances are

contained in the task patterns. Connectors are model

elements representing the adaptation of the task

pattern to target application environments.

The representation of a task pattern consists of

the description of the problem addressed by the task

pattern, a knowledge model proposing a solution for

the problem addressed, and a rationale behind the

solution, i.e. an explanation about the most

important preconditions, principal results and most

important work steps.

4.2 Ontology Design Patterns

In a computer science context, the aim is to

efficiently produce high quality ontologies as a basis

for semantic web applications or enterprise

knowledge management. Despite quite a few well-

defined ontology construction methods and a

number of reusable ontologies offered on the

Internet, efficient ontology development continues

to be a challenge, since this still requires a lot of

experience and knowledge of the underlying logical

ORGANIZATIONAL KNOWLEDGE PATTERNS - Definition and Characteristics

233

theory. Ontology Design Patterns (ODP) are

considered a promising contribution to this

challenge. In 2005, the term ontology design pattern

in its current interpretation was mentioned by

Gangemi (Gangemi, 2005) and introduced by

Blomqvist and Sandkuhl (Blomqvist and Sandkuhl,

2005). Blomqvist defines the term as “a set of

ontological elements, structures or construction

principles that solve a clearly defined particular

modelling problem“. Ontology design patterns are

considered as encodings of best practices, which

help to reduce the need for extensive experience

when developing ontologies, i.e. the well-defined

solutions encoded in the patterns can be exploited by

less experienced engineers when creating ontologies.

The two types of ODP probably receiving most

attention are logical and content ODP. Logical ODP

focus only on the logical structure of the

representation, i.e. this pattern type is targeting

aspects of language expressivity, common problems

and misconceptions. Content ODP often are

instantiations of logical ODP offering actual

modelling solutions. Due to the fact that these

solutions contain actual classes, properties, and

axioms, content ODP are considered by many

researchers as domain-dependent, even though the

domain might be considering general issues like

‘events’ or ‘situations’.

5 DISCUSSION

After defining the term of organizational knowledge

patterns in section 3.3, the purpose of this section is

an application of the characteristics and their initial

validation by investigating to what extent the

patterns type presented in section 4 is an

organizational knowledge patterns. Furthermore, we

will briefly discuss whether or not the concept of

organizational knowledge patterns helps to achieve

reusable knowledge easy-to-understand and easy-to

deploy. Table 1 shows the characteristics of OKP

introduced in section 3.3 and to what extent task

patterns show these characteristics. The purpose of

this comparison is to illustrate the borderline

between knowledge patterns and organization

knowledge patterns. Not only offering reusable

organizational knowledge, but also making the

context of its use explicit, requires the inclusion of

the task to be performed. Task patterns meet this

characteristic, ontology design patterns do not. All

other characteristics are equally met by both

developments.

The

table also illustrates some of the future

Table 2: Comparing task patterns and ODP based on

characteristics of OKP.

Characteristic of

OKP

Task Pattern

Ontology Design

Pattern

For an organizational

task

Task patterns are

capturing specific

organizational tasks

Ontology design pattern in

general do not address

tasks, but capture best

practices for “engineering

ontologies”.

Are recurring

Task patterns were

developed with the

intention to be reused in

various enter-prises;

reuse has been reported

in some cases

Ontology design patterns

are available for reuse and

numerous cases of reuse

have been reported

Abstracting from

organization specific

aspects

Task patterns need to be

configured and adjusted

for the target

organization, i.e. the

pattern provides an

abstraction from a

specific organization

Ontology design patterns

need to be configured and

adjusted for the target

ontology, i.e. the pattern as

such provides an

abstraction from a specific

solution

Formalization of

knowledge

Task patterns are

formalized in a

modelling language

Ontology design patterns

are captured in ontology

languages

Asset for organization

The evaluation of task

pattern use confirmed

economic advantages for

the organizations using

them. An investigation

whether task patterns are

considered an asset was

not performed yet.

In organizations

developing or using

ontologies, we expect this

characteristic to be met.

However, an investigation

towards this aspect was not

performed yet.

Of value for an

organizational actor

The evaluation of task

patterns shows

acceptance by the actors

involved, i.e. it is

assumed that they are of

value for them

Ontology design patterns

are expected to be of value

for ontology engineers, i.e.

in organizations

developing or using

ontology, this

characteristics will be met

Stakeholder adequate

quality

The evaluation of task

pattern showed adequate

quality for both,

IT-experts and

organizational

stakeholders.

The quality is deemed to

be considered adequate for

ontology engineers.

research needs. To validate the characteristics of

being of value for an organizational actor and an

asset for the organization requires additional efforts

and probably a new perspective in validation.

The main difference between knowledge patterns

(section 3.1) and organizational knowledge patterns

is the organizational focus, which is emphasizing the

importance of also representing the context of

knowledge use in order to be able to reduce time-to-

KMIS 2011 - International Conference on Knowledge Management and Information Sharing

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solution. The lessons learned from task pattern use

and the positive results of the economic evaluation

in this context (Sandkuhl, 2010) are supporting this

perspective but are far from sufficient. Much more

and systematic evaluation has to be performed.

The ambition of organizational knowledge

patterns to be easy-to-understand has to be discussed

in the context of the intended use of these patterns.

Aiming at organizational knowledge management,

different groups of stakeholders are involved,

including business professionals applying the

context part and IT specialists using the technical

part of the patterns. Involvement of non-IT-

professionals in model development and use and

effects of notation on model understanding have

been subject to numerous research activities. There

is an opinion that visual models with stakeholder

adapted terms and language extensions increase

pragmatic quality. This view supports our proposal

to apply visual modelling languages. Again, more

work is needed.

6 SUMMARY AND FUTURE

WORK

The work presented addresses the subject of

organizational knowledge patterns as contribution to

systematic development and reuse of organizational

knowledge. The contributions of this paper are the

definition of the term organizational knowledge

pattern in relation to other pattern types from

computer science, to identify characteristics of such

patterns, and to examine task patterns and ontology

design patterns in order to expose the key features of

organizational knowledge patterns.

One of the purposes the definition of

organizational knowledge patterns was to make

explicit what the commonalities and what the

differences to related terms in knowledge

engineering are. Organizational knowledge patterns

and established knowledge patterns show a number

of commonalities, like separation of structure and

solution, capturing of recurring knowledge, or use of

formalization. Future work on organizational

knowledge patterns will benefit from having these

commonalities in mind and of trying to apply and

transfer experiences from knowledge pattern use to

organizational knowledge patterns.

From a computer science perspective, sound and

fairly mature technological concepts for representing

and deploying knowledge patterns exist, but more

attention should be paid to organizational aspects,

like business value and deployability.

Further work has to be spent on refining the

requirements of patterns being easy-to-understand

and easy-to-deploy. The concept of being easy-to-

understand could be refined by using work from

model quality or the physics of visual languages. For

easy-to-deploy, classifications for the formalization

of models and specifications, like the differentiation

between executable and enactable, would be relevant

when detailing this concept.

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