Empowering the Knowledge Worker

End-User Software Engineering in Knowledge Management

Witold Staniszkis

Rodan Development, Wyczółki 89, 02-820 Warszawa, Poland

Keywords: Knowledge Management, End-User Software Engineering, Dynamic Workflow, Semantic Content

Modelling, Knowledge Maps, Adaptive Case Management.

Abstract: We present a novel architecture of a knowledge management system meeting the end-user software

engineering requirements, thus empowering the knowledge worker to eliminate such intermediaries as

system analysts and application programmers. Advantages of direct representation of user requirements in

executable knowledge management application specifications, as well as the resulting system agility and

ease of maintenance is highlighted. The state-of-the-art in the end-user software engineering area pertaining

to the knowledge management systems realm comprises information about the on-going research and

development efforts. The principal features of a knowledge management system toolbox are described,

comprising among others such functional areas as semantic modelling of knowledge object repositories, and

adaptive management of knowledge management processes. Finally we succinctly discuss the end-user

oriented methodology guiding specification of the knowledge management application solutions.

1 INTRODUCTION

Rapid growth of international trade and cooperation

on the one hand and the global Information and

Communication Technology (ICT)-driven

communication powered by the Internet have fuelled

unprecedented expansion of global collaboration in

practically all walks of human activity. Virtual

organisations spanning not only diverse countries

but also the entire regions become an ubiquitous and

dynamic phenomenon. A good example are the

European research programmes based on

international project consortia, i.e. virtual

organisations, characterised by well-defined goals to

be attained within a specific time frame.

Also the nature of human activities has

undergone a dramatic change resulting in more than

50% of workers being classified as “knowledge

workers”, a termed coined by Peter Drucker over

half of century ago, whose productivity underlies the

competitive advantage of all developed economies.

Indeed, again according to Peter Drucker (Drucker,

1999), productivity of the knowledge workers

represents the major management challenge of the

century.

Notwithstanding the ubiquity of such ICT

environments as networking, email, social media

and content management enhancing the capability of

goal-oriented collaborating teams, jointly known as

organization 2.0 platforms, much needs to be done

to leverage investment in intellectual capital

represented and produced by the knowledge

workers.

A survey of knowledge worker activities

reported by Nathaniel Palmer (Palmer, 2014) reveals

that over 60% of the working day is spent in

unstructured and often unpredictable work patterns.

This telling result explains, at least partially, the

common fallacies of the business process

management (BPM) projects aiming at supporting

human collaboration within the knowledge-intensive

work activities. Clearly a novel approach is needed

to support the non-production (in the Fredric Taylor

sense) work processes of the knowledge worker.

The major advantage of the end-user-driven

design and development of the knowledge

management application solutions is the elimination

of intermediaries, such as system analysts and

application programmers, thus enabling the direct

representation of the user requirements in executable

application specifications. Direct involvement of the

end-users in the development process leads to

increased system agility and ease of maintenance.

The ubiquitous cloud environments provide

Staniszkis W.

Empowering the Knowledge Worker - End-User Software Engineering in Knowledge Management.

DOI: 10.5220/0006806400010001

In Proceedings of the 17th International Conference on Enterprise Information Systems (ICEIS 2015), pages 7-19

ISBN: 978-989-758-096-3

flexibility, and relative low cost, of computing and

storage resources, that can be readily obtained and

easily adjusted to the current application workload.

All of the above characteristics are a perfect match

for the requirements of the transient and goal-

oriented knowledge management application

solutions.

The non-IT users of the knowledge management

development tools should be able to design and

implement fully functional knowledge management

solutions comprising a repository of information

objects organized according to a semantic model,

providing the principal view of the repository

information to the system users, as well as the

process management functionality supporting

execution of the knowledge workers’ procedures and

tasks.

The substantial impact of the end-user

development is exemplified by data published by the

US Bureau of Labour and Statistics in 2012, quoted

in (Ko, 2011), showing that there have been in the

United States fewer than 3 million professional

programmers but more than 55 million people are

using spreadsheets and databases at work, many of

whom write formulae and queries to support their

job.

A significant challenge in involving non-IT

professional developers creating complex

application solutions, notwithstanding the scope of

automated development tools support (e.g.

application generating wizards), is the notorious lack

of sound software engineering practices, such as

quality assurance of produced solutions, which often

precludes sufficient reliability and robustness of the

resulting applications.

Our research and development work in the area

of the knowledge management software tools

initiated within the ICONS FP5 research project

(ICONS, 2000) and further expanded within the

eGovBus FP6 research project (eGovBus, 2008), as

well as the ensuing engineering of the research

results resulting in development of the

OfficeObjects® knowledge management platform

(OfficeObjects, 2010), provided us with the solid

basis for design, construction, and implementation

of agile end-user-oriented knowledge management

application solutions.

OfficeObjects® is a proprietary JEE (Java

Enterprise Edition) framework integrated with

several specialized community open source

components supporting such functionality as fill text

search, business intelligence and reporting, and the

portal environment.

In the following sections we discuss the principle

user requirements, defining the functional scope of

the knowledge management software tools and the

underlying application development methodology,

which had provided the guidelines for design and

development of the OfficeObjects® knowledge

management software tools, as well as the pertinent

state-of-the-art research and development results.

Further we succinctly present the end-user-

oriented development features of the

OfficeObjects® architecture highlighting the

strengths and challenges of the knowledge

management software tools, and finally we present

the end-user oriented development methodology.

2 THE KNOWLEDGE

MANAGEMENT APPLICATION

REQUIREMENTS

The challenges facing knowledge workers,

particularly those having direct negative effect on

their productivity, have been identified in the

already mentioned study performed by Nathaniel

Palmer (Palmer, 2014) repeatably in 2011 and 2013.

Table 1 summarizes the results obtained in the 2013

survey, where column “%” provides the proportion

of respondents giving the positive answer, and the

remaining columns refer to the KMS feature areas,

shown in Figure 1 relevant to the corresponding

challenge.

The analysis results clearly indicate the

relevance of the “Content Repository” features to

alleviating obstructions impeding the knowledge

worker productivity, immediately followed by such

feature areas as “Workflow Process Management”

and “Knowledge Representation”.

The KMS feature model has been introduced in

(ICONS, 2002), serving subsequently as the road

map of the OfficeObjects® development project,

undergoing revisions motivated by experience

derived from a number of large scale knowledge

management applications. Another important lesson

learnt in the course of these projects was the utmost

importance of empowering the KMS end-users to

ensure their active participation, not only in the user

requirements analysis, but first of all in the KM

solution development and maintenance processes.

The rapidly growing end-user software

engineering (EUSE) field, as presented in section 3,

has also influenced the focus of the OfficeObjects®

software architecture design to embrace the EUSE

techniques and methodologies. The user-oriented

Table 1: Knowledge worker challenges vs. the KMS features.

Knowledge workers’ challenge */ % 1 2 3 4 5 6

Lack of visibility into the current state or status

of others’ work supporting your own

X X X X

Difficulty tracking “to do” items or task lists

X X

Difficulty organizing and assembling the right

team

X X X

Difficulty managing documentation and

information needed for a given project

X X

Difficulty finding co-workers/collaborators with

the right experience

X X X X

Difficulty determining the next step or course of

action

X X X

1. Enterprise 2.0 Ontology

2. Knowledge Representation

3. Content Repository

4. Workflow Process Management

5. Enterprise 2.0

6. Knowledge Integration

*/ (Palmer, 2014)

Figure 1: Feature requirements of the Knowledge Management System.

assessment of the eGovernment service bus system

(eGovBus2008) developed with the use of the

OfficeObjects® platform, in particular of its service

design and development tools, has shown that non-

programming IT technicians were able to develop

complex services published in the Web.

The ensuing development of the subsequent

versions of the OfficeObjects® platform has been

concentrated on the ergonomic aspects of end-user

interfaces, both in the area of application solution

development tools, and the functional system areas,

such as the content repository, workflow process

graphic interfaces, and the HCI features.

The existent and emerging software standards

pertaining to the OfficeObjects® platform have been

incorporated in the software design in order to

facilitate high acceptance level of the end-users and

IT professionals, as well as to support

interoperability with information systems and data

sources that may be integrated within the knowledge

management application solutions.

3 THE KMS RESEARCH

ACTIVITIES

The architecture of knowledge management

systems is a field of intensive research and

development effort. Notwithstanding the research

and innovation currently under way, the

comprehensive integrated end-user development

tools supporting agile development of advanced KM

application solutions are rarely meeting the

advanced knowledge management system

requirements. Apart from the OfficeObjects®

platform (OfficeObjects, 2008), the closest example

is a prototype of the knowledge management

platform presented in (Langenberg, 2011).

Analogously to our approach, the above authors

propose a distributed platform replicating functional

components to achieve load balancing effect under

the varying workload conditions. Also the virtual

organizations, possibly involving several

independent partners, are envisaged as the prime

users of the proposed system. The system is

supporting advanced content management solutions,

but it does not provide application development

tools oriented towards the end-user software

engineering community. System security is a

significant concern in knowledge management as

well as general collaborative systems, these issues

are discussed at length in (Ruiz, 2011) and (Tolone,

2005) respectively.

The End-user Software Engineering (EUSE)

field has been growing significantly over the last

several years, evolving from the spreadsheet

financial models, through the graphic user interface

implementations, to the end-user developed mashup

applications. The Service-oriented Architecture

(SOA), providing an integration platform for

accessing domain-specific application environments,

has enabled development of complex and robust

applications by non-programmers.

It is the common believe that the knowledge

management application design and specification

tools are to provide an abstraction level concealing

the underlying technological complexity of a KMS

platform, thus enabling the end-user developer to

concentrate on the application requirements of the

KM solution. A comprehensive overview of current

end-user development tools has been presented in

(Ko, 2011). The field has been growing considerably

over the last several years and a number of important

research initiatives have been published. A

composition model facilitating the programming-

illiterate knowledge workers to develop rich internet

applications, integrating pre-existing software

components to be published in a graphic web

interface (a mashup), has been presented in

(Lizcano, 2011). Other mashup frameworks bridging

the perspective of the service based software

development and the end-user development have

also been presented in (Mehandjiev, 2012 and

Nestler, 2011).

Development of Web 2.0 tools and techniques

has enabled end-users to move from content and

personalization to functionality in the direction of

user-developed web services. A number of such

projects, spanning from ambient intelligence,

through to wizard-based process development, have

been presented at the AVI Workshop held in Rome

on May 25-29 2010 (Costabile, 2010). The use of

design patterns in the end-user development projects

has also been growing as presented in (Verginadis,

2010). A good example of a design pattern

repository is the MIT process library described in

(Malone, 2003).

Semantic knowledge content modelling,

similar to the OfficeObjects® knowledge map

approach, has been proposed in (Doerr2008). Yet the

platform, serving the cultural heritage applications,

is a closed software system providing no

development tools for the system users. The

corporate knowledge management domain is

represented by an advanced prototype of a

knowledge management system SKMS (Smart

Knowledge Management System) presented in

(Mancilla-Amaya, 2010). The platform provides a

powerful document structuring mechanism in the

form of dynamic categorization trees, but similarly

to the above solutions, it neither provides tools for

specification of the knowledge management or

scientific workflow processes, nor it allows for

semantic modelling of the knowledge repository

content.

Several KM systems currently under

development are equipped with formal ontology

models in the form of semantic nets, as represented

by the Topic Maps ISO standard (ISO 13250),

mostly supporting semantic browsing features

referencing the repository and external information

objects. An example of Topic Maps-based semantic

net implementation is the DREAM platform

presented in (Badii, 2009) utilized for semantic

indexing and search of visual objects. Topic Maps

are also used for categorization of documents on the

basis of their meta-data attribute values. Examples

of such architectures may be found in (Cahier2010)

as well as in (Damen, 2009, Park, 2008, Vatant,

2001).

The role of an ontology model in the knowledge

management system has been extensively discussed

in (Davis, 1993, van Harmelen, 2007). It is generally

agreed that an ontology specification language can

be seen as a knowledge representation language,

which should guarantee that every concrete ontology

enjoys the following properties: (i) it is a surrogate

for the things in the real world; (ii) it is a set of

ontological commitments; and (iii) it is a medium

for human expression. In other words, an ontology

may be specified without any particular reasoning

paradigm in mind, and it does not necessarily have

to be a theory of representational constructs plus

inferences it recommends, or a medium for efficient

computation.

Many tailor-made ontology specification

languages have been defined so far. In the context of

the DARPA Knowledge Sharing Effort, for

example, Gruber defined Ontolingua (Gruber,

1993). Such a language was developed as an

ontology layer on top of KIF (Ginsberg, 1991),

which allowed frame style definition of ontology

models (such as classes, slots, and subclasses). Other

languages, such as Conceptual Graphs (Sowa, 1976,

van Harmelen, 2007), have also been popular for

specifying ontologies.

Recently, the XML-based W3C Web Ontology

Language (OWL) (OWL, 2007, van Harmelen,

2007) has gained wide popularity. The language is

characterized by very high expressiveness, but to get

some guarantees with respect to computability, a

user has to limit herself to a well-understood

fragment of OWL, called OWL DL, based on

Description Logics (DL) (Baader, 2001, Calvanese,

2001, Baader, 2003, van Harmelen, 2007).

The Human Computer Interaction field

enriched by ubiquity and growing computing power

of mobile devices, such as smartphones and tablets,

as well as the new mobile context-aware software

standards exemplified by HTML5, open a vast field

for new intelligent applications based on knowledge

management systems, such as the OfficeObjects®

platform. Development of the graphic user interface,

as well as configuring of the mobile device apps

serving as clients, represents important challenges of

the end-user KM application development. The field

is rich with research projects concentrating on issues

of automatic generation of mobile device graphic

interfaces on the server side, as described in

(Chmielewski, 2010, Lakshman,, 2011, Walczak,

2012), as well as the component-based end-user

development of complex graphic interfaces

integrating heterogeneous data sources and

application functions, such as mashups described in

(Lizcano, 2011, Mehandjiev, 2012).

The Ambient Intelligence field is a growing

application area to be supported by the end-user

software development tools, like those available in

the OfficeObjects® platform, either as a new

solution development by parameterization of the

existing design patterns, or as an application of the

off-the-shelf components. Examples of such

application solutions have been presented in

(Aggarwal, 2011, Lee, 2012).

Workflow management platforms available in

the Cloud computing realm are subject of many

research efforts, and consequently quite widely

published, in particular in the eScience area. Many

projects concentrate on workflow tools and run-time

platforms supporting scientific workflows moving

vast amounts of data resulting from scientific

experiments. Automation of data interchange is a

subject of many publications in particular related to

the field of HPC (High Performance Computing),

among others interesting results are presented in

(Juve, 2010, Shams, 2010, Vockler, 2011, Zinn,

2011).

All of the presented system prototypes use the

workflow management platforms as a middleware

layer responsible for coordination of scientific

computation tasks, providing facilities for parallel

scheduling of complex computations and passing

intermediate result data among such computations.

Ubiquity of these solutions in the scientific

computation community bodes well for other

application areas, such as among others the

knowledge management field.

New workflow paradigms are being proposed in

response to the growing need to support and

measure efficiency of the knowledge work. Working

methodologies, such as SCRUM for example, are

becoming ubiquitous not only in the software

development work. One of the significant proposals

of the new workflow paradigm is the Role Model

developed by Keith Harrison-Broninski (Harrison,

2005, Harrison, 2012).

A set of lightweight methods called "agile" are

being developed in recent years (OfficeObjects,

2010) to better fit the dynamic nature of projects and

organizations. Agile methods adopt a dynamic

process control model, which is meant for processes

that are not always well defined and are sometimes

unpredictable and unrepeatable.

A comprehensive discussion of the scientific

workflow models is provided in (Talia, 2013)

highlighting a number of issues that are still open.

Amon others, the outstanding problems include (a)

adaptive/dynamic workflow models. (b) service-

oriented workflows on cloud infrastructures. (c)

workflow provenance and annotation mechanisms

and systems.

Adaptive Case Management (ACM) is a fast

growing area of management innovation, rather than

computer science research, fuelled by the widely

believed constatation that the classic graph-oriented

workflow models are incompatible with the nature

of knowledge work. A convincing proof is provided

by the quoted above results of a survey conducted by

Nathaniel Palmer (Palmer, 2014), as well as by

explicit calls for a BPM paradigm shift presented in

(Bider, 2014, Silver, 2011, Swenson, 2014).

Additional argumentation, calling for a major

overhaul of the presently available workflow process

and content management architectures, may be

found in (Matthias, 2011, McCauley, 2010, Palmer,

2011, Palmer, 2012, Pucher, 2010, Pucher, 2012,

Swenson, 2010, Swenson, 2011, Swenson, 2012).

Another important line of thought presented in

(Khoyi, 2010a, Khoyi, 2010b, Kraft, 2010) is the

data orientation of the ACM platforms stressing

importance of the rich knowledge object repository

structures and the semantic modelling as the

principal vehicle for the knowledge work support.

Indeed for a growing engineering field anchored in

purely practical issues, the intensity of general

interest, exemplified by the number of publications,

is astonishing. In fact, this vouches for the real

practical impact of knowledge worker efficiency, as

stated by Peter Drucker at the turn of the 20

century (Drucker, 1999).

The ACM field, notwithstanding its practical

flavour, attracted also attention of the computer

science research community approaching the

existing issues from a theoretical vantage point. One

of such projects, initiated at the Sorbonne University

in Paris has been presented in (Rychkova, 2014).

4 THE OfficeObjects® KM

ARCHITECTURE

The OfficeObjects® software architecture, presented

in Figure 2, has been evolving over the last 4 years

to provide the comprehensive set of features

required for the knowledge management application

development. As we stressed in the preceding

discussion, the end-user orientation has been the

major focus of our design and development effort.

The presented software architecture meets the

application requirements included in the knowledge

management feature model shown in Figure 1.

The OfficeObjects® functional modules are

deployed within three principal packages installed in

the virtualized processing environment. The user-

visible functionality, representing the application

solutions, is deployed within the JSR 286 Portal

Framework (Liferay2009) providing a rich and

mature environment for the end-user-oriented mush

up application development.

A rich and extensible library of portlets supports

the state-of-the-art Enterpise 2.0 solutions packaged

within the Static Content Management Area. The

portal administration tools are available within the

Portal Administration Tools pages. Both

functional areas render themselves readily for the

end-user software development, which is usually

based on the use of assorted web applications.

The knowledge management functionalities,

comprising the OfficeObjects® components, as well

as the integrated open source software components,

such as the community Jaspersoft report server

incorporating the Mondrane ROLAP engine

(Pentaho2009) executing the Multidimensional

Expressions (MDX) analytical language

(Spofford2001). The above functionalities may be

deployed as portlets, depending on the knowledge

management solution requirements, within the

Knowledge Management Repository and the

Business Intelligence (BI) Analytics areas.

The Knowledge Management Repository

publishes all OfficeObjects® services dedicated to

content, process and ontology management. An

important knowledge management tool the

Knowledge Map, based on the Topic Maps ISO

12350 standard, supports creation and delivery of

semantic models, superimposed on the knowledge

repository content, providing semantically enriched

knowledge artefact navigation and selection

functionality. A knowledge map may comprise

references to the repository information objects as

well as to the external information objects, such as

web pages, Wikipedia entries, database queries etc.

The knowledge maps and the dynamic object

categorization trees used in advanced knowledge

management systems prove to be intuitive and user-

friendly.

Figure 2: OfficeObjects® Platform Architecture.

The KMS features concerned with integration of

external knowledge resources, data, and services

may by supported by the OfficeObjects® Service

Broker module facilitating deployment of complex

services within the Portal Framework developed

with the use of OfficeObjects® tools and deployed

on the OfficeObjects® WorkFlow platform.

The Ontology model, supported by the Topic

Maps Ontology Navigator, comprises all

information concerning the KMS organizational

environment, such as the organization structure, user

accounts and access rights, role models, etc., as well

as the semantic model features comprising

controlled vocabularies, data dictionaries,

information object class specifications, and the

knowledge map definition.

All of the above components of the run-time

OfficeObjects® architecture are supported by the

OfficeObjects® Tool Box components providing

design and development functions for the users

specifying a knowledge management application

solution. The Process Design Tool coupled with the

Form Editor provide tools to specify the workflow

process BPMN model and the corresponding process

GUI. The Knowledge Map (KM) Modeller may be

based on any available UML Class Diagram tool

producing the XMI notation to be subsequently

processed by the OfficeObjects® Ontology Manager

module and mapped into the ontology structure to

form a Knowledge Map definition.

The scope of design specifications supported by

the Tool Box components becomes apparent in the

context of the design decision trees, discussed in

section 5.

The MDX Workbench, the Extract-

Transform-Load (ETL) Workbench, and the

Report Editor, are used to develop data marts, and

the associated ROLAP models, within the integrated

Business Intelligence solution. Although, all of

these tools require data analysis skills, they may be

used by no-IT personnel, hence they fall into the

broad class of the EUSE tools.

The underlying data Storage package represents

systems and facilities, such as data base

management systems, file systems, web services,

and web pages, that may be referenced to select and

retrieve information objects accessible via the

Knowledge Management Repository reference

structures.

The workflow process instances managed on

the OfficeObjects® WorkFlow platform are stored

in a WfMC run-time meta-model format. Event data

Figure 3: OfficeObjects® Repository Data Model.

resulting from execution of workflow process

instance is recorded in the form of process logs,

which subsequently may be used to generate process

execution reports and ROLAP models. The

workflow process definitions are available via the

OfficeObjects® Process Design Tool and may be

exported/imported with the use of the WfMC XPDL

notation.

The OfficeObjects® Repository data model is

presented in Figure 3 as a UML Class Diagram of

information resources coupled with a set of

interfaces representing the repository referential

structure. The repository contains instances of

information object classes, where an object may

belong to only one object class characterized by the

meta-data model. The physical structure of an

information object instance, i.e. the number, size and

type of binary objects (files), stored in an object is

completely arbitrary, thus independent of the

corresponding information object class.

The semantics of a repository are dependent on

its referential structure, i.e. on information object

classification and assignment to respective object

collections. The classification and assignment

actions are subdivided into three principal modes,

namely the Automatic mode, the Manual mode,

and the Knowledge Map mode. The last variant

may be considered a variation of the Automatic

mode.

The automatic collection represents the

following object collection semantics; (a) Full Text

Retrieval pertain to the entire population of all

information classes automatically indexed and made

eligible for retrieval on the basis of their textual

content, (b) the remaining three automatic

collections, i.e. the Categorization Tree, the Meta-

data Search, and the Register, pertain to the

population of one class only. The categorization

trees support a hierarchical access path to

information objects selected on the basis of a

sequence of meta-data attribute values, and the

registers are chronological ordering of objects within

the corresponding class and sub-class defined by a

selection predicate defined on the meta-data

attributes.

The manual collections, such as the case files or

repository folders, represent a manual, information-

bearing classification process, since most often the

allocation activity may not be reproduced on the

basis of meta-data values. In fact, the allocation

decisions are implemented by direct user actions.

However, in some applications it may be possible to

perform such allocations automatically, if

appropriate information, such as for example the

case file identifier, are present in the meta-data of

the information object to be categorized.

The knowledge map is constructed and

maintained automatically, controlled by the

construction rules, defined on the meta-data

attributes, and the appropriate mapping rules. The

mapping rules decide, which meta-data attributes are

to be represented in the corresponding knowledge

map topics (nodes), and the construction rules

determine the relationships maintained among the

knowledge map topics, thus establishing the required

transversal path within the map.

5 THE KMS SOLUTION

END-USER SPECIFICATION

METHODOLOGY

We have selected two knowledge management

application design and specification areas to

illustrate the merits and limitations of the

OfficeObjects® application development tools, in

particular their eligibility for the end-user. We need

to make a reservation, that we expect the computer

literacy of the end-user system developer, often such

a role being called the power-user, at least on the

level of an expert spreadsheet user or a personal

database user. As we mentioned before, such

qualifications are ubiquitous among the

professionals using computers for their work.

We concentrate on two principal design areas of

the knowledge management system functional

spectrum, namely on the knowledge repository and

workflow management platform, shown in Figure 4

and Figure 5 respectively. A convention used in both

mind maps is the

X symbol meaning that the

decision branch and all descending children are

ineligible for the end-user, due to their complexity

calling for the professional IT skills.

The Repository Semantic Level includes all

design decisions, either pertaining to the conceptual

model of the repository knowledge resources, or to

the underlying data structure specifications

providing the building blocks for the higher level

constructs, such as the meta-data specifications of an

information object class. Design specification, which

we believe might be too complex for the non-

programming user, are the categorization tree

materialization queries, since they require advanced

SQL operations such as JOIN and GROUP BY

queries.

All of the other design specifications pertaining

to the semantic modelling of the knowledge

resources, such as the automatic assignment

predicates aligning information objects within the

target referential objects, such as Registers and

Case Files, are well within the grasp of a power-

user. All in all, it is quite possible, that the power-

users define a complex repository data model, albeit

some OfficeObjects® methodology and tools

training is advisable.

On the other hand, definition of the Repository

Storage Structure Model requires decisions calling

for specialized data management skills, hence

usually rests beyond capabilities of even advanced

power-users. The solution here is to apply default

physical data structure configurations, pre-

configured in the software distribution version,

offering good performance support for typical

repository use patterns.

The Knowledge Map Model is a critical feature

for most knowledge management applications

supporting semantic views over the information

objects stored in the knowledge repository.

Superimposing a class diagram model over the

Topic Maps ontology, and maintaining references

between topics and information objects, allows the

repository user to select and manipulate the

knowledge resources, i.e. the information objects,

according to a domain-oriented semantic data model.

Navigation in the network of binary topic

relationships, linking internal and external

Figure 4: OfficeObjects® Repository specification decision tree.

knowledge artefacts, constitutes a powerful search

platform guiding navigation along the associative

selection paths.

The knowledge map design may proceed in a

“top down” manner, starting from the UML Class

Diagram referencing the information object classes

and linking them with appropriate relationships, or

using a “bottom up” method, defining the topic

relationships and the associated relationship

predicates directly using the Topic Maps formalism.

The latter method may not be advisable for the

power-users.

The recommended design methodology is to

define the UML Class Diagram of a knowledge map,

tag the relationships with the selected association

predicates defined over meta-data attributes of the

associated classes, and automatically generate the

Topic Maps specifications via the XMI interface.

We also assume that both Dynamic integrity

constraints as well as Data integrity rules and

procedures may be too complex for a non-IT

professional and will require help from the system

administration staff. Notwithstanding the above

limitations, we may safely claim that a working

knowledge management repository may be

designed, specified and maintained by non-IT

professionals possibly supported by system

familiarization rudimentary training.

The second important design area of the

knowledge management application solution

implementation is the Workflow Process Design &

Implementation area. The scope of design decisions

facing the system designer is depicted in Figure 5.

Most of the application specification tools, such the

process graph specification, the graphic user

interface form editor, the functional rule

specification language, and the process participant

role model, have proven to be sufficiently user

friendly to be productively employed by the power

users.

We find that specifying generic workflow

models, employing the dynamic process

modification features (eGovBus2006), may exceed

the capabilities of the power user. On the other hand,

parameterizing such processes, available in the

process pattern library, is quite straightforward and

Figure 5. OfficeObjects® Workflow specification decision tree.

may readily be performed by the users.

In order to address the requirements identified in

section 2, rather than utilizing the BPMN graphical

process model, one may specify the Goal Model

process (OfficeObjects2010) much more suitable for

planning and executing project-oriented activities.

The Goal Model processes are specified as the check

list of all process tasks, the participant assignment

rules for each task, and the dependency graph

representing the precedence relationships among

tasks. Task execution is scheduled only for task that

are not bound within any precedence relationships.

The process goal is met when all tasks have been

executed. Such process specification and

maintenance tasks as interpreting the process

control data tables, for diagnostic and

performance-oriented process design purposes, may

require assistance from the process administration

staff. Also the process application integration

specifications, may either require the power users to

undergo substantial training, or collaboration with

the process administration staff.

6 CONCLUSIONS

The end-user oriented methodology underlying

development of the knowledge management

application solutions has been verified in the course

of a number of application projects. Amon others, a

large-scale knowledge management application

system has been implemented in the period of 2010

– 2012 serving a community of 2000 scientists

working for 20 research organizations.

The knowledge management system is currently

operated as a tool to support network cooperation,

taking into account the requirements of industrial

organizations co-operating within a network of

research institutes according the recommendations

of the Open Innovation model.

The platform, which serves as a tool supporting

communication and cooperation, as well as

providing information on the resources and skills

possessed by the participating organizations,

facilitates their cooperation and the dissemination of

best practices in the area of research work and

management.

The lessons learnt during design and

development of the above system confirm, that all

major application functions were indeed developed

without the recourse to classic application

programming languages, such as Java or C++. The

only hurdle to overcome by the non-programming

developers were the Java Script validation

expressions. Although the power users were

successfully involved in the system development

effort, provision of sufficiently thorough training

materials, as well as technical help available on-line

could significantly improve the implementation

process.

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