Extracting and Maintaining Project Knowledge
Using Ontologies
Panos Fitsilis
, Vassilios Gerogiannis
and Achilles Kameas
Project Management Dept., Technological Education Institute of Larissa,
41110 Larissa, Hellas.
Hellenic Open University, 23 Sahtouri str., 26222 Patras, Hellas
Abstract. One of the most valuable resources for organizations today is
knowledge developed and held within their teams during the execution of their
projects. Although the need for maximal reuse of lessons learned and
knowledge accumulated for keeping companies at the leading edge is evident,
this knowledge is often lost because it can be difficult or impossible to
articulate. k.PrOnto
framework infuses the process of project management
with knowledge management technology and provides project managers with
concepts and tools to support them in decision making and project control. The
tools operate at a stand-alone mode, but, in the context of k.PrOnto architecture,
can also be used as components of a distributed system operating at a higher
organizational level. Thus the k.PrOnto framework assists large organizations in
identifying best practices, metrics and guidelines, starting from individual
projects and in amplifying their efforts to achieve organizational maturity and
build corporate culture and memory.
1 Introduction
In a competitive and fast changing business environment, an organization's ability to
efficiently align resources and business activities with strategic objectives can mean
the difference between succeeding and just surviving. For achieving strategic
alignment, organizations are increasingly managing their activities as projects —in
essence, becoming project-based organizations— in an attempt to monitor
performance more closely and make better business decisions about their overall work
portfolio. By planning and tracking projects with clarity and precision, organizations
can respond with greater agility to the demands of a fast-changing business
Contemporary project management science has become a multi-disciplinary
research field influenced by disciplines as diverse as psychology, pedagogy, business
administration, organization theory, industrial engineering and sociology [22]. The
k.PrOnto framework has been partially funded by the project MISSION-SPM which is co-
funded by the European Social Fund and Hellenic national resources (EPEAEK II/
Archimedes II programme).
Fitsilis P., Gerogiannis V. and Kameas A. (2006).
Extracting and Maintaining Project Knowledge Using Ontologies.
In Proceedings of the 1st International Workshop on Technologies for Collaborative Business Process Management, pages 72-83
discipline of project management has evolved because the more traditional, well-
established industrial age principles and methods for managing our classical
functional organizations (involving on-going, repetitive operations of various kinds)
do not work well for planning, controlling, and managing projects, programs, or
project portfolios. Projects are comprised of diverse tasks that require diverse
specialist skills, and hence cut across the traditional functional organizational lines.
They are temporary endeavors with a finite lifetime and so do not provide stable
organizational homes for the people involved.
Thus, one of the aims of project management is to capture the knowledge
developed before, during and after projects, as, after the project ends, it is usually kept
in the minds of the project teams or hidden in the project deliverables. At the same
time, especially in multi-partner projects, one has to deal with different background
and culture, incompatible procedures and distributed experience, which must be
combined with the need to protect each organization’s procedures and project
k.PrOnto (extracting knowledge using Project Ontologies) is a framework that
applies recent developments in knowledge engineering, software engineering, on
existing project management processes in order to support organizational networking
and process integration and thus assist organizations in improving adaptability and
responsiveness to rapidly changing market demands and customer requirements.
The k.PrOnto framework infuses the project management process with knowledge
management technology and provides project managers with tools to support them in
decision making process and project control. These tools are deployed as components
within a web-based component framework, which enables them to operate at a stand-
alone mode (i.e. a project “dashboard”), or as components of a networked system
operating at a higher organizational level. Thus k.PrOnto framework can assist large
organizations in identifying best practices, metrics and guidelines, starting from
individual projects and in amplifying their efforts to achieve organizational maturity,
to build corporate culture and memory and to establish secure and trusted knowledge-
based collaboration practices with peer organizations, achieving in the end real-time
k.PrOnto provides the infrastructure, so that a project organization can gain
visibility, insight, and control its portfolio of projects, whether they are executed on a
single site, or on multiple distributed sites, either by a single organization or by a
business network. k.PrOnto allows organizations to improve productivity, reduce
cycle times, decrease costs, and increase quality, because it enables them to:
Select projects and programs that are aligned with the organization's strategies and
Make the best use of available resources by applying to the highest priority
Regularly assess how projects and programs are contributing to project portfolio
Take management action to keep the portfolio in compliance with business
In brief, k.PrOnto toolkit supports:
Project managers in the decision making process in real time.
Individual groups in project knowledge exchange across the same organization.
Organizations in the identification of their best practices and metrics targeting to
effectiveness and performance improvement.
Business inter-networking based on project knowledge exchange.
Summarizing, the main objective of k.PrOnto is to provide a project management
specific knowledge management framework that can be used primarily to implement
organization’s project memory and as collaboration tool among different projects and
secondarily as a training tool for complex project cases and scenarios.
In the following sections we outline the project management knowledge areas and
practices, project processes and project information representation, and we present
how k.PrOnto framework is addressing project knowledge management. Finally we
present k.PrOnto high level architecture and we are closing by presenting the
2 Background
The practice of project management has evolved over half a century and permeates all
industries, institutions and governments throughout the world. In response to the
perceived need to organize thinking about project management a number of
frameworks have been produced. Two kinds of frameworks are broadly identifiable,
both of which have sought to model the subject area by presenting only what is
“generally” agreed. These are:
Life-cycle or maturity models. Common examples include the ISO series
(especially BS ISO10006:2003 [5]), “Project Excellence Model” by the
Association of UK Project Managers [30], “Project Management Maturity Model”
[29], the Japanese designed P2M modal and “Projects In Controlled Environments
2 (PRINCE 2)” [25], the family of Software Engineering Institute “Capability
Maturity Models” in general [6], etc.
Bodies of Knowledge. They provide the standards against which would-be project
managers aspire and form the basis for training courses from which such managers
may become certified. More fundamentally, they also provide a knowledge
framework for understanding the elements that comprise project management. In
these areas we have APM Body of Knowledge, PMI Guide to the Project
Management Body of Knowledge [31], BSI BS6079 Guide to Project Management
[4], Japanese Project Management Body of Knowledge. At the same time there are
numerous project management methodologies for software development and
Project processes represent knowledge about software development activities.
Capturing, storing and using process knowledge of an organization has to deal with
several typical characteristics of software development. The fact that we are referring
to software development projects does not limit k. Pronto framework since it could
support other domains such as construction projects provided that relevant ontologies
have been developed.
Processes are inherently nondeterministic, concurrent and distributed. The non-
determinism of processes results from the fact that the sequence of development steps
cannot be predicted in advance. Reasons are the existence of many creative
development steps (e.g. design steps), possible choices among different alternative
paths for plan execution, and product changes triggered from inside or outside the
development organization. Concurrency and distribution of processes result from
interacting development activities that can be performed in parallel. Especially,
outsourcing of development activities and the pressure to incorporate distributed
agents enforces the distribution of tasks to different partners-contractors.
Within process models, metamodels are useful for specifying the concepts, rules
and relationships used to define a family of related methodologies. Although it is
possible to describe a methodology without an explicit metamodel, formalizing the
underpinning ideas of the methodology in question is valuable when checking its
consistency or when planning extensions or modifications. A good metamodel must
address all of the different aspects of methodologies, i.e. the process to follow and the
work products to be generated.
In turn, specifying the work products that must be developed implies defining the
basic modeling building blocks from which they are built [18].
In the software market sector, a number of metamodels have been constructed to
both underpin and formalize methodologies. Examples are: the Object Management
Group’s Software Process Engineering Metamodel (SPEM) [27], the OPEN Process
Framework (OPF) [13], the OOSPICE (developed by a European Commission funded
project) metamodel for capability assessment [15] and the LiveNet [17] approach for
Computer Supported Collaborative Work (CSCW) are the most prominent.
The SPEM was created by the Object Management Group as a de facto, high-level
standard for processes used in object-oriented software development. Initially, it was
created as a stand-alone metamodel but later it was reformulated to be a UML [26]
(Unified Modeling Language) Profile. This means that the authors recast the process-
oriented concepts into model-oriented concepts.
There have been efforts to produce a standard project representation data model
without significant success. Three are the main reasons for this failure: unwillingness
of project management tools providers to collaborate for commercial reasons; lack of
strong technical project management community to push for the development of the
standard; lack of consensus at the level conceptual project modeling.
Further, there have been various attempts from academic institutions [8, 20, 34] to
produce XML Document Type Definitions (DTD) for project modeling.
As result, a project management XML specification [32] has been proposed by
Pacific Edge Software Inc. in 2000 under the auspices of the PMXML consortium.
Primavera Systems, Welcom, eProject.com, Great Plains, PlanView, NASA, Oracle
and others joined the consortium, which maintains the PMXML standard. Using
PMXML standardized schema each compatible application can exchange data with
each other and interpret the data accurately. Currently the standard consists of data
definitions and specifically the four major project management data types (project,
resource, task and assignment) and a few minor ones.
The definition starts with a ProjectManagementSchema and it contains:
InstanceData, a collection of user and application specific data; PoolResources, a
collection of resource definitions; Projects, a collection of project definitions.
From an outsiders point of view the PMXML standard currently seems to be a pure
data definition. Messaging or relations to other standards, especially to the broader
integration standards, like ebXML, that could help to embed the project management
activities into the broader business processes between organizations, are not publicly
At the same time tool vendors are developing interfaces to XML. Microsoft with
Project Server 2003 is the clear market leader in the market of project management
tools. Similarly with PMXML, Microsoft Project Server 2003 defines data types for
projects, WBSs, Calendars, tasks, resources and assignments [23].
So far projects have been regarded as scheduling problems from an IT point of
view: there is a broad range of standard software packages (project management
tools) available on the market supporting various network analysis techniques such as
Program Evaluation and Review Technique (PERT) or Critical Path Method (CPM).
Project management tools like Microsoft Project, Primavera, SuperProject, Artemis or
even larger integrated ERP systems like SAP R/3 or ORACLE Business Suite etc. are
not being optimized from the knowledge point of view.
Project knowledge can be classified as either explicit or tacit. Generally speaking:
Explicit knowledge is that which has been codified and expressed in formal
language; it can be represented, stored, shared and effectively applied [24]. Explicit
information is the information that enables or facilitates the execution of particular
information, including contracting, drawing, solving problems or approving
Tacit knowledge is personal, rooted in action with commitment and involvement in
specific context. It consists of paradigms, viewpoints, beliefs and concrete skills.
Consequently, it is difficult to model and cannot be documented in formal
The distinction between these two types of knowledge is important because each
must be managed in a different way. This implies that the problems for acquiring and
using tacit project knowledge are different from those faced in managing explicit
knowledge. For example in the case of reusing tacit project knowledge the main
problems are related with knowledge, experience and know how loss while in the case
of explicit knowledge the problem areas include project knowledge representation,
incomplete information etc.
Therefore, in order to achieve project knowledge management and knowledge
reuse, several enabling activities could be considered. By collecting explicit
knowledge and tacit knowledge, a knowledge management system can store
information and knowledge about these activities. The use of associated
information/knowledge makes the activity-based knowledge management system [34]
substantially different from traditional project scheduling systems. Consequently,
each activity in the activity-based knowledge management system involves two types
of information, which correspond to explicit knowledge and tacit knowledge. Tacit
knowledge records the forms of resources and information as well as statements of
experience and domain knowledge.
Further, project knowledge can be classified according to [9] in:
Knowledge about projects, which concerns methodological knowledge on how to
manage projects. Usually methodological knowledge is related with project
processes, methods, templates, skills etc.
Knowledge in projects, which is knowledge that members of project team acquire
during the execution of the project. This type of knowledge includes informal
information that is exchanged through e-mail, meetings, personal discussions etc or
it is the outcome of the project itself, the project deliverables and documentation.
Knowledge from projects, which has been generated in projects that have already
finished. During the entire project lifecycle, efforts have been made by the project
team for solving problems. These experiences should flow into a company’s
organizational knowledge base in order to provide input for future projects.
Although, project experiences is regularly requested in the sense of final project
reports, literature and experience shows that this is done incompletely and
Project experiences produced by post project reviews, post project appraisals, after
action reviews, project postmortem review, debriefings, reuse planning, experience
factory, post implementation-installation evaluations constitute a significant asset for
every knowledge organization and therefore their management attracted a lot research
attention the last years [2, 3, 7, 19, 35].
A number of different projects and works have addresses similar or partially the
same problem areas addressed by k.PrOnto. Among them, Caramba system
implements a Process-Aware Collaboration System Supporting Ad hoc and
Collaborative Processes in Virtual Teams [11]; TeamLog system implements
knowledge mining of ad-hoc processes [12]; FRODO project studied the methods
and tools for building and maintaining distributed organizational memories in an
enterprise environment (www.dfki.de/frodo); MILOS system supports dynamic
coordination of distributed software development teams by integrating project
planning and workflow technologies over internet [21], etc.
3 k.PrOnto Framework
k.PrOnto an ontology-based approach is used for knowledge management.
Specifically, we use ontologies to represent project knowledge and semantics. An
ontology is a formal specification of a shared conceptualization, as defined by Gruber
[16]. Ontologies allow the specification of concepts with attributes of a specific type.
Concepts can be organized in a hierarchy (using the specialization relationship
between two concepts). General information regarding ontological engineering
foundations and a survey of most well-known ontologies can be found in [14]. An
illustration of the relationship between ontological engineering and other disciplines
(software engineering and object oriented software development, in particular) is
given in [10].
Considering the large number of ontologies developed, ranging from generic and
core ontologies to domain and application specific ontologies, and the lack of
standardization, an evolution of methodologies and supportive tools for “ontology
engineering” is expected. In k.PrOnto, we use standardized ontology languages [28]
and development tools, Protégé ontology development tool [33].
In order to address the full spectrum of knowledge in project management, tacit
and explicit knowledge, knowledge about projects, knowledge in projects and
knowledge from projects a number of different complementary ontologies has to be
developed. In k.PrOnto, for each subject domain there are three sub-ontologies
covering three distinct project knowledge areas; content, experience and process [9].
More specifically:
Experience ontology: The experience ontology describes the skills and
qualifications required for performing specific task types. Example skills could be
“code reading” and “Java programming”. Further it describes the know-how that is
produced by each project.
Process ontology: The process ontology allows defining a hierarchical process type
structure and alternative process decompositions. For example, it is possible to
state that “white box testing” is a subtype of “testing”. In addition, it is possible to
annotate each process type with required skills and information from the project
Project content ontology: The project ontology allows representing information
about the project context. Examples are: “Size of the project in person years = 9”,
“average skill level of employees = experienced”, “application domain = real time
communication systems”, or “Goal for uptime = 99.999%”.
Knowledge management life cycle includes building knowledge, organizing and
holding, distributing and pooling, and applying knowledge to work object. According
to k.PrOnto approach, project knowledge management is activity centric. This implies
that knowledge is associated with specific project activities. Knowledge and
information associated with activities in previous projects may be reused and applied
in future projects. Information and domain knowledge from all projects are divided
and saved as “activity” units in categories related to the projects for collection and
management. The main advantage of activity based knowledge management is the
ease with which the information and knowledge can be understood and reapplied. An
overview and conceptual framework of activity-based knowledge management used
in k.PrOnto is presented in figure 1.
According to k.PrOnto approach, knowledge lifecycle consists of the following
Knowledge Acquisition: Knowledge acquisition is the collection of related data and
information, concerning of a typical project.
Knowledge Extraction: Knowledge extraction is the process of translating data and
information into knowledge.
Knowledge Storage: Knowledge has been stored under a centralized and safe
Knowledge Sharing: Knowledge sharing enables the engineer to share the valuable
knowledge and information which has stored in the system by using the internet or
Knowledge Update: The feedback from various users which has put back to the
knowledge management system and updates the knowledge base for reuse.
proposes best alternative scenarios to the project manager in order to take final
Project Management Browser is used for browsing existing knowledge. Further
it can be used to see knowledge that has been captured automatically and to
validate the automatic extracted rules, guidelines etc.
Project Management Collaborator is used to enable and monitor collaboration
sessions among networked businesses.
Component Framework: It is a web-based layer that uses server-side logic to
implement various service components. These include the semantic web engine,
the ontology manager and the privacy enforcement component. It also provides
collaboration services enabling networked business to exchange project data and
knowledge using specific proprietary agents, which make use of the knowledge
and policies stores in the local ontologies and the reference definitions included in
the core ontology in order to negotiate transactions with peer agents who belong to
other organizations.
5 Conclusions
k.PrOnto system explores the process of project management by assisting large
distributed project organizations in their efforts to capitalize on the acquired project
At the same time, k.PrOnto advances state of the art in the area of real-time project
governance especially in the area of virtual project organizations. This research area
attracts increasing attentions since more and more organizations are subscribing to
this model.
Of the many factors involved in project management, three are of paramount
importance: a) exponential growth of knowledge b) growing demand for complex and
customized products and services c) the evolution of worldwide markets.
In addition, the introduction of internet technologies brings new challenges in the
field as virtual organizations assemble and disassemble on an opportunistic manner,
while real-time governance of dynamic organizational structures is required.
k.PrOnto addresses these challenges using a holistic approach based on automatic
knowledge acquisition. Distributed project information is attained, processed using
domain specific project ontologies and stored in a knowledge base in order to be used
in project toolkits implementing real-time governance. It enables enterprises to
capitalize on their expertise and to manage new projects as simple new instances in a
continuous enterprise project timeline. More specifically, k.PrOnto enables
organizations to:
continuously evaluate project status and quickly identify at-risk and
underperforming projects using roll-up scorecard reports that graphically display
key project metrics
gain insight into the performance of the project since results are directly compared
with similar projects. Thus, trends and problem areas can be easily identified
enable the exchange of knowledge and data between networked business/virtual
organizations either in the form of good practices or in the form of quantitative
continuously identify valuable resources within the organization or in high market
demand and help project managers in optimizing their utilization or performance.
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