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Full Proposal

Project Title: ΚΝΟWLEDGE MANAGEMENT for SOFTWARE

PROJECT MANAGEMENT USING ONTOLOGIES AND SOCIAL

NETWΟRKS

Project Acronym: ONSOCIAL

1. Project Synopsis

The objective of the ONSOCIAL project (Knowledge management for software project management using

ontologies and social networks) is to propose and establish methods for utilizing social capital available in

today’s’ social networks into the software project management process.

Social capital is widely referred to as the resources accumulated by individuals or groups through

relationships in a network [1]. These relationships contain knowledge that after certain analysis can be

utilised for various purposes. Therefore, social capital has been associated with a variety of positive socio-

economic outcomes, such as improved public health, decreased crime rates, and more efficient financial

markets [2]. Based on their social capital, individuals can draw on assets (e.g., helpful information, personal

relationships, capability to form groups, etc.) from other members of the networks to which he or she

belongs.

As a result social networks and specifically enterprise social networks can be used in the context of software

project management in order to answer questions, such as:

How to select the best performing project team?

What is the know-how available to project through the competences of its stakeholders?

What is the most efficient way to allocate tasks to personnel according to their know-how?

As somebody could imagine, the number of different questions that can be asked is almost infinitive and as

such they do not constitute a systematic or practical way to utilize the social capital available. What are

needed are: a) a holistic approach and b) a number of validated for their usefulness measures in order to

convert the social capital to a practical software project management tool.

Therefore, ONSOCIAL project motive is to study business social networks, along with their

characteristics, used measures etc., in the context of two different software development models

(development of open source software and agile software development projects) and to propose a

methodology where social capital is converted into project knowledge able to assist/improve the

software development project.

2. State of the Art & Project Objectives

ONSOCIAL project is based on three different disciples and attempts to combine them in a single model.

Namely these disciplines are: software project management, enterprise social networks and ontologies and

knowledge management.

The 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 endeavours with a

finite lifetime and so do not provide stable organizational homes for the people involved [3].

The practice of project management (PM) has evolved over half a century and permeates all industries,

institutions and governments throughout the world. In response to the perceived need to organise thinking

about project management a number of frameworks have been produced. Two forms of framework are

broadly identifiable, both of which have sought to focus the subject area by presenting only what is

‘generally’ agreed. In doing so, they provide a useful entry point for those seeking to understand the subject

matter. The two types of framework for project management are the following:

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The first of the framework types are life-cycle or maturity models. Common examples include the ISO

series (especially BS ISO10006:2003)[4], Project Excellence Model by the Association of UK Project

Managers[5], Project Management Maturity Model [6], the Japanese designed P2M modal and Projects In

Controlled Environments 2 (PRINCE 2) [7], the family of Software Engineering Institute Capability

Maturity Models in general [8], etc.

The second type of framework is the various ‘Bodies of Knowledge’. For some their influence has been

primary. 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 many elements that comprise project management. In these

areas we have APM Body of Knowledge, PMI Guide to the Project Management Body of Knowledge [9],

BSI BS6079 Guide to Project Management [10], Japanese Project Management Body of Knowledge or

International Project Management Association Capability Baseline (ICB) [11]. At the same time there are

numerous project management methodologies for software development and construction projects [12].

A third approach recently employed is empirical software project management, where emphasis is given to

teamwork and continuous communication [13]. Empirical approaches become quite popular judging from the

large number of different methodologies available such as eXtreme Programming [14], SCRUM [15],

Feature-Driven Development (FDD) [16], etc. and from the large number of works presented in the

literature.

The nature of the project may differ from project to project depending on its subject (for example, R&D,

construction, manufacturing, etc.), but the success of a project is the common goal for any organization that

performs the project. Many studies have analyzed factors that affect project success [17, 18]. Traditionally,

software projects are analyzed controlled and monitored by controlling project scope, time, cost and quality.

A large number of techniques, methods and tools are available in the literature on how to control projects,

identify potentials risks, improve performance, etc.

However, this is not sufficient since software project management is a process that relies heavily on

knowledge and teamwork. Therefore, we need to be able to answer to a set of different questions such as: to

make sure that the knowledge is available in the project team, to ensure the project communication is

smooth, that resources are of the appropriate level, etc.

Social Network Analysis (SNA) offers a powerful tool that provides the means for analyzing informal

networks [19]. Social network analysis aims to understand the relationships between people, groups,

organizations, and other types of social entities [20], and has been used extensively in fields such as

sociology [21] and management [22]. A social network is modeled as a graph with nodes representing the

individual actors in the network and ties representing the relationships between the actors. The key benefit of

SNA is the ability to visualize networks and manipulate these visualizations in real-time. As such, in the

context of project management, SNA can acts as a diagnostic gap-analysis tool for social networks in

organizations. Broadly speaking, the benefits of interventions based on SNA include: a) promoting the

collaboration within groups or teams of an organization; b) facilitating communication c) enabling smooth

information flow within the teams.

Prior work has also shown that software artefact properties are directly influenced by social network

properties of teams, such as their email interactions, and their contribution history of developers. In earlier

work, Bird et al. [23] constructed email social networks from open source project mailing lists and found that

social network analysis measures were highly correlated with development activity. In addition, they found

that global connectivity measures such as betweenness were better indicators of development activity than

local measures such as degree centrality. Pinzger et al. [24] used contribution history to construct the

networks of binaries and the developers that contributed to them. They found that measures such as degree

centrality, closeness centrality, and Bonacich power incontribution networks also had very good predictive

power in determining failure-prone binaries [25, 26, 27, 28]. Meneeley et al. [29] created networks that

consisted solely of developers where edges between developers were based on collaboration on common

files. They used social network analysis to assign values of metrics such as betweenness, degree, and

closeness to developers. The value of a metric for a file was based on the values of the developers that

contributed to that file (such as maximum, sum, or average of a metric for developers for a file). A holistic

approach for combining knowledge, tasks’ needs in knowledge, project geographical different location was

presented from Fitsilis et al. [30] where seven different project dimensions were used together in order to

give answers to more complex queries.

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As such SNA is a valuable tool for creating knowledge. This type of knowledge is basically tacit knowledge

since it is knowledge that is based on the experience of the network members and it described by the

relationships of this network. Generally speaking, tacit knowledge is difficult to be expressed and cannot be

documented in formal languages. Further, tacit knowledge refers to the information that is visibly or

invisibly related to a part of a knowledge (including experience and know-how)[31]. On the other hand

explicit knowledge is that which has been codified and expressed in formal language; it can be represented,

stored, shared and effectively applied. Explicit information is the information that enables or facilitates the

execution of particular information, including contracting, drawing, solving problems or approving

proposals. 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 [32] 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 [33] 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 superficially.

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 [34, 35, 36, 37].

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 PERT (Program Evaluation and Review Technique) 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. [38] are not being optimized

from the knowledge point of view.

Therefore, in order to achieve project knowledge management and knowledge reuse, several enabling

activities and alternatives approached should be considered. One approach that offers substantial benefits and

can be combined with SNA is that of ontological engineering.

Over the last few years, ontologies have become part of popular research topics from a variety of different

fields. Infused mostly by the initiative of the Semantic Web, knowledge engineering in general and ontology

engineering in particular has become a major research subject.

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An ontology is a formal specification of a shared conceptualization, as defined by Gruber [39]. 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 [40]. An

illustration of the relationship between ontological engineering and other disciplines (software engineering

and object oriented software development, in particular) is given in [41].

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. However, among the most prominent and

standardized ontology languages is OWL 2 [42] and among the development tools, Protégé ontology

development tool [43].

3. Expected Benefits from the Project Results

The ONSOCIAL project targets to develop a system that will provide local/regional SMEs with an

innovative and seamless project management toolkit, which will be adaptable to their needs and their specific

type of projects. The ONSOCIAL framework will be adaptable to organisations’ specific needs like the type

of projects that they manage and the variant knowledge that they have. The main aim of the ONSOCIAL

project is to enable the composition, sharing and distribution of knowledge that will result to business

solutions evolvement. The ONSOCIAL system will support organisations to identify their best practices and

metrics targeting to effectiveness and performance improvement that result to the advancement of

adaptability and responsiveness to rapidly changing market demands and customer requirements. Further,

ONSOCIAL will enable the dynamic formation of virtual teams by facilitating knowledge exchange, while at

the same time protecting private knowledge assets, as the multi-layer ontology will also encode policies for

data usage.

The innovative system proposed by the ONSOCIAL project is ideal for exploitation by SMEs, R&D

institutes and public administrations and by any organization that follows various project management

processes. Market opportunities are immense and the proposed system has the potential for massive growth.

4. Methodology

ONSOCIAL project will combine SNA and semantic modelling techniques in order to provide to

project managers a methodology, techniques and tools to transform the social capital available today

in large enterprise social networks to economic benefit for its users. ONSOCIAL project will advance

the existing work found in the literature [44, 45, 46, 47] in a attempt to offer a systematic and integrated

methodology that could have practical use.

ONSOCAL will use Project Management Body of Knowledge and the subject areas defined there in order to

create an ontology that will enable to codify the project knowledge and project artefacts. Project

Management Body of Knowledge (PMBOK) [9] is defined in terms of process groups and knowledge areas.

In this study, we will focus on the knowledge areas, since these areas are offering a more precise idea of

what is project management about and at the same time they give the overall picture. The knowledge areas

are the following:

Project Integration Management describes the processes and activities that integrate different aspects

of project management. It consists of the following processes: Develop Project Charter, Develop

Preliminary Project Scope Statement, Develop Project Management Plan, Direct and Manage

Project Execution, Monitor and Control Project Work, Integrated Change Control, and Project

Closure.

Project Scope Management. It encapsulates processes that are responsible for controlling project

scope such as Scope Planning, Scope Definition, Creation of Work Breakdown Structure (WBS),

etc.

Project Time Management, which describes the processes concerning the timely completion of the

project such as Activity Definition, Activity Sequencing, Activity Resource Estimating, etc.

Project Cost Management that includes processes concerning the cost. The processes that are part of

this knowledge area are: Cost Estimating, Cost Budgeting, and Cost Control.

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Project Quality Management describes the processes involved in assuring that the project will satisfy

the objectives for which it was undertaken. It consists of three processes which are: Quality

Planning, Perform Quality Assurance, and Perform Quality Control.

Project Human Resource Management includes all necessary processes for organizing and managing

the project team such as Human Resource Planning, Acquire Project Team, Develop Project Team,

etc.

Project Communications Management describes the processes concerning communication

mechanisms of a project, and relate to the timely and appropriate generation, collection,

dissemination, storage and ultimate disposition of project information.

Project Risk Management describes the processes concerned with project-related risk management.

Project Procurement Management includes all processes that deal with acquiring products and

services needed to complete a project.

Based on this knowledge codification, queries results posed in social networks can be evaluated and utilised

in a systematic way.

It is clear that knowledge management in a software project should take into account all the above subject

areas and to model the knowledge corresponding to each of them [49]

Project Communication

Project

Purchasing

Quality Assurance

Personnel

September 5

Monday Tuesday Wednesday Thursday Friday Saturday Sunday

6 7 8 9 10 11

12 13 14 15 16 17 18

9/10/2005 - 9/17/2005

Project

Schedule

Project Finance

Risk

Management

Project

Information

Agile

Life cycle (Scrum)Spiral

Life cycle (Boehm)

Organisation’s

Project Knowledge

Assets

Tacit

Knowledge

Explicit

Information

Figure 1. Software project management knowledge management

As it was mentioned two are the basic forms in which knowledge exists within an enterprise environment the

tacit knowledge and the explicit knowledge). Tacit knowledge is inherent in the form of experience and it is

largely personal, related to personal feelings and is directly related to the organizational culture of the

company. Therefore, in order to manage tacit knowledge we need to investigate the human behavior at work.

Explicit knowledge is knowledge made explicit and clear, easily described in the form of electronic

documents, instructions and manuals and refers to specific processes. The end result is that it is managed

relatively easily.

In such cases an ontology can be helpful because:

Provides specific and particular views on the organization's knowledge.

Helps in the homogenization of knowledge from the perspective of the organization, since

information sources and the forms that knowledge exists are heterogeneous.

It can simulate the evolution of knowledge (e.g. by matching between successive snapshots of the

ontology)

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Another approach would be as follows: For each project we have an exclusive ontology (but all ontologies

are compatible because since they inherit from the same upper ontology). Based on this upper ontology

(enterprise ontology), we can create views (projections) of the general social network that relates only to the

specific project.

Figure 2. Tacit and explicit project knowledge

The main objective of the proposed approach is the conversion of tacit knowledge that exists in software

projects to explicit knowledge. In order to achieve the above objective we will attempt to analyze the tacit

knowledge held by members of the project team or the organization using social networks in an attempt to

organize it based on the ONSOCIAL ontology. Moreover, the social network to be developed will be used to

answer to ad-hoc queries.

TACIT

KNOWLEDGE

EXPLICIT

KNOWLEDGE

SOCIAL NETWORK ANALYSIS

Figure 3. Transforming tacit knowledge to explicit.

According to this view, the knowledge of each employee is the sum of personal knowledge together with the

knowledge that results from the social network. It is very customary to go back for a quick solution of a

problem to partners or friends who have encountered the same problem before. At the enterprise level,

members of the organization possess documents of different types (publications, deliverables, presentations),

e-mails, contacts, etc. The analysis of the above information will enable us to build a social network with the

properties we desire. At this point we should mention the "Social Software" [50], ie, software designed to

support social networking, communication and cooperation groups and individuals, taking into account the

social environment.

The social software and the corresponding scientific field "Social Computing" [51] which examines the

development and use ICT to enhance or facilitate social action of the user evolves rapidly in recent years.

Members of organizations are using social software applications such as e-mail, instant messaging, internet

forums, blogs, wikis, tools for collaborative authoring texts, tools, social networking, social bookmarking

tools, etc. both within the organization and outside it. The extraction and analysis of information generated

and stored by these tools can help build the social network with the properties we desire.

The steps for knowledge extraction in the proposed system are presented graphically in the figure below.

The information (documents, e-mails, contacts, etc.) staff evaluated using the procedures and structure of the

ontology. The information is evaluated and stored using the proposed ontology.

At the same time we can draw conclusions about the characteristics of the project team in order to optimize

the selection of team members.

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…

Software Project Ontology

Personnel information

2

Personnel knowledge evaluation

Knowledge management

3

1

Team selection

4 Social network

5

Figure 4. ONSOCIAL system architecture

For achieving the above we need a theoretical model able to combine Social Networks and Semantic

Modelling. The theoretical foundation that ONSOCIAL project is formalised using the concept of confluence

nests [48].

Confluence Nest (CN) is a tripartite graph with hyperedges. A tripartite graph is a graph whose vertices can

be divided into three disjoint sets and edges are connecting vertices from these three disjoint sets. Formally,

the confluence nest is defined as

CN = (O, S, I, E) where

O is a graph representing a Software Project Management Ontology

S is a graph representing a Enterprise Social Network

I is a set of Information Objects containing knowledge or reusable components

E is a set of hyperedges connecting vertices of O, S and I

The idea that a confluence nest is attempting to represent is “which artefact is developed by whom and

contains knowledge of what type”

Figure 5: Confluence Nests

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Project organization

The basic steps of the methodology to be followed in the proposed project are:

Creation of the social network model

Construction of the software project management ontology

Selection of software projects to be studied

Qualitative and quantitative project knowledge data analysis and knowledge generation

Enrichment and adaption of the ontology

Study of the data produced and planning corrective actions

To achieve the project objectives, the work is decomposed into the seven Work Packages (WPs):

WP1: Modeling the social network for software project management

Description of the approach: The main objective of this work package is the modelling of the social

network. In order to develop the ONSOCIAL Social Network Model a conceptual analysis should be done.

Conceptual analysis enables the designer to define the schemata for a knowledge based system [52].

Therefore in order to design the social problem we need to analyse the software project management

problem domain for understanding the concepts, the relations, the facts, the principles and the important

features. The end result of this analysis will be represented with a UML model that will be able to capture

the required classes of information and their relationships.

WP2: Development of software project management ontology

Description of the approach:

The development of ontologies goes by the names of ontology engineering or ontology building, and can

also be investigated under the rubric of ontology learning. For the last twenty years there have been many

methods put forward for how to develop ontologies. For the last twenty years there have been many methods

put forward for how to develop ontologies. Among them worth mentioning, a) ONIONS (ONtologic

Integration Of Naive Sources) – a set of methods especially geared to integrating multiple information

sources [53], with a particular emphasis on domain ontologies b) COINS (COntext INterchange System) – a

long-running series of efforts from MIT’s Sloan School of Management [54] c) METHONTOLOGY – one

of the better known ontology building methodologies; however, not many known uses [55], d) OTK (On-To-

Knowledge) was a methodology that came from the major EU effort at the beginning of last decade; it is a

common sense approach reflected in many ways in other methodologies [56] e) UPON (United Process for

ONtologies) – is a UML-based approach that is based on use cases, and is incremental and iterative [57], etc.

A recent survey on the ontology development methodologies can be found in [58].

Even though each methodology has differences and peculiarities the general phases of an ontology

development methodology are: 1) feasibility study; 2) kickoff; 3) refinement; 4) evaluation; and 5)

application and evolution.

WP3: Tool selection and prototype development

Description of the approach:

In this work package we will evaluate tools for analysing social networks and for the development of

ontologies. The evaluation will be done using multi-criteria decision-making methods. Particular emphasis

will be put on open source tools since this will lower the cost and it will allow to research teams to develop

the required extensions. Integration of the selected tools will be done at the level of data. The prototype

system will be used in the selected case studies.

WP4: Open source software project case study

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Description of the approach: Based on the developed Social Network and on the developed ontology and

by using the ONSOCIAL system prototype a selected software project should be studied. The project should

be selected according to a number of specific criteria such as: sufficient size and complexity, an active

development community, and active user community, geographical distribution, availability of project data,

availability of project web site, availability of log data etc.

Most preferably this should be a well know open source project that will be obtained from well established

open source repository such as http://sourceforge.net/. Currently, the sourceforge repository has more than

320,000 archived project and according to an initial research numerous project satisfy the above mentioned

criteria.

WP5: Commercial software project case study

Description of the approach: Based on the developed Social Network and on the developed ontology and

by using the ONSOCIAL system prototype a selected commercial software project should be studied. The

project should be preferably selected from the portfolio of projects of Intrasoft International without

excluding other opportunities. Again a number of selection criteria will be used such as: sufficient size and

complexity, geographical distribution of stakeholders, number of different legal entities, various levels of

trust, availability of project data, etc. This case study will be focused an stakeholder management and team

selection

WP6: Project Management & Dissemination of Results

Description of the approach: The project coordinator will take the main responsibility for managing the

project activities. WP6 has to assure the timely preparation of high-quality technical deliverables as well as

informative project progress reports. In particular, WP6 efforts will be devoted to deliver the project

deliverables consistently with the pre-specified time and budget constraints, while also maintaining high

quality of the final project results. The project coordinator will be responsible for the smooth coordination of

the collaborating researchers (both the members of the basic research team and the external researchers), the

follow-up and monitoring of all project tasks. The scientific coordinator has to cooperate strongly with all

project members to ensure that a high-level of commitment from all researchers is always present with

respect to the project objectives and research interests. Strong cooperation and high-level of commitment are

also required for the systematic validation of the project results and their successful application in the case

companies.

The project coordinator will submit to the Archimedes Program Research Committee, two (2) reports of

progress, where the project process and the taken actions will be described in detail along with any eventual

problems that were faced and the measures that were considered to overcome these difficulties. By the end of

the project, the coordinator will submit the final progress report describing the overall course of events along

with the results that were achieved and summaries of all the scientific publications produced during the

project life cycle. The coordinator will be also responsible for managing the required actions for

disseminating/presenting the project results in scientific conferences/journals.

Dissemination activities of the project results include: i) development of the project web site, ii) presentation

of the project research results in international conferences (at least 4 publications are expected to be

presented in conference proceedings) and international research journals (at least 2 publications are expected

to be presented in scientific journals).

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APPENDIX

I. Outline of research interests of the involved institutes and description of relevant joint

research (with active web links)

1. The Department of Project Management (DPM) of the Technological Education Institute of Larissa

Greece (TEI/L) belongs in the School of Business & Economics and was founded in September 2000. The

mission of the department is to promote knowledge, research and practice in Project Management and to

equip the department’s graduates with knowledge and skills in applying current scientific methods, tools and

methodologies when managing projects. Project Management, as a management discipline, deals with

various activities in both the public and private sectors. It focuses on the management of varied unique

projects, with specific implementation schedules and deliverables, which require varied knowledge, abilities

and skills and are carried out once in comparison with the continuous operations of an enterprise. Studies in

the department cover the nature and processes of project and operations management in terms of goal

accomplishment, project scheduling, resources planning, cost management, human resource management,

material and environmental resources management, and place special emphasis on the application of

scientific and analytical methodologies with the use of ICT. The department faculty is very active in R&D

activities. A detailed list of publications from the faculty members is presented in

http://dde.teilar.gr/publications.aspx?UICulture=en-US. DPM has built strong relationships with a number of

national and foreign institutions, including the Staffordshire University UK, in implementing jointly post

graduate programs.

2. As far as research cooperation at a national level is concerned, members from the Department of Project

Management of the TEI of Larissa maintain strong links in particular with the Software Engineering Group

(SEG), part of the Programming Languages & Software Engineering Lab (http://sweng.csd.auth.gr)in the

Department of Informatics of the Aristotle University of Thessaloniki. The members of SEG group are

interested in research, development and teaching of software engineering in general, and, in particular, of all

aspects related to the assessment of software characteristics, such as quality, cost, reliability, etc. SEG is

particularly interested in the empirical evaluation of the above characteristics. The current research areas of

the group include: Open Source Software Engineering (SQO-OSS, FLOSSMETRICS projects), including

Open Source Software Reuse of software components with CBSE (Component-Based Software Engineering)

methods (OPEN-SME project), Software Value, Cost and Quality Estimation (Diergasia project), Software

Project Management Anti-patterns and Open Source Projects as vehicles for Software Engineering Education

(OPENSE, OPENED and FLOSSCOM projects). Of special interest to the group is also the software buyer's

point of view, i.e. which tools and techniques are useful for controlling the cost and evaluating the quality of

the software systems acquired. The coordinator of the group is Associate Professor Ioannis Stamelos while

the director of the PLaSE laboratory is Professor Ioannis Vlahavas.

Members from the above two institutes perform joint research in the area of project and software project

management in the context of various national/international projects. A successful example of this

cooperation (2006-2008) was the MISSION SMP project funded from the European Social Fund and the

Greek Ministry of Education, in the context of the ARCHIMEDES II national research program.

Similarly, the proposed project includes collaboration with Hellenic Open University and Informatics

Department. Associate Professor Achilles Kameas has extensive experience and he is the head of DAISY

research group (http://daisy.cti.gr) DAISY research group was founded in 2001 at Computer Technology

Institute at Partas. Since then, it undertook and implemented successfully a number of research projects.

Among them it was SOCIAL project which had as objective to design and develop teams of co-operating

autonomous agents, which could generally be used to expand the action-horizon of humans in inaccessible

industrial fluidic applications. Further, Daisy research group has extensive research experience in ontological

engineering. DAISy team has developed various ontlologies especially related to pervasive computing and ambient intelligent systems.

Finally, the research team includes an industrial partner at the area of software project management. Intrasoft

International (http://www.intrasoft-intl.com/) is a leading the leading European company in the area of Information and Communication Technology Services. It has a broad portfolio of activities which address a wide range of International and National, Public and Private Organisations. In the context of

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ONSOCIAL project Intrasoft International will validate project results in the context of WP5. TEI Larissa, and the specific research team has worked with Intrasoft International at the past offering consultancy work at the area of software engineering.

II. Recent publications of the research staff relevant with the research topics of the

ONSOCIAL project (with active web links)

1. Gerogiannis, V.C., Fitsilis, P., Voulgaridou, D., Kirytopoulos, K.A., Sachini, E. (2010), A Case Study

for Project and Portfolio Management Information System Selection: a Group AHP-Scoring Model

Approach. International Journal of Project Organisation and Management, 2(4): 361-381.

2. Fitsilis, P., Gerogiannis, V. C., Anthopoulos, L., Savvas, I. K. (2010), Supporting the Requirements

Prioritization Process Using Social Network Analysis Techniques. Proceedings of the 19th IEEE

International Workshops on Enabling Technologies: Infrastructures for Collaborative Enterprises,

WETICE 2010, Larissa, Greece, IEEE press, pp. 110-115.

3. Stamelos, I. (2010), Software Project Management Anti-Patterns. Journal of Systems and Software,

83(1): 52-59.

4. Bibi, S., Stamelos, I., Gerolimos, G., Kollias, V. (2010), BBN based Approach for Improving the

Software Development Process of an SME: a Case Study, Journal of Software Maintenance, 22(2).

5. Fitsilis, P., Gerogiannis, V. C., Anthopoulos, L., Kameas, A. (2009) Using social network analysis for

software project management. Proceedings of the 2009 International Conference on the Current Trends

in Information Technology (CTIT 2009), Dubai, IEEE press, pp. 1-6.

6. Fitsilis P, Kameas A. & Anthopoulos, L. 2009. Classification of Software Projects’ Complexity. 18th

International Conference on Information Systems Development (ISD2009) Nanchang, China, September

16-19, 2009

7. Fitsilis P., (2009). Modeling project management knowledge as confluence nests, Technical Report, TEI Larissa, Project Management Department.

8. Bibi, S., Stamelos, I., Angelis, L., (2008), Combining Probabilistic Models for Explanatory Productivity

Estimation. Information and Software Technology Journal, 50(7-8): 656-669. 9. Gerogiannis, V.C. , Mavridis, A., Ipsilandis, P., Stamelos, I., (2008), Evaluating Schedules of Iterative

/Incremental Software Projects from a Real Options Perspective. Proceedings of the 3rd ICSOFT

Conference (International Conference on Software and Data Technologies), Porto, Portugal, pp. 224-

233. 10. C. Goumopoulos, A. Kameas and A. Cassells, “An Ontology-Driven System Architecture for Precision

Agriculture Applications”, International Journal of Metadata, Semantics and Ontologies (IJMSO), 2008

11. Understanding Knowledge Sharing Activities in Free/Open Source Software Projects: An Empirical

Study’, S. K. Sowe, I. Stamelos, L. Angelis, Journal of Systems and Software, Elsevier, 81(3), pp. 431-

446 (2008)

12. Gerogiannis, V. C. & Ipsilandis, P. G. (2007), Multi Objective Analysis for Timeboxing Models of

Software Development. Proceedings of the 2nd ICSOFT Conference (International Conference on

Software and Data Technologies), Barcelona, Spain, pp. 145-153.

13. Fitsilis P., (2007). "Comparing PMBOK and Agile Project Management Software Development

Processes", International Joint Conferences on Computer, Information and System Sciences, and

Engineering (CISSE 2007).

14. Fitsilis, P., Gerogiannis, V., and Kameas, A., (2006). Extracting and Maintaining Project Knowledge

Using Ontologies, 1st International Workshop on Technologies for Collaborative Business Process

Management, Cyprus.

15. Gerogiannis, V. C., Kakarontzas, G., Stamelos, I. (2006), A Unified Approach for Software Process

Representation and Analysis. Proceedings of the 1st ICSOFT Conference (International Conference on

Software and Data Technologies), Setubal, Portugal, pp.127-132.

16. Settas, D., ,Bibi, S., Sfetsos, P., Stamelos, I., Gerogiannis, V.,C., (2006), Using Bayesian Belief

Networks to Model Software Project Management Antipatterns. Proceedings of the Fourth International

Conference on Software Engineering, Research, Management and Applications (SERA 2006), Seattle,

Washington, USA, IEEE Press, pp. 117-124. 17. Mavridis, A., Stamelos, I. (2009), Real Options as Tool Enhancing Rational of OSS Components

Selection. Proceedings of the 3rd IEEE International Conference on Digital Ecosystems and

Technologies, Instanbul, IEEE press, pp. 613-618 (best paper award).