Supporting Adaptive Enterprise Collaboration through Semantic ...

Supporting Adaptive Enterprise Collaboration through Semantic Knowledge Services Keith Popplewell1, Nenad Stojanovic2, Andreas Abecker2, Dimitris Apostolou3, Gregoris Mentzas3, Jenny Harding4 1 2 3 4

Coventry University, Priory Street, Coventry CV1 5FB, United Kingdom [email protected] Forschungszentrum Informatik, Haid-und-Neu-Str. 10-14, D-76131 Karlsruhe, Germany {nstojano, abecker}@fzi.de Institute of Communication and Computer Systems, 157 80 Athens, Greece {gmentzas, dapost}@mail.ntua.gr Loughborough University, Loughborough, Leicestershire, LE11 3TU, United Kingdom [email protected]

Abstract. The next phase of enterprise interoperability will address the sharing of knowledge within a Virtual Organisation (VO) to the mutual benefit of all VO partners. Such knowledge will be a driver for new enhanced collaborative enterprises, able to achieve the global visions of enterprise interoperability. This paper outlines the approach to be followed in the SYNERGY research project which envisages the delivery of Collaboration Knowledge services through interoperability service utilities (ISUs): trusted third parties offering web-based, pay-on-use services. The aim of SYNERGY is to enhance support of the networked enterprise in the successful, timely creation of, and participation in, collaborative VOs by providing an infrastructure and services to discover, capture, deliver and apply knowledge relevant to collaboration creation and operation. The proposed approach aims to (a) provide semantic ontology-based modelling of knowledge structures on collaborative working; (b) develop a service-oriented self-adaptive solution for knowledgebased collaboration services; and (c) facilitate the testing and evaluation of the efficiency and effectiveness of the solution in concrete case studies. Keywords: enterprise interoperability, semantic web, knowledge services, knowledge management, trust, virtual organisation.

1 Introduction In a recent roadmap of the European Commission (Enterprise Interoperability Research Roadmap – EIRR hereafter, [5]) four challenges were identified as

382

K. Popplewell, N. Stojanovic, A. Abecker, D. Apostolou, G. Mentzas, J. Harding

strategic directions of research in the area of Enterprise Interoperability: (i) interoperability service utility; (ii) web technologies for enterprise interoperability; (iii) knowledge-oriented collaboration; and (iv) a science base for enterprise interoperability. Here, we discuss the development of the necessary technological infrastructure for supporting the third grand challenge, i.e. the next phase of development of deeper functionality of enterprise interoperability that will allow the sharing of knowledge within virtual organizations (VOs) to the mutual benefit of the VO partners. Such research will help mitigate two primary needs of enterprises in successfully forming and exploiting VOs: rapid and reliable formation of collaborative consortia to exploit product opportunities; and application of enterprise and VO knowledge in operational and strategic decisionmaking, thereby leading to enhanced competitiveness and profitability. In this paper, we claim that research on semantic web services [12] [19] has the potential to facilitate the satisfaction of these needs and provide the underlying technological infrastructure for supporting adaptive enterprise collaboration through semantic knowledge services [14]. Specifically, we outline the major objectives and architectural directions of a multi-national research project (SYNERGY), which aims to enhance support for the successful and timely creation of, and participation in, collaborative virtual organizations by providing an infrastructure and services to discover, capture, deliver and apply knowledge relevant to collaboration creation and operation. Section 2 outlines the motivation of this research, while section 3 gives the overall objectives and conceptual architecture of the SYNERGY infrastructure – it focuses on three categories of knowledge services to be developed: moderator services; collaboration pattern services; and knowledge evolution services. Section 4 discusses related work, while the final section 5 presents the main conclusions and further work.

2 Motivation The last decades show a clear trend in business – away from big, comprehensive trusts which can cover all stages of a value creation chain, and away from long standing, well-established and stable supply chains; instead, companies increasingly focus on their core business competencies and often enter into flexible alliances for value creation and production. For example, in the automotive industry the market speed demands flexible configuration and re-configuration of supply-chains, in typical “knowledge-oriented businesses” (like management consulting and software engineering) more and more freelancers and small specialized companies form project-specific coalitions for customer-specific products or services, while in life sciences and biotech technological progress comes from research-based companies in co-opetitive relationships which require flexible and ad-hoc co-operations. This growing demand for flexibly interactive and efficiently integrated businesses and services has already led to a huge amount of scientific and technological research in enterprise interoperability. Although such research has achieved already promising results and partially led to first commercial products

Supporting Adaptive Enterprise Collaboration through Semantic Knowledge Services

383

and service offerings, as well as operational, deployed applications, these remain nevertheless at the level of data interoperability and information exchange; they hardly reach the level of knowledge integration, and certainly fall short of knowledge-based collaboration. Seen from the business-process perspective, today’s approaches to business interoperability mainly address support processes (for instance, how to manage ordering and buying a given product), but they hardly support the companies’ core processes (e.g., finding a decision about what product to buy) with the companies’ core knowledge assets in the centre of value creation and competitive advantage. If we rely on typical definitions of the term “knowledge” as widely accepted in the Knowledge Management area [13], some of the key characteristics of knowledge are that it is highly context-dependent, interlinked with other pieces of knowledge, action-oriented, and often either bound to people or expressed in complex, often logic-based, knowledge representation formalisms. This shows that today’s business interoperability approaches usually address the level of information and application data, but clearly fail to achieve the “knowledge level”. This situation is sketched in Figure 1. Knowledge subject to uncontrolled sharing Knowledge which SHOULD be shared but rarely is • Organisation knowledge assets • Policy • Strategy

Enterprise N Enterprise 3 Enterprise 1

Enterprise 2

Legacy Systems

Data Interoperability

Legacy Systems

(eg. ERP, CAD, etc)

Process Interoperability

(eg. ERP, CAD, etc)

• Etc.

Knowledge which MUST NOT be shared but often is

Isolated, ad hoc, interpersonal communications

Misunderstanding; Core IPR confidentiality lost

• Core IPR • Competing projects • etc.

Lost opportunities to learn and adapt from past collaborations

Missed Collaboration Opportunities

The Collaborating Partner The Virtual Organisation

Fig. 1. Current Forms of Knowledge-Oriented Collaboration

Some of the identified shortcomings of the current situation are as follows: Existing solutions for automated business interoperability address data interoperability for (more or less hard-coded) support of business processes as implemented, e.g., in ERP systems. All forms of “higher-level” interoperation in

384


knowledge-intensive processes ([1], [18]) usually take place in the form of isolated, selective, informal person-to-person contacts, such as e-mails, meetings, telephone conversations, etc. If the business partners do not know each other already and do not have deep insights in the other company’s internal affairs, they can not be aware of their partner’s internal rules, regulations, experiences, core knowledge assets, etc. which easily lead to misunderstandings, wrong estimations, etc. Even worse, “uncontrolled” and unsystematic collaboration about complex issues may not only be subject to inefficiencies, misunderstandings, or wrong decisions because of missing knowledge about the business partner; it is also exposed to the risk of unaware, accidental disclosure of corporate secrets and all kinds of confidential information. Furthermore, unmanaged knowledge exchange can not only cause direct problems such as inefficiency, mistakes, or confidentiality problems; there are also indirect problems which stem from the fact that a systematic assessment of new opportunities, a continuous collaboration-process improvement, etc. can only happen if there is some level of formality and documentation as its basis. Modular, Ontology Based Knowledge Knowledge shared with controls & understood risks • Organisation knowledge assets • Policy • Strategy • Etc.

ISU Services Enterprise 1

Enterprise 3 Enterprise 2

Information and Process Interoperability Services Enhanced VO Collaboration

Collaboration Patterns

Common Understanding

VO Opportunity & Decision Conflict Identification & Resolution

Moderator Services

The Learning VO

Learning Services

New Knowledge The Learning Enterprise

Collaboration structured for enhanced support of VO

Partner KM Services

Knowledge Sharing and Security

Protected knowledge • Core IPR • Competing projects • etc.

Enterprise N

Learning Loop

Collaboration Registry Services

Publishing Capabilities Searching for Contributions

The Collaborating Partner The Virtual Organisation

Fig. 2. SYNERGY Vision of Knowledge-Oriented Collaboration

Figure 2 illustrates the overall idea of the SYNERGY project in terms of the TO-BE situation which will be enabled by the SYNERGY project results. In this TO-BE situation, a Web-based and service oriented software infrastructure will help all kinds of companies which need to engage in collaborative businesses, to


385

discover, capture, deliver and apply knowledge relevant to collaboration creation and operation thus helping them to effectively and efficiently participate in Virtual Organizations (VOs) whilst avoiding the above mentioned shortcomings and problems. The next section outlines in more detail the objectives and conceptual architecture of our approach.

3 The SYNERGY Approach 3.1 Objectives

Following the vision and approach of the IST Enterprise Interoperability Research Roadmap (EIRR, [5]), the SYNERGY architecture takes up and refines the challenge of the Interoperability Service Utility (ISU), i.e. of an open, serviceoriented platform which allows companies to use an independently offered, intelligent infrastructure support to help planning, setting-up, and running complex knowledge-based collaboration. The ISU services to be investigated, designed, prototypically implemented and tested in the SYNERGY project can be organized in three groups: x

x

x

basic collaboration support, including: collaboration registry services that allow publication of and search for capabilities; and information and process interoperability services that may include, e.g., data mediation at the message level, protocol mediation at the service orchestration level, process mediation at the business level, etc. [19]: enhanced collaboration support, including: partner-knowledge management services: services helping a company that wants to enter the collaboration space, to efficiently build up and manage a knowledge base of collaboration-oriented internal knowledge, together with sharing and exchange services which guarantee adequate treatment of confidentiality concerns etc.; collaboration pattern services: as a means to use and reuse proven, useful, experience-based ways of doing and organizing communication and collaboration activities in specific collaborative tasks; and moderator services: which implement the role of a trusted third party helping to establish and run a specific collaborative engagement, to employ collaboration patterns, to mediate conflicts and communication problems, to implement intelligent services at partner site such as opportunity detection, etc; collaboration evolution support, i.e. learning services which continuously accompany and evaluate ongoing activities in order to realize a continuous improvement of knowledge residing both in the central services (such as the collaboration patterns) and at the partner sites (partner-specific collaboration knowledge).

The overall aim of SYNERGY is to enhance support of the networked enterprise in the successful, timely creation of and participation in collaborative

386


VOs by providing an infrastructure and services to discover, capture, deliver and apply knowledge relevant to collaboration creation and operation. The infrastructure must facilitate the sharing of knowledge within an enterprise, between potential and actual VO partner enterprises, and across industrial sectors, whilst allowing, and indeed actively promoting, the protection of individual and shared commercial interests in operating knowledge and expertise and intellectual property rights (IPR). Note that whilst the results of this research are aimed at providing services which could be integrated into the offerings of an ISU, it is not the intention to duplicate research, carried out elsewhere, into the policy, strategy, delivery and operation of ISUs in general. Rather our research effort aims to define the way in which ISUs in general can provide the essential infrastructure for knowledgeoriented collaboration.

3.2 Conceptual Architecture SYNERGY supports collection and preservation of individual enterprise knowledge about inter-organizational collaboration and its secure integration and harmonization within the existing knowledge landscape of a networked enterprise, stored globally in the ISU or locally at the enterprise level. Through collaboration-knowledge services, SYNERGY provides an active platform for efficient maintenance of and access to shared and individual knowledge, and moderation of inter-organizational collaboration, including the ability to continually learn from experience. In this section, we present in detail how we plan to realize this idea. Figure 3 presents an overview of the SYNERGY conceptual architecture. ISU Services

Partner KM Services

Moderator Services Learning Services Collaboration Registry Services

Access to ALL Knowledge Repositories through ISU Services

Collaboration Patterns

Application

Enterprise IPR Collaboration Experience etc..

ISU Knowledge Registry Moderator Knowledge Industry Knowledge Collaboration Capabilities Collaboration Patterns etc..

Distributed Knowledge Repositories

ISU Service Information and Process Interoperability Services

Networked Enterprise

Local Repositories

Repositories at ISU

Fig. 3. Overview of SYNERGY Conceptual Architecture: distributed knowledge repositories, residing locally in an enterprise or globally in the ISU (right-hand side), which


387

can both be maintained and accessed through collaboration-knowledge ISU services (lefthand side)

Each network will develop, through its lifetime, project-specific knowledge. This is in part knowledge specific to the network’s product or service, and to the processes and technologies involved, but it is also related to the current state of the network in its life-cycle. In most cases, such knowledge needs to be maintained only for the network and its partners because it is of no use, and possibly even very confusing, outside that context. Nevertheless, there may be a need to analyse such knowledge and its evolution to provide improved patterns for the future, thus forming a basis for organisational learning. Such collaboration patterns may then enter the public domain to support future collaborations across, say, an industrial sector, but there will be (perhaps most) cases where it is precisely this knowledge which represents competitive advantage to the network or partners concerned, so there is a need to identify where this is the case, and how services might deliver new learning to a specified and appropriate audience of future users – perhaps only partners in the network generating this new knowledge. Within SYNERGY we aim to deliver a Collaboration Knowledge Services Framework (CKSF), a structural framework for knowledge repositories and collaboration services defining mechanisms to manage correct sharing and protection of knowledge. In order to effectively share information and knowledge, it is essential to know when sharing is advantageous: the CKSF will embody knowledge to provide this capability. The maintenance of a library of appropriate collaboration patterns, available as process and service templates to be specialised as necessary and applied to network enterprises either as they form or as they subsequently evolve, is central to the support of partner collaboration in a VO. The CKSF will therefore embody structures and services to define collaboration pattern templates and to select (according to the nature of a developing or existing/changing network), specialise and apply such templates. It is envisaged that the distribution of repository knowledge will reflect its commercial sensitivity, so that at one extreme the most sensitive, perhaps enterprise core competence, would reside within the enterprise’s own systems, whilst at the other extreme a set of collaboration patterns applicable to different scenarios common across an industrial sector would reside in the service provider’s repository. Between these extremes, services may deposit or access knowledge from the service provider or from other partners, but the significant issues relate to the control of access regardless of the location of knowledge. Enterprise knowledge relevant to the formation and operation of collaborative ventures will include, though not necessarily be limited to, (i) Enterprise Core Competence, (ii) Process knowledge for VO Formation, (iii) Process knowledge for partner selection, (iv) VO Operations Management Knowledge. The architecture will be mainly based on the development of a number of ISU services for collaboration: moderator services, pattern services and knowledge evolution services. They are examined in more detail in the following sections.

388


3.2.2 Collaboration Moderator Services A critical aspect of effective knowledge sharing within VOs is the identification of the most appropriate knowledge for reuse or exploitation in a particular context combined with the most efficient tools and mechanisms for its identification, sharing or transfer. Knowledge has a life-cycle and therefore, to maintain its value it must evolve through ongoing maintenance and update. These issues are addressed through the identification of appropriate knowledge sources and the concept of a Collaboration Knowledge Model to support knowledge-sharing activities. However, these elements on their own are insufficient to actively support knowledge sharing and interactions between collaborating partners in the VO. Partners also need to be aware of when knowledge needs to be shared, the implications of doing so and when their decisions are likely to affect other partners within the collaboration. Therefore tools and methods are needed to support identification, acquisition, maintenance and evolution of knowledge and to support knowledge sharing through the raising of awareness of possible consequences of actions and other partner's needs during collaboration. SYNERGY addresses these issues, by exploiting the identified sources of collaboration knowledge in the design of a Collaboration Moderator to raise awareness of needs, possible consequences and likely outcomes in collaboration activities between the partners of the VO. Collaboration Moderation Services comprise the process of identifying key knowledge objects and processes as well as understanding their relevance in context and their relationships. We will exploit previous research work [8] [11[11]] and will also identify innovative knowledge acquisition approaches to extend existing moderator functionalities to enable improved collaboration support through ongoing knowledge updating and maintenance. 3.2.3 Collaboration Pattern Services The collaboration-computing experience is currently dominated by tools (e.g. groupware) and the boundaries they introduce to collaboration processes. As new integration methods (e.g. Web Services) enable users to work more seamlessly across tool boundaries and to mix and match services opportunistically as collaboration progresses, a new organisational model becomes desirable. The challenge is not simply to make integration easier, but also to support the users deal with a multiple of collaboration-related information, tools and services. By adopting collaboration patterns as the organizational model of collaboration, users will work in a more complete context for their actions and be burdened by fewer manual integration tasks. At the same time, by dividing collaborative work into distinct collaboration activities, users can focus more readily on a particular activity and deal more easily with interruptions by suspending and resuming activities as needed. Collaboration patterns augment rather than replace collaboration services and tools. Through reference-based integration methods, collaboration patterns introduce new views and organizational schemes that cut across service and tool boundaries, thereby increasing the integrity of the representation of work and mitigating scatter.


389

SYNERGY will assess the appropriate level of pattern granularity (abstraction) and represent collaboration patterns using ontologies. We will then develop the Collaboration Patterns Editor, a software component for defining collaboration patterns. The editor will represent collaboration patterns as a collection of relationships that emerge between people, the resources they use, and the artefacts they work on, as well as the communication, coordination, and business processes that are used to complete their work. Collaboration patterns will link to services that are already exposed by collaborative tools, such as workflow tools, word processing, wikis, etc. We envisage three ways for generating collaboration patterns: manually, from best practice data; semi-automatically, by detecting prominent usage patterns using folksonomy techniques (e.g. users typically tend to send an email to all other users asking their feedback when a meeting agenda is sent out); and by community members themselves, either from scratch or as refinements of existing patters. A collaboration pattern created with the editor can be used as a template that guides the informal collaborative process without constraining it. We will also develop a simulator that takes as input information about on-going collaborations taking place and being recorded in a collaboration-pattern knowledge base. The simulator will focus on visualizing collaborative networks as well as transactions inside them. 3.2.5 Knowledge Evolution Services One of the unique features of the SYNERGY approach is based on the idea that an explicit management of knowledge-based collaborative work opens up completely new possibilities regarding (semi-) automatic verifying, evolving, and continuously improving the collaboration-knowledge bases. We aim at a comprehensive management of all dynamic aspects in the proposed knowledge bases, including: (i) automated searching for inconsistencies and problems; (ii) automated recommendation of possible new collaboration opportunities; (iii) propagation of evolutionary changes in the collaboration environment toward dependent artefacts in the codified information space; or (iv) implementing means for self-adaptive collaboration that will enable learning from experience and continuously adapt collaboration patterns and their usage preconditions. Altogether, this will lead to a further development of the concept of the learning organization toward a “learning virtual organization” or, better, a “learning business ecosystem”. Methodologically, we intend to extend ideas and approaches of the Learning Software Organization [9].

4 Related Work The European Commission’s EIRR [5] identifies the state of the art of a number of research areas relevant to enterprise interoperability in general and to SYNERGY in particular. For example, the EIRR recognises ontology definition as necessary to the sharing of knowledge, almost by definition – Gruber [7] defines a domain ontology as “a formal, explicit specification of a shared conceptualisation”.

390


Similarly, the EIRR anticipates that delivery of enterprise interoperability capabilities will be achieved through Interoperability Service Utilities (ISUs) providing services to clients, possibly on a pay-per-use business model making them affordable to SMEs. SYNERGY aims to define collaboration knowledge services [14] explicitly to be delivered as services in this way. Specifically, two of the main innovations of SYNERGY include: (i) a reference architecture for an interorganisational knowledge-sharing system, based on knowledge services; and (ii) the formal representation of meta-knowledge for network enterprise collaboration, as well as for risk assessment, propagation and evaluation in networked enterprise collaborations. Concerning moderator services, a lot of research has been reported since the early work of Gaines et al. [6]. Although recent efforts promote the research agenda in this field (e.g. [10], [20], [23]), none of them have addressed interoperability and semantic heterogeneity issues. In SYNERGY, we will provide reference ontologies and example knowledge bases for Collaboration Moderator Services and design and develop a prototype implementation of semantic Collaboration Moderator Services. Collaboration between partners in a VO from a wide variety of domains will result in the need to share knowledge from varied sources, with different data types, file formats and software tools. To cope with this, [16] proposed an ontology-based approach to enable semantic interoperability. The case study proves the effectiveness of ontologies in collaborative product development to support the product-data exchange and information sharing. However, for interoperability to be achieved effectively, it is essential that the semantic definitions of the knowledge objects, processes, contexts and relationships are defined based on mathematically rigorous ontological foundations [11]. Much current work utilises the Web Ontology Language (OWL) for the representation of semantic objects, but this has a very limited capability in terms of process definition. Similarly, the Process Specification language (PSL) has a strong process representation capability, but is weak in its representation of objects. Researchers are therefore increasingly identifying the need for heavyweight ontologies and improved knowledge formalisms [3, 22]. Within SYNERGY, we will develop a blueprint (requirements, language, system architecture, runtime experience) for a knowledge representation and reasoning solution dedicated to knowledge-based collaboration support, as well as a prototype implementation dedicated to knowledge-based collaboration-support requirements. Patterns and pattern languages are becoming increasingly important in various areas such as community informatics [2], activity management [15] and workflow management [21]. A pattern formalizes the structure and content of an activity and the integration methods it depends on, thereby making it reusable as a template in future activities. Collaboration patterns can be regarded as abstractions of classes of similar cases and thus describes a kind of best practices for the execution of specific collaboration activities. Collaboration patterns are useful because they may be used to suggest possible tasks to the users, they can provide information about dependencies between tasks, provide insight about the roles that are required, the resources needed, etc. By sharing collaboration patterns, users can ‘‘socialize’’ best practices and reusable processes. Recently, [4] provided a categorization of


391

collaboration patterns, while [17] presents a first collaboration-patterns ontology. However, to our knowledge there exist no software tools that exploit collaboration patterns as a means to support collaboration in real-time. In SYNERGY, we intend to develop a collaboration pattern-based system that gathers and manipulates many types of content without relying on their native applications. Specifically, we will develop: (i) a reference ontology for collaboration-pattern representation; (ii) methods and service-based tools for collaboration-pattern management and use; and (iii) novel methods of collaborative work and knowledge-task management based on collaboration-patterns support and awareness mechanisms. The ATHENA European FP6 integrated research project considered aspects of enterprise models for interoperability and model driven interoperability. ATHENA focused on application interoperability and on the necessary ontological and semantic requirements to support interoperability of enterprise information. Reports of results and pilot implementations can be accessed through the ATHENA web site [24].

5 Conclusions In this paper we outlined the major objectives of the SYNERGY project, which aims to enhance support for the successful and timely creation of, and participation in, collaborative virtual organisations. Moreover, we presented the architectural directions for a software infrastructure and services supporting collaborative virtual organisations to discover, capture, deliver and apply knowledge relevant to collaboration creation and operation. SYNERGY is expected to benefit collaborating organisations in many ways. As a "learning organisation" a collaborating partner is better able to exploit past experience in responding to future opportunities and in particular to opportunities for participation in collaborative networks. Improved risk assessment may enable collaborating partners to participate in more networks than previously seemed safe, whilst minimising exposure to survival-critical risk. Enhanced sharing of knowledge, with dynamic access control and security accelerates and improves network decision making, shortens time to market and reduces network operating costs, whilst improved capture and especially re-use of enterprise and network knowledge reduces the cost of repeating work of earlier projects, and of repeating past errors. Improved, risk-aware decision making reduces the costs of wrong decisions, and failed collaborations. The SYNERGY software infrastructure will be extensively evaluated against the sophisticated collaborations which arise in the pharmaceutical industry and the engineering domain. The participation in the project of collaborating organisations from more than one industrial sector will enable the evaluation of different aspects of collaboration and, at the same time, will ensure that SYNERGY is generic and not sector-specific.

392


References [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18]

[19]

Abecker A.: Business Process Oriented Knowledge Management – Concepts, Methods and Tools. Phd Thesis, University of Karlsruhe (2003) Chai, C.S., Khine, M.S.:. An Analysis of Interaction and Participation Patterns in Online Community. Education Technology & Society, 9(1):250-261 (2006) Cutting-Decelle, A.-F., Young, B.I., Das, B.P., Case K., et al: A Review of Approaches to Supply Chain Communications: From Manufacturing to Construction. Itcon, vol. 12, pp 73-102 (2007) den Hengst, M., Adkins, M.: Which Collaboration Patterns are Most Challenging: A Global Survey of Facilitators. In: Proc. 40th Hawaii Int. Conf. on System Sciences (2007) European Commission: Enterprise Interoperability: A Concerted Research Roadmap for Shaping Business Networking in the Knowledge-based Economy (2006) Gaines, B.R., Norrie, D.H., Lapsley, A.Z.: Mediator: An Intelligent Information System Supporting the Virtual Manufacturing Enterprise. In: Proc. 1995 IEEE Int. Conf. on Systems, Man and Cybernetics, pp. 964-969 (1995) Gruber, T.R.: Towards Principles for the Design of Ontologies used for Knowledge Sharing. Int. J. of Human-Computer Studies, vol. 43, pp.907-928 (1993) Harding, J.A., Popplewell, K.: Driving Concurrency in a Distributed Concurrent Engineering Project Team: A Specification for an Engineering Moderator. Int. J. of Production Research, 34(3):841-861 (1996) Henninger, S. Maurer, F.: Advances in Learning Software Organizations: 4th Int. Workshop (LSO 2002). Springer, Heidelberg, 2002. Huang, G. Q.: Web Based Support For Collaborative Product Design Review. Int. J. of Computers in Industry, 48(1):71-88 (2002) Lin, H.K., Harding, J.A.: A Manufacturing System Engineering Web Ontology Model on the Semantic Web for Inter-Enterprise Collaboration. Int. J. of Computers in Industry, 58(5):428-437 (2007) Martin, D., Domingue, J.: Semantic Web Services, Part 1. IEEE Intelligent Systems, September/October, pp. 12-17 (2007) Mentzas, G., Apostolou. D., Abecker, A., Young, R.: Knowledge Asset Networking: A Holistic Approach for Leveraging Corporate Knowledge”, Springer, Heidelberg (2002) Mentzas G., Kafentzis, K., Georgolios, G.: Knowledge Services on the Semantic Web. Comm. of the ACM, 50(10):53-58 (2007) Moody, P., Gruen, D., Muller, M.J., Tang, J., Moran T.P.: Business Activity Patterns: A New Model for Collaborative Business Applications. IBM Systems Journal 45(4):683–694 (2006) Mostefai, S., Bouras, A., Batouche, M.: Effective Collaboration in Product Development via a Common Sharable Ontology. Int. J. of Computational Intelligence, 2(4):206-216 (2005) Pattberg, J., Fluegge, M.: Towards an Ontology of Collaboration Patterns. In: Proceedings of Challenges in Collaborative Engineering 07 (2007) Remus, U.: Integrierte Prozess- und Kommunikationsmodellierung zur Verbesserung von wissensintensiven Geschäftsprozessen. In: Abecker, A., Hinkelmann, K., Maus, H., Müller, H.-J. (eds): Geschäftsprozessorientiertes Wissensmanagement, pp. 91-122. Springer, Heidelberg (2002). In German. Studer, R., Grimm, S., Abecker, A.: Semantic Web Services. Concepts, Technologies, and Applications. Springer, Heidelberg (2007)

Supporting Adaptive Enterprise Collaboration through Semantic Knowledge Services [20] [21] [22] [23] [24]

393

Ulieru, M., Norrie, D., Kremer, R., Shen, W.,: A Multi-Resolution Collaborative Architecture for Web-Centric Global Manufacturing. Information Sciences 127, 3-21 (2000) van der Aalst, W.M.P., ter Hofstede, A.H.M., Kiepuszewski, B., Barros, A.P.: Workflow Patterns. Distributed and Parallel Databases, 14(3):5-51 (2003) Young, R.I.M., Gunendran, A.G., Cutting-Decelle, A.-F., Gruninger, M.: Manufacturing Knowledge Sharing in PLM: A Progression Towards the Use of Heavy Weight Ontologies. Int. J. of Production Research, 45(7):1506-1619 (2007) Zhou, L., Nagi, R.: Design of Distributed Information Systems for Agile Manufacturing Virtual Enterprises Using CORBA and STEP Standards. J. of Manufacturing Systems, 2(1):14-31 (2002) ATHENA Project Public Website: http://www.athena-ip.org/