The recent 1-2 decades show a clear trend in business ? away from big, comprehensive trusts which can cover all stages of a value creation chain; also away from long standing, well-established, supply chains, stable over many years; instead, companies increasingly focus on their core business and core competencies and enter more often, and in a much more agile manner, flexible alliances for value creation and production:
- be it in areas like automotive industry with traditionally strong supplier-OEM relationships where a faster clock speed of markets and technological innovation demands more flexible configuration and re-configuration of supply-chains;
- be it in typical ?knowledge businesses? like consulting, software engineering or any kind of research where more and more freelancers, small and specialized companies, or outsourced, offshore and nearshore partners often form project-specific new coalitions for creating a customer-specific knowledge-based product or service;
- be it in relatively new branches like life sciences and biotech which exhibit new market and organization forms anyway, where technological progress is based on many, small, research-based companies in co-opetitive relationships which require flexible and ad-hoc, temporary cooperations.
- Web Service technology to allow easier (semi-)automatic (re-)configuration of cross-organizational, computer-based business processes
- Grid technology as the basis for flexible on-demand allocation of resources in distributed, heavily computing-oriented applications
- Semantic Web technology as well as its applications for smarter versions of the above (Semantic Web Services, Semantic Grid technology) in order to achieve higher degrees of automation and better automatic data type and database schema mappings.
Although such research achieved already promising results and partially led to first com¬mer¬cial products and service offerings, as well as operational, deployed applications, they 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 (in the above example, 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, 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 current situation is sketched in Figure 1:
- Existing solutions for highly automated business interoperability address data interoperability for (more or less hardcoded) support business processes as implemented, e.g., in ERP systems.
- All forms of ?higher-level? interoperation in knowledge-intensive processes (Abecker 2003; Remus 2002) 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 for a significant time, 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, meta-level 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.
2. SYNERGY OVERALL PROJECT VISION
Figure 2 above illustrates the overall idea of the SYNERGY project in terms of the TO-BE situation 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 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. Following the vision and approach of the IST Enterprise Interoperability Research Roadmap (EIRR, 2006), the SYNERGY architecture takes up and refines the first Grand Challenge: the ?Interoperability Service Utility (ISU)? : All services of the SYNERGY project shall be offered through an open, service-oriented platform which allows companies, and in particular SME?s, to use 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:
- Basic collaboration support, including:
- Collaboration registry services that allow publication of and search for both core competences and collaboration capabilities
- 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. (cp. Studer et al 2007)
- 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
- Moderator services: which monitor the activities of partners within the collaboration to identify opportunities for enhanced collaboration, or potential conflicts between partner strategies or decisions. These services also orchestrate exploitation of identified opportunities or resolution of potential conflicts
- Collaboration evolution support, including:
- Learning services: 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 the research is to enhance support of the networked enterprise in 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 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 IPR. This overall, project-level, aim of SYNERGY is decomposed into the following groups of objectives:
Semantic ontology-based modelling of knowledge structures about collaborative working1. Identify, with end-user partners and others, the range, scope and content of knowledge relevant to collaborative working, including the identification and abstraction of collaboration patterns for the learning enterprise and VO.
This objective will be achieved through the delivery of:
- Collaboration Use-cases and Knowledge Modelling requirements for the Collaboration Moderator
- The Collaboration Patterns Model and Ontology
- A consistent Knowledge Collaboration Services Framework
- The design and development of a Collaboration Risk Evaluator
4. Define a service oriented semantically-based inter-organisational knowledge management architecture, to foster collaboration between enterprises, supporting best practice collaboration patterns, enabling automatic extension of knowledge. This objective will be achieved through the delivery of:
- A Knowledge Collaboration Services Framework and the Conceptual architecture of the SYNERGY integrated system
- The development of a Collaboration Patterns Model and Ontology
- The design and development of a Collaboration Patterns Editor and Simulator
- The design and development of a Collaboration Patterns Assistant
- Prototypes for an evolution component
- The Specification of a Collaboration Moderator
- The implementation of a prototype Collaboration Moderator
- The Conceptual architecture of the SYNERGY integrated system
9. Define a methodology for developing and applying knowledge-based collaboration services which may be of value to individual partners or groups of partners within a VO.
This objective will be achieved through the delivery of:
- The SYNERGY Methodology for Knowledge-based Collaboration Services
- The Pilot study specifications and corresponding application of tools
- The Final evaluation of pilot development and implementation