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Firms compete by the skills and knowledge of their employees to deliver a range of customized solutions to meet their clients' needs. Knowledgeable workers thereby play a pivotal role in today's knowledge-based economy. In knowledge-intensive business service (KIBS) firms, service providers exchange explicit knowledge with service customers through various delivery channels. The collaboration between service actors is an ad hoc and human-driven process that does not follow a predefined workflow. Further, exchange data or explicit knowledge are sometimes unstructured and difficult to process with activity-based processes. In this paper, we propose a data-driven collaborative approach integrating business artifacts, collaboration patterns, and business rules to model dynamic and ad hoc collaboration within the service delivery channel. We also present a generic service system framework and provide an ontological representation of service systems to reason about service entities and their characteristics.