As standards in best practices in data quality assurance and quality control evolve, methods for discovery and transport of information relating to these practices must also be developed. An observation's history, from sensor descriptions, processing methods, parameters and quality control tests to data quality flags and sensor alert flags, must be accessible through standards-based web services to enable machine-to-machine interoperability. This capability enables a common understanding and thus an underlying trust in the expanding world of ocean observing systems. For example, a coastal observatory conducts several tests to evaluate and improve the quality of in situ time series data (e.g. velocity) and then generate an oceanic property (e.g. wave height). Using content-rich webenabled services, a data aggregation center will be able to determine which tests were conducted, interpret data quality flags and provide value added services, such as comparing the parameter with those from near-by observations. These additional processing steps may also be documented and sent along with the data to other participating ocean observing systems throughout the world. By utilizing standards-based protocol (Open Geospatial Consortium (OGC) frameworks) and welldefined community adopted QA/QC (Quality Assurance/Quality Control) tests and best-practices (Quality Assurance in Real-Time Oceanographic Data -QARTOD), information about the system provenance, sensor and data processing history needn't be lost.Are data providers ready, willing and able to describe sensors and processing history? And can we transport the information using a framework that offers semantic and syntactic interoperability? The group developing this community white paper has demonstrated that it can be and is being done. A project called Q2O, QARTOD to OGC (Open Geospatial Consortium), bridges the QARTOD community with the OGC community to demonstrate and document best practices in the implementation of QA/QC within the OGC Sensor Web Enablement (SWE) framework. This paper describes this demonstration project and documents the existence of parallel related efforts. With adequate funding to enable the strengthening and broadening of these communities, a solid foundation for ocean observing systems will be built with the assurance that best-practices of data quality are communicated in a meaningful way.

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Abstract. The successful application of Grid and Web Service technologies to real-world problems, such as e-Science [1], requires not only the development of a common vocabulary and meta-data framework as the basis for inter-agent communication and service integration but also the access and use of a rich repository of domain-specific knowledge for problem solving. Both requirements are met by the respective outcomes of ontological and knowledge engineering initiatives. In this paper we discuss a novel, knowledge-based approach to resource synthesis (service composition), which draws on the functionality of semantic web services to represent and expose available resources. The approach we use exploits domain knowledge to guide the service composition process and provide advice on service selection and instantiation. The approach has been implemented in a prototype workflow construction environment that supports the runtime recommendation of a service solution, service discovery via semantic service descriptions, and knowledge-based configuration of selected services. The use of knowledge provides a basis for full automation of service composition via conventional planning algorithms. Workflows produced by this system can be executed through a domain-specific direct mapping mechanism or via a more fluid approach such as WSDL-based service grounding. The approach and prototype have been used to demonstrate practical benefits in the context of the Geodise initiative [2].

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