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A goal of the Geosciences Network (GEON) is to MotivationThe NSF-funded Geosciences Network (GEON) project is a collaborative effort among researchers from a broad cross section of computer science and earth science disciplines [1]. GEON is comprised of computation clusters that include compute nodes and data nodes that store high quality geological information and software services and that enable data access, analysis, modeling, and visualization. GEON is an example of a "virtual scientific community" that uses cyber-infrastructure (CI) to support and enhance the scientific process.Different groups from the GEON community are developing ontologies that support search [2], information integration [3], and service discovery [4]. An ontology [5] is an explicit specification of the objects, concepts, and other entities that are assumed to exist in a specific domain and the relationships that hold among them.In addition to development of ontologies, many research teams are using workflow techniques to specify the computation of complex scientific activities [6,7,8]. In this paper, we describe a new approach to ontology design called Workflow-Driven Ontologies (WDO). WDOs are distinguished from domain-based ontologies that capture basic knowledge about a domain. Use cases typically drive the specification of domain-based ontologies [9]. In the WDO approach, abstract workflow specifications drive the elicitation and specification of classes and their relationships. For example, domain experts, i.e., earth scientists, begin the knowledge acquisition process by identifying a product and from the product identify methods that can generate the product. Further, domain experts can identify data that are required as input for the identified methods. Knowledge acquisition methodologies based on WDOs are flexible since earth scientists can refine WDOs by refining a WDO-derived workflows and vice-versa. We claim that abstract WDO-derived workflow specifications are indeed the use cases for WDOs.Prior to presenting the details of WDOs, this paper first motivates the utility of WDOs by presenting a case study in Section 2. The case study illustrates how a contour map can be generated from composition of services from the gravity domain. Section 3 explains how workflows are derived from WDOs using the WDO class hierarchy and core relationships. Section 4 presents related work including a discussion on how WDOs compare to other ontologies. Section 5 summarizes the main contributions and open issues related to the development of the WDO approach. Gravity Case StudyThis section describes the Gravity ontology [10] and the use of the ontology to specify workflows. To remain consistent with the terminology used by the OWL Web Ontology Language community, we use the term "class" to denote types of objects captured by the ontology.

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The realization of an international cyberinfrastructure of shared resources to overcome time and space limitations is challenging scientists to rethink how to document their processes. Many known scientific process requirements that would normally be considered impossible to implement a few years ago are close to becoming a reality for scientists, such as large scale integration and data reuse, data sharing across distinct scientific domains, comprehensive support for explaining process results, and full search capability for scientific products across domains. This article introduces the CI-Miner approach that can be used to aggregate knowledge about scientific processes and their products through the use of semantic annotations. The article shows how this aggregated knowledge is used to benefit scientists during the development of their research activities. The discussion is grounded on lessons learned through the use of CI-Miner to semantically annotate scientific processes in the areas of geo-sciences,