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Scientific experiments generate a large amount of data to be processed and analyzed. As the amount of data increases, the way engineers define their own experiments, analyze the output and share them is becoming complex to manage. Scientific Workflow Management Systems (WfMS) are being used to orchestrate a sequence of programs, services and resources, defined by scientific workflows. However, current WfMS are focused on the workflow execution and present limitations on the semantic support to design the experiment. These tools lack on semantic descriptions of available resources to design scientific workflow. This paper presents an ontology for deep water oil exploration workflow. This ontology has been used to present some semantic concepts to help defining a workflow to be further executed by a WfMS. We evaluate this semantic support on a real workflow that calculates fatigue on risers in deep water oil platforms. The results reinforce the benefits of semantic support over program chaining in manual workflow design.

Over the past 5 decades society has been increasingly requiring immediate results, and this is reflected in business. Due to this, the attention given to strategy, strategy management and strategy planning has increased. The use of the Balanced Scorecard (BSC) is a way of achieving this strategic capability. Moreover, a proper BSC has effective metrics to track its goals. This work proposes a system that recommends metrics in accordance with the goals of a BSC. The recommendation is made using data mining techniques, in particular association rules.