Semantic-Based Workflow Composition for Video Processing in the Grid

We outline the problem of automatic video processing for the EcoGrid [1]. This poses many challenges as there is a vast amount of raw data that need to be analysed effectively and efficiently. Furthermore, ecological data are subject to environmental changes and are exception-prone, hence their qualities vary. As manual processing by humans can be time and labour intensive, video and image processing tools can go some way to addressing such problems since they are computationally fast. However, most video analyses that utilise a combination of these tools are still done manually. We propose a semantic-based hybrid workflow composition method that strives to provide automation to speed up this process. The requirements for such a system are presented, whereby we aim for a solution that best satisfies these requirements and that overcomes the limitations of existing Grid workflow composition systems.