We outline the problem of automatic video processing in the Grid for
the EcoGrid project. 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 very 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.