We propose a framework for digital image searching which seeks to include the best practices learnt from document information retrieval systems. In particular, we motivate the importance of the user in the search process, and show how the user's task can significantly alter the evaluation of results from the search system. The framework makes the roles of the user explicit to avoid the academic omniscient truth approach which characterizes current content-based image retrieval systems. While primary (low-level) features are a necessary part of the image search process, it is the higher level semantics which have created significant results from image analysis and search. We show that the user is a necessary component in this process.