The growth from terabytes of 3D imaging data and soon approaching petabytes from material analysis has left the scientists involved with a set of challenges. In particular, the ability to analyze this collection when going from developing an algorithm for a single image, to efficiently scale this analysis to 100s if not 1000s of images. The MUMMERING research project aims to solve this by providing ability to submit workflows to automate this process. We explore and present our initial design thoughts in this endeavor. This includes a proposal to utilize the IDMC system developed at UCPH, which includes job scheduling support to accomplish part of this. In addition, we introduce the mig_utils Python library that enables local IO like access data directly in an imaging analysis program.