One of the most vexing issues in digital imaging is the challenge of image validation. Images may be corrupted at any point in the handling chain, from capture through transfer, image editing, storage and migration. Our research into image validation workflow has led to a lifecycle-based set of recommendations, used in conjunction with the DNG file format. These techniques can create an end-to-end workflow that is validated at each step, once an initial visual verification has been performed. This leads to both an increase in security, as well as a reduction in the resources needed to maintain the integrity of image files.The traditional approach to data validation is to make a database of checksums of stored files, and to run a periodic validation sampling. While this approach does provide some good protection for static archived files, it is only appropriate for files that are completely static - any alteration to the file, such as image adjustment or the addition of embedded metadata produces a mismatch. Moreover, a traditional checksum approach typically relies on an external database of checksums, which creates a difficult workflow as files are transferred between different computers.This paper provides an alternate methodology for a fully validated image file workflow, from initial image creation through to archive. It makes use of two tools to accomplish this: the Adobe DNG file format, as well as Parametric Image Editing (PIE) software. In a Parametric Image Editing environment, source image data is never modified, but instead is reinterpreted. This allows preservation of the original image, even as the image may be re-rendered according to different parameters. The Adobe DNG file format includes an area to store the source image data, rendering settings, metadata, as well as one or more fixed renderings of the image. One of the metadata fields that is part of the specification is an open source MD5 Checksum that refers only to the unchanging source image data.Effective use of the DNG file, therefore, creates a portable validation key that can be assigned very early in the lifecycle, and travel with an individual file. The checksum remains viable even as a file is changed, or as the image is readjusted. Adobe has also released several free software tools that can check on the integrity of large collections of image file data automatically and reliably. These tools can, for instance, reliably identify a single changed bit in a file inside a multi-terabyte archive.While the DNG can provide the majority of data validation needs for a digital image library, other validation tools are needed to fill in the gaps. Visual validation is still required at the start of workflow, and transfer validation should also be used regularly. When images must be converted to a rendered filetype, it becomes necessary to rely on the more traditional data validation tools.