Numerous dipmeter and borehole image log data sets have been acquired over the years and are being used to build subsurface models. Dealing with dipmeter and image log data remains a niche skill within the petroleum industry, and because these are not conventional log data sets, they tend to be neglected in the way data are stored and quality controlled. A variety of wireline and logging-while-drilling tools exist, and each logging run contains a variety of curves with tool-specific mnemonics. For a particular data set, there may be several tens of curves from the raw data set and hundreds from the processed and interpreted data sets. Data quality control (QC) is an essential procedure that has to be conducted to assure dipmeter and image log data integrity in the subsurface models. Data QC should be performed iteratively during data acquisition, data management, processing, and interpretation. This chapter presents standard and globally applicable corporate guidelines for data management and data QC of dipmeter and image log data sets.