Quality research data are essential for quality decision-making and thus for unlocking true innovation potential to ultimately help address unmet medical needs.The factors influencing quality are diverse. They depend on institution type and experiment type and can be of both technical and cultural nature. A well-thought-out governance mechanism will help understand, monitor, and control research data quality in a research institution.In this chapter we provide practical guidance for simple, effective, and sustainable quality governance, tailored to the needs of an organization performing nonregulated preclinical research and owned by all stakeholders.GLP regulations have been developed as a managerial framework under which nonclinical safety testing of pharmaceutical and other products should be conducted. One could argue whether these regulations should be applied to all nonclinical biomedical studies. However, the extensive technical requirements of GLP may not always be fit to the wide variety of studies outside the safety arena and may be seen as overly prescriptive and bureaucratic. In addition, GLP regulations do not take into account scientific excellence in terms of study design or adequacy of analytical methods. For these reasons and in order to allow a lean and fit for purpose approach, the content of this chapter is independent from GLP. Nevertheless, certain topics covered by GLP can be seen as valuable across biomedical research. Examples are focus on transparency and the importance of clear roles and responsibilities for different functions participating in a study.