Leinenbach, FrankFrankLeinenbachStumm, ChristopherChristopherStummKrieg, FabianFabianKriegSchneider, AaronAaronSchneider2025-03-042025-03-042025https://publica.fraunhofer.de/handle/publica/48441210.1007/978-3-030-48200-8_73-1To achieve a sustainable value from data repositories and datasets, it is crucial to ensure the high quality and integrity of the stored information and to guarantee its continuous availability. NDE (Non-Destructive Evaluation) processes not only represent an information source but also provide ongoing insights into material properties and performance, significantly enhancing the potential for reuse. These processes deliver essential data that are critical for the evaluation and characterization of materials and components. Moreover, this information, along with forward-looking process parameters, serves as a valuable resource for data-driven optimizations, such as efficient process optimization, training data for modern AI (Artificial Intelligence) applications, or the implementation of current circular economy strategies (R-strategies). To enable this utilization effectively, the NDE data needs to be easily accessible and available over a long time frame. Equally important is their systematic structuring and readability to facilitate easy use by various stakeholders. This chapter outlines the necessary steps to realize an NDE data cycle from the generation of information to the efficient reuse of data and emphasizes the importance of continuous improvement of these processes.enNDE4.0Data reusabilityData integrityData-driven optimizationCircular economyData structuringFAIR principlesDICONDEDigital transformation600 Technik, Medizin, angewandte Wissenschaftenbook article