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Interlaboratory studies are common tools for collecting comparable data to implement standards for new materials or testing technologies. In the case of construction materials, these studies form the basis for recommendations and design codes. Depending on the study, the amount of data collected can be enormous, making manual handling and evaluation difficult. On the other hand, the importance of the FAIR (findable, accessible, interoperable, and reusable) principles for scientific data management, published by Wilkinson et al. in 2016, is constantly growing and changing the view on data usage.
The benefits of using data management tools such as data stores/repositories or electronic laboratory notebooks are many. Data is stored in a structured and accessible way (at least within a group) and data loss due to staff turnover is reduced. Tools usually support data publishing and analysis interfaces. In this way, data can be reused years later to generate new knowledge with future insights. On the other hand, there are many challenges in setting up a data repository, such as selecting suitable software tools, defining the data structure, enabling data access, and understanding by others and
ensuring maintenance, among others.
This talk discusses the advantages and challenges of setting up and applying a data repository using the interlaboratory study on the mechanical properties of printed concrete structures carried out in RILEM TC 304-ADC as example. First, the definition of a suitable data structure including all information is discussed. The tool-dependent upload process is then described. Here, the data
management system openBIS (open source software developed by ETH Zurich) is used. Since in most cases an open compute platform allowing access from different organisations is not possible or available due to data protection and maintenance issues, tool-independent export options are discussed and compared. Finally, the different query and analysis possibilities are demonstrated.
Since 1999 there has been a continuous development of non-destructive head check inspection. Especially in case of modern rail inspection systems, high demands on a fast, detailed detection and classification of defects called for improved testing methods. Due to the large amount of different rail types and profiles, the adaptation and optimization of algorithms is still in progress. Additional data analysis is under devel-opment for combined eddy current and ultrasonic inspection methods. This presentation gives an over-view of further enhancement and linking of testing systems as well as data processing. Main foci of the development are an improved sensitivity and an increased reliability of the testing results. Also, additional information can be obtained like determination of local hardness and roughness of the rail as well as an enhanced resolution for locating of defects which will be part of the presented work.
Since 1999 there has been a continuous development of non-destructive head check inspection. Especially in case of modern rail inspection systems, high demands on a fast, detailed detection and classification of defects called for improved testing methods. Due to the large amount of different rail types and profiles, the adaptation and optimization of algorithms is still in progress. Additional data analysis is under devel-opment for combined eddy current and ultrasonic inspection methods. This presentation gives an over-view of further enhancement and linking of testing systems as well as data processing. Main foci of the development are an improved sensitivity and an increased reliability of the testing results. Also, addi-tional information can be obtained like determination of local hardness and roughness of the rail as well as an enhanced resolution for locating of defects which will be part of the presented work.
Medium resolution nuclear magnetic resonance spectroscopy (MR-NMR) currently develops to an important analytical tool for both quality control and process monitoring. One of the fundamental acceptance criteria for online MR-MNR spectroscopy is a robust data treatment and evaluation strategy with the potential for automation. The MR-NMR spectra were treated by an automated baseline and phase correction using the minimum entropy method. The evaluation strategies comprised direct integration, automated line fitting, indirect hard modeling, and partial least squares regression.