Managing measurement data with openMDM
Keywords:openMDM? measurement data? Matlab? ASAM? ODS?
Day-to-day practice in the test departments of companies shows: Modern measurement and test procedures create enormous amounts of data. It is increasingly becoming a problem to manage them efficiently. In many companies, approaches to cope with the data flood that have been pieced together over many years still prevail. Three distinct approaches can be identified here: management of measurement data in file-based directory structures, management in individually developed database solutions and the use of proprietary solutions from providers in the field of test engineering. These approaches have one thing in common: They are limited by departmental boundaries.
Let testers speak the same language
The automobile industry as an example: Here the product development requires a lot of testing effort. It is therefore not surprising that many of the efforts to make test results more easily interchangeable are rooted in this industry. Association for Standardisation of Automation and Measuring Systems (ASAM) is a working group of leading automotive manufacturers that, in Open Data Services (ODS) (), has defined a format for the storage of measurement data and their metadata. Thereby, a cross-application, vendor-independent standard was established.
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Figure 1: Graphical representation of a selected measurement value/measurement result in a so-called XY chartviewer in the openMDM platform. |
The good thing about it: ODS is generic enough to also map any specifications apart from the automobile industry. It is therefore perfectly suitable to establish a standardised format for the results of different test procedures and thus to create a standardised test data management system that applies company-wide. Test data from different test systems are documented with descriptive information to be able to always correctly interpret and compare them, even from a different location or at different times. These metadata are used to evaluate the professional, organisational and technical context of the data. The context includes, for instance, the description of the test specimen C the "UnitUnderTest" in the language of the ASAM ODS C the test sequence, the test structure, the simulation parameters and the organisational and order-related data. This meta information is an important prerequisite to be able to search and navigate later on in the data stock, e.g. to be able to assign it to different product and test data.
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