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Scanning Electron Microscopy (SEM) - Metadata extraction tool and schema mapper

Joseph, Reetu Elza ORCID iD icon 1; Vitali, Elias Guilio Georg 1; Aversa, Rossella ORCID iD icon 1
1 Scientific Computing Center (SCC), Karlsruher Institut für Technologie (KIT)


The management of research data should follow the guidelines provided by the FAIR (Findable, Accessible, Interoperable and Reusable) principles. In particular, data should be described by rich metadata following community standards and schemas in order to be reused. Collecting a plurality of metadata attributes can be demanding for the user, if manually performed. Thus, this task should be automated whenever possible, and tools need to be developed to fulfil it.
As an example of application, we focused on the image data generated from Scanning Electron Microscopy (SEM) measurements in the TIFF file format. We developed a Python tool which extracts the metadata attributes enclosed in the file and maps them to a metadata schema we published in 2021, which reached a consensus within the user community of the projects we are involved in (NFFA-Europe Pilot, Joint Lab MDMC "Integrated Model and Data-driven Materials Characterization", NFDI-MatWerk).
The tool is provided with a web Graphical User Interface (GUI), which enables the users to access and use it without any prior programming knowledge. The final output is a downloadable JSON metadata document containing the extracted attributes. ... mehr

Volltext §
DOI: 10.5445/IR/1000156874
Veröffentlicht am 15.03.2023
DOI: 10.21955/materialsopenres.1115090.1
Cover der Publikation
Zugehörige Institution(en) am KIT Scientific Computing Center (SCC)
Publikationstyp Poster
Publikationsdatum 27.02.2023
Sprache Englisch
Identifikator KITopen-ID: 1000156874
HGF-Programm 46.21.05 (POF IV, LK 01) HMC
Weitere HGF-Programme 46.21.01 (POF IV, LK 01) Domain-Specific Simulation & SDLs and Research Groups
Veranstaltung MaRDA Annual Meeting (2023), Online, 21.02.2023 – 23.02.2023
Bemerkung zur Veröffentlichung This poster received one of the best poster awards for the MaRDA Annual Meeting 2023
Schlagwörter SEM, TIFF, Schema, Metadata, Mapping, Zeiss, Scanning Electron Microscopy, Electron Microscopy
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