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Project INF | Susanne Kunis, Michael Hensel & Arne Möller

Structured storage, metadata annotation, and analyses of experimental data

This project will further develop the current platforms for image data management and provide data management for additional data formats from proteomics and lipidomics mass spectrometry and flow cytometry. The project will interface the current data management platforms with an electronic lab notebook system for demands of SFB 1557 to enable the digitization of instrumental and experimental metadata alongside the data generation in experiments and analyses.

© Susanne Kunis

Project Summary
Dr. Susanne Kunis

Osnabrück University
School of Biology/Chemistry
Integrated Bioimaging Facility Osnabrück (iBiOs)

Prof. Dr. Michael Hensel

Osnabrück University
School of Biology/Chemistry
Research Group Microbiology

Prof. Dr. Arne Möller

Osnabrück University
School of Biology/Chemistry
Research Group Structural Biology

The technical developments, especially in the field of imaging methods, are enormous. Still, the protocol status of the accompanying experimental processes is established at a poor level of digitization (as a hardcover lab book) or in isolated solutions within the working groups.

Due to the different and non-standardized data management, the advantages of data management according to FAIR principles or ‘FAIRification’ has not been fully exploited. An SFB with close interactions between researchers from various areas of biomedical sciences and shared instrumental infrastructure and the common PhD training program (IRTG) represents an ideal basis to established standards for FAIRification and optimize data management procedures.

To create a common Big Data resource that complies with the FAIR principles and enables interdisciplinary work with and on the data, in this INF project, we want to establish a platform with an integrated ELN and inventory management that enables common management of the various data types and their underlying experimental processes.

The lab-book will integrate the data management system set up in the last funding period specifically for microscopy data (INF and Z project of SFB 944) and the computing cluster of structural data analysis, which is tailored to the requirements of cryo-EM. For the management of mass spectrometry for proteomics and lipidomics and flow cytometry data, we are striving for uniform data management by introducing an ELN that explicitly supports these data types.

Project-related Publications
  • Kunis, S., Hänsch, S., Schmidt, C., Wong, F., Strambio-De-Castillia, C., Weidtkamp-Peters, S. (2021) MDEmic: a metadata annotation tool to facilitate management of FAIR image data in the bioimaging community. Nat Methods. 18, 1416-1417.

  • Nelson, G., Kunis, S., Nitschke, R. (2021) QUAREP-LiMi: A community-driven initiative to establish guidelines for quality assessment and reproducibility for instruments and images in light microscopy. J Microsc. 284, 56-73.

  • Rigano, A., Ehmsen, S., Öztürk, S. U., Ryan, J., Balashov, A., Hammer, M., Kirli, K., Boehm, U., Brown, C. M., Bellve, K., Chambers, J. J., Cosolo, A., Coleman, R. A., Faklaris, O., Fogarty, K. E., Guilbert, T., Hamacher, A. B., Itano, M. S., Keeley, D. P., Kunis, S., Strambio-De-Castillia, C. (2021). Micro-Meta App: an interactive tool for collecting microscopy metadata based on community specifications. Nat. Methods, 18, 1489–1495.

  • Kunis, S., Zobel, T., Weidtkamp-Peters, S. (2021) RDM4mic working group – Research Data Management for microscopy data as a community task. doi: 10.22443/rms.elmi2021.187 Poster European Light Microscopy Initiative 2021.

  • Moore, J., Norio Kobayashi, N., Kunis, S., Onami, S. Swedlow, J. R. (2019) On Bringing Bioimaging Data into the Open (World). pp. 44–53. url: SWAT4HCLS 2019 - Conference paper.