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Research Open Science Open Research Award

Winner 2022 - FAIR data management of a large-scale electron microscopy database for type 1 diabetes

Ahmad Alsahaf (BSCS, UMCG), Anouk Wolters (BSCS, UMCG), Ben Giepmans (BSCS, UMCG), Dieuwke Roelofs-Prins (UMCG), Morris A. Swertz (Faculty of Medical Sciences)

Open Research objectives/practices

Making the outputs of research, including publications, data, software and other research materials freely accessible.

Making scientific research more reproducible by increasing the amount and quality of information placed on the public record.


In 2020, an open-access dataset that contains large-scale electron microscopy (aka ‘nanotomy’) images of nPOD pancreas tissue was created and made publicly available on a website hosted by the research group ( Analysis of the dataset led to the discovery of novel anomalies in type 1 diabetes samples [1].

In 2021, the dataset's open-access status and its compliance with FAIR data principles were significantly improved by publishing it in two open access repositories relevant to the domain of microscopy, the Image Data Resource [2], and the Bio Image Archives [3].

The former publishes reference image datasets that are deemed to have broader value to the community beyond the supporting the publication connected to them, e.g., through continued reuse in other studies.

Before publishing, the image data was converted to a standardised microscopy image format (OME-TIFF), and the metadata was prepared using Molgenis [9].

The dataset is now available to download in full, or to view and analyse directly using the repository's built-in tools [4]. Moreover, each image in the dataset contains rich metadata, including links to NCBI patient data.


The initial open access status of the dataset (while hosted on led to its reuse in several studies.

However, due to the large size of the images in the dataset, and the richness and diversity of the metadata, additional efforts (described above) were needed to further increase the dataset’s access and reusability, especially for automated learning, and to make it compatible with FAIR data principles.

Those efforts were undertaken to publish the dataset in two public repositories [4,5], including an improvement in the linked metadata, and a major shift from using proprietary file formats visualisation software to a unified open-source format for microscopy images (OME-TIFF), which is now being implemented across different projects in the group.

Lessons learned

Even in the presence of supporting bodies for compliance with FAIR data (in the case of microscopy, the Open Microscopy Environment [7]), and the availability of tools to facilitate open-access (e.g. open-access formats and conversion tools [8]), active participation from the research institute is needed. In our case, this came in the form of creating ad-hoc file software for file format conversion whose usage is to be expanded in the future to meet the various needs of the community [6].

URLs, references and further information

[1] (Article)



[4] (Data; IDR)

[5] (Data, BIA)

[6] (Code)




Last modified:20 December 2022 3.32 p.m.