{"id":125517,"date":"2026-07-05T06:49:15","date_gmt":"2026-07-05T06:49:15","guid":{"rendered":"https:\/\/www.embl.org\/about\/info\/arise\/?p=125517"},"modified":"2026-07-05T06:49:15","modified_gmt":"2026-07-05T06:49:15","slug":"we-are-all-doing-data-management-but-lets-do-it-fair","status":"publish","type":"post","link":"https:\/\/www.embl.org\/about\/info\/arise\/blog\/2026\/07\/we-are-all-doing-data-management-but-lets-do-it-fair\/","title":{"rendered":"We are all doing data management, but let\u2019s do it FAIR"},"content":{"rendered":"\n

ARISE fellow Alexandra Zakieva on making imaging data FAIR and a glimpse into the resources she is developing to help scientists adopt good data management practices.<\/h2>\n\n\n\n
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This illustration portrays the joint effort in data management involving various stakeholders from diverse domains of science. Credit: Daniela Ramos\/EMBL<\/figcaption><\/figure>\n\n\n\n

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From a very young age, Alexandra has been interested in science. Originally from Moscow, Russia, she moved to Strasbourg at the age of 16, where she earned her Bachelor’s and Master’s degrees in Biology from the University of Strasbourg<\/a>, France. Later, she completed her Ph.D. in plant developmental biology at Heidelberg University<\/a> in Germany.<\/p>\n\n\n\n

Motivated by a desire to make knowledge more accessible to the public and to help more data-supporting research reach the scientific community, Alexandra decided to join the ARISE programme<\/a> in the group of Yannick Schwab at EMBL Heidelberg<\/a>, where she is developing a FAIR (Findable, Accessible, Interoperable, and Reusable) image data management and data stewardship service.<\/p>\n\n\n\n

Can you tell us more about your ARISE project?<\/h3>\n\n\n\n

I manage and steward imaging data for the Traversing European Coastlines<\/a> (TREC) and AtlaSymbio<\/a> consortia, which study planetary biology and symbiosis, respectively. I help my colleagues organize, share, archive, and prepare their imaging data for publication. There has been a lot of microscopy imaging going on, including light and electron microscopy and X-ray imaging, in 2D and 3D, at room temperature and under cryo conditions. In some cases, my colleagues hand over the data to me; in others, data collectors prefer to manage their data themselves. Therefore, I also scout for the best practices in data management and the most suitable tools for TREC and AtlaSymbio data, as well as training my colleagues in following and implementing them.<\/p>\n\n\n\n

What is data management, and why is it so important in bioimaging?<\/h3>\n\n\n\n

Data management is the organisation, sharing, archiving, and publishing of one\u2019s data in a mindful, traceable, and efficient way. No research is possible without collecting or transforming any data even if it is just text. We are actually all doing data management by default. The question is how sustainable our data management is and whether we can find best practices. To achieve this, data management planning at the very beginning of a project is crucial. This is what we tried to do with the data manager Kerstin Leberecht. Together with other TREC colleagues, we wrote a Data Management Plan (DMP) that explains TREC\u2019s data management practices to funders and consortium members alike. The goal is for anyone accessing TREC data to read the DMP and find clear instructions on how to Find, Access, Interoperate, and Reuse the data, as well as how to keep it FAIR in their own work.<\/p>\n\n\n\n

Which resources are you developing for the scientific community to help them acquire good data management skills?<\/h3>\n\n\n\n

Together with the EMBL-EBI Training team<\/a>, TREC and AtlaSymbio colleagues, we received a two-year EMBL Planetary Biology Transversal Theme seed funding for the STANDFLOW project – Towards a STANDardised Data Management WorkFLOW. During this period, we have found, tested, and implemented the best tools for TREC and AtlaSymbio imaging data, written a data management plan, stewarded the first two datasets to the BioImage Archive (S-BIAD2258<\/a>, S-BIAD3173<\/a>), and created a tutorial \u201cImaging Data Management: a Community Effort to Implement FAIR Principles\u201d. I am also developing a REMBI role-play game that helps scientists structure their imaging metadata according to the Recommended Metadata for Biological Imaging standard. Metadata can be very overwhelming; therefore, I am working on different training formats beyond classical lectures. I hope to address another crucial task on electron microscopy (EM) metadata standardisation in the upcoming months to make EM data even more FAIR.<\/p>\n\n\n\n

Can you tell us more about the STANDFLOW tutorial and where people can access it?<\/h3>\n\n\n\n

STANDFLOW tutorial is published on the EMBL-EBI Training catalogue<\/a> as an open educational resource. It is based on my experience and that of more than a hundred colleagues in working with imaging and environmental data. While working with TREC and AtlaSymbio data and interacting with leading experts in the field, we developed best practices for imaging data management for environmental biologists. This tutorial is also suitable for any biologist who would like to make their imaging data FAIR. Our unique chapter \u201cWorking together\u201d explains the deeply human aspect of data management: how to communicate with data stakeholders efficiently and work as a team. We additionally asked the VIB Training team from Belgium to voluntarily review the tutorial. Of course, it hasn\u2019t fully replaced the peer-review process, as we didn\u2019t have an unbiased editorial overview, but it increased tutorial quality, and the general reviewer\u2019s feedback was very positive.<\/p>\n\n\n\n

I particularly appreciated the contributions of the data and imaging experts from EMBL<\/a>, European Marine Biology Resource Centre ERIC<\/a>, Euro-BioImaging ERIC<\/a>, France BioImaging<\/a>, and NFDI4BIOIMAGE<\/a>. It was such an honor and great learning experience for me to see all these experts gather around one document and forge the best imaging data management practices together. The EMBL-EBI Training team made the tutorial as easy to follow as possible. We would be happy to hear everyone\u2019s feedback on this tutorial, because my goal is to make data FAIRification as easy as possible for every scientist. So please, follow the tutorial, fill in the feedback at the end, and share it with your colleagues!<\/p>\n\n\n\n

What do you envision for the future in data management?<\/h3>\n\n\n\n

I hope that most of the data management processes get automated, so scientists would not even have to think about it. Just enter metadata once and press the \u201cpublish data\u201d button. However, to reach this stage, a lot of engineering is needed on both the back end and the front end. And I am not talking only about technical stuff. Most of the bottlenecks lie in people\u2019s practices and habits. A lot of scientists are still used to writing their metadata in paper labbooks, and I understand them. It is indeed often easier to write something down with a pencil or draw a graphical workflow on paper than to fill in a digital form. I don\u2019t want data management to be another bureaucratic task for my colleagues – something I call \u201cdata bureaucracy\u201d.<\/p>\n\n\n\n

Fortunately, Artificial Intelligence (AI) tools are becoming increasingly powerful. My TREC colleagues, Matej Trojak and Marco Rhennecker, are using hand-written text recognition and metadata processing tools powered by AI on the data we are stewarding at this very moment. The new generation of scientists is also transitioning to electronic labbooks. Imaging data communities like the Open Microscopy Environment<\/a> and foundingGIDE<\/a> are standardising imaging data, making it easier to manage each year.<\/p>\n\n\n\n

And in general, I hope that science will become more data-centric than article-centric. I see the tremendous work done by EMBL-EBI<\/a> curators to extract precious data dispersed in scientific publications and enter it in public repositories. In the 21st century, in the age of Linked Open Data and AI, it makes more sense to reverse this information flow: first, scientists should publish their standardised data in public repositories, and second, base their scientific publications on their data accessions. As scientific research is mostly funded by public money, the resulting science belongs to academia, but the data belongs to the public. Therefore, data coming from academia must be as FAIR and Open as possible. Keeping it in the supplementary material of research articles is not enough.<\/p>\n\n\n\n

Besides science, what other activities do you enjoy outside of work?<\/h3>\n\n\n\n

I like hiking and playing hurdy-gurdy.<\/p>\n","protected":false},"excerpt":{"rendered":"

ARISE fellow Alexandra Zakieva on making imaging data FAIR and a glimpse into the resources she is developing to help scientists adopt good data management practices. From a very young age, Alexandra has been interested in science. Originally from Moscow, Russia, she moved to Strasbourg at the age…<\/p>\n","protected":false},"author":21,"featured_media":125333,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[1,3127,3125,2511],"tags":[],"embl_taxonomy":[],"class_list":["post-125517","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-general","category-project","category-tools","category-training"],"acf":[],"embl_taxonomy_terms":[],"featured_image_src":"https:\/\/www.embl.org\/about\/info\/arise\/wp-content\/uploads\/2026\/06\/FAIR_Illustration_text_DR_thumbnail.jpg","_links":{"self":[{"href":"https:\/\/www.embl.org\/about\/info\/arise\/wp-json\/wp\/v2\/posts\/125517","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.embl.org\/about\/info\/arise\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.embl.org\/about\/info\/arise\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.embl.org\/about\/info\/arise\/wp-json\/wp\/v2\/users\/21"}],"replies":[{"embeddable":true,"href":"https:\/\/www.embl.org\/about\/info\/arise\/wp-json\/wp\/v2\/comments?post=125517"}],"version-history":[{"count":2,"href":"https:\/\/www.embl.org\/about\/info\/arise\/wp-json\/wp\/v2\/posts\/125517\/revisions"}],"predecessor-version":[{"id":128911,"href":"https:\/\/www.embl.org\/about\/info\/arise\/wp-json\/wp\/v2\/posts\/125517\/revisions\/128911"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.embl.org\/about\/info\/arise\/wp-json\/wp\/v2\/media\/125333"}],"wp:attachment":[{"href":"https:\/\/www.embl.org\/about\/info\/arise\/wp-json\/wp\/v2\/media?parent=125517"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.embl.org\/about\/info\/arise\/wp-json\/wp\/v2\/categories?post=125517"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.embl.org\/about\/info\/arise\/wp-json\/wp\/v2\/tags?post=125517"},{"taxonomy":"embl_taxonomy","embeddable":true,"href":"https:\/\/www.embl.org\/about\/info\/arise\/wp-json\/wp\/v2\/embl_taxonomy?post=125517"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}