Medicine and biology are among the most important research fields, having a significant impact on humans and their health. For decades, these fields have been highly dependent on visualization—establishing a tight coupling which is crucial for the development of visualization techniques, designed exclusively for the disciplines of medicine and biology. These visualization techniques can be generalized by the term Biological and Medical Visualization—for short, BioMedical Visualization. BioMedical Vi-sualization is not only an enabler for medical diagnosis and treatment, but also an influential component for today’s life science research. Many BioMedical domains can now be studied at various scales and di-mensions, with different imaging modalities and simulations, and for a variety of purposes. Accordingly, BioMedical Visualization has also innumerable contributions in industrial applications. However, it is still very common to address BioMedical Visualization as a mere application subdomain of the broader field of Visualization, despite its proven maturity and value.

To enable the field to further thrive, it is important to formalize its characteristics independently from the general field of Visualization. Formalization has become particularly urgent, with the latest advances of BioMedical Visualization—in particular, with respect to dealing with Big Data Visualization, e.g., for the visualization of multi-scale, multi-modal, cohort, or computational biology data. Rapid changes and new opportunities in the field, also regarding the incorporation of Artificial Intelligence with ”human-in-the-loop” concepts within the field of Visual Analytics, compel further this formalization. By enabling the BioMedical Visualization community to have intensive discussions on the systematization of current knowledge, we can adequately prepare ourselves for future prospects and challenges.

During this 4-day seminar, we would like to bring visualization experts from academia, research centers and companies together to discuss, identify, formalize, and document the specifics of our field. We see this as a great opportunity to cover a range of relevant and contemporary topics, and as a systematic effort towards establishing better fundaments for the field and towards determining novel future challenges. To this end, we will include a diverse audience of participants—especially, students, junior researchers and junior faculty members.

The main aim of the seminar is to formalize the current status of the field of BioMedical Visualization and to determine future challenges for novice researchers. While tasks and requirements in BioMedical Visu-alization differ from the general field of Visualization, these differences have not yet been systematized independently. A free and open discussion between all participants will broaden our knowledge—opening novel, interesting paths for the future and contributing to new, creative collaborations. This effort might serve in the future as a model for other research fields within the visualization community, where inter-disciplinary collaboration is also required.

We have identified a number of topics, which we believe are relevant for all involved participants. These define our three main pillars: the Data, the involved Stakeholders, and the conducted Tasks and Processes.

1. Topics Related to BioMedical Data:

[BioMedical Data Privacy and Protection] In biomedical research, data has to be anonymized in dedicated software, so that the involved people cannot be identified by, e.g., the visualization expert or the audience of the visualization. With the new advances of medical imaging and visualization techniques, such as high-quality volume rendering, the high resolution of the acquired patient images can already reveal the identity. Should BioMedical data privacy and protection move also towards the anonymization within the data? What other ethical implications does our work entail? How could the field of Biology help here by simulating data?

[BioMedical Data Integration and Standardization] Data integration relates to combining and representing multi-sourced data. As data are derived from inconsistent sources, standardization, i.e., consensus for compatibility, interoperability, safety, and repeatability, becomes essential. How can data integration be formalized through standardization across the disciplines?

[BioMedical Data Complexity vs. Knowledge] BioMedical data is steadily increasing in complexity, especially due to the fields of computational biology and bioinformatics. Despite the recent advances of combined automated and visual data analysis, we (and also domain experts) still have limited knowledge about the data. For this case, automated data analysis approaches are not suitable, while semi-automated analysis is still considered tedious. What are significant challenges? And (in)evitable limitations?


2. Topics Related to BioMedical Stakeholders:

[Internal Stakeholders] We often discuss bridging the gap between visualization and domain experts, academia and industry, and also between Bio- and Medical Visualization. However, visualization experts often need a profound knowledge of the application domain to obtain significant outcomes. How can we move towards a unified and integrated BioMedical Visualization, without separating into Bio- and Medical Visualization? What can we learn from each other? How can the distinct disciplines support each other?

[External Stakeholders] Broader Audiences of BioMedical Visualization involve two main categories: the public and students (or future researching generations). For the former, we are often designing and developing visualizations, e.g., for anatomical or biological education, which may help our domain in gaining recognition within the general public. For the latter, an inherent part of our work involves attracting students to work within our research field, e.g., through teaching. How can the research field become more attractive to the broader audiences? Can we create popularization and teaching guidelines to attract the general public and new, highly-promising work force?

3. Topics Related to BioMedical Tasks and Processes:

[Equalizing the Degree of Sophistication] Apart from the increasing complexity of the data, we are noticing a trend for more and more sophisticated visualization designs, as well. Is this degree of complexity always justifiable? Is the visualization community developing complex solutions, which could be eventually simpler? How can we obtain solutions that are useful for the domain experts, and are still balanced despite, e.g., data complexity? What can academia learn from the practicality of industry on this matter?

[Reusability, Generalizability, and Adoptability] The rapid advances in BioMedical visualization have resulted in a large collection of prototypes, visual designs, techniques and development kits. These tools are domain- and problem-specific, and cannot become more generalized and extensible to other domains. How can we design generalized applications, which are practical and reusable? How to promote and motivate sustainability in BioMedical visualization? Can we design a basis for next generation BioMedical visualization tools? What can we learn from past successes, where prototypes underwent certification processes and were adopted into clinical practice? And, finally, can we determine a way of sharing our designs and results to the parent field of Visualization? How can we contribute back to the broader Visualization community?

The expected outcome of the seminar will be a compilation and publication of guidelines for researchers at all levels, containing all topics addressed during the event. Additionally, the future challenges will be summarized and published to the wider (BioMedical) visualization community—either with a short communication, or with a tutorial or panel discussion at one of our venues, such as IEEE Vis.