the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 09 Dec 2025
Interactive physical data cubes: A novel perspective for exploring Earth system dynamics
Abstract. Earth system datasets continue to expand in size and complexity, making it increasingly difficult for non-experts to explore satellite observations and model outputs. We argue that new avenues for data exploration are needed to lower this barrier. Here we present the first interactive, touch-enabled physical data cube that allows users to explore any Earth system dataset intuitively across space, time, and variables. Exhibiting the physical data cube at a major conference showed that users could easily explore and identify patterns in atmospheric and land-surface data through direct physical interaction, demonstrating the system’s potential for scientific discovery, education and public engagement.
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Status: final response (author comments only)
- AC1: 'Supplementary Video File', Maximilian Söchting, 17 Dec 2025
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RC1: 'Comment on egusphere-2025-5632', Anonymous Referee #1, 08 Jan 2026
The authors introduce a tangible interface for interacting with spatiotemporal Earth system data, consisting of a physical cube where the faces represent the intrinsic dimensions of analysis-ready data cubes, i.e., latitude, longitude, and time. As a Perspective, they successfully identify the challenge non-experts face when exploring increasingly complex and high-dimensional Earth system datasets. Their approach aligns well with the scope of Earth System Dynamics, particularly regarding novel tools and interdisciplinary communication.
The physical data cube is a novel and appealing concept that will be of significant interest to the community. I recommend the manuscript for publication, subject to minor revisions. The authors should focus on providing sufficient technical detail to foster community adoption, strengthen the conceptual arguments regarding the benefits of spatiotemporal reasoning, and critically reflect on the potential/limitations of the physical data cube.
1) The current hardware description is high-level. More details can be provided to ensure the tool is reproducible. Could you explain the technical connection between the overview monitor and the cube more comprehensively? Please also include a technical section or appendix with basic specifications (e.g., screen resolution, CPU/GPU requirements for low latency, etc.) to facilitate readers in assessing the feasibility of deploying this solution in institutions such as research centers and schools.
2) The authors argue that current 2D visualizations constrain "spatiotemporal reasoning and intuitive understanding". Could you complete the discussion based on the cited literature on data physicalization (e.g., Jansen et al., 2015) to motivate why the physical cube aids scientific discovery?
3) Given the educational context, why can manipulating a cube of data be better for learning dynamics than spinning a globe? What could help users to mentally map the transition from the front face (map) to the side face (Hovmöller diagram)? Explicitly contrasting the "geometry-first" approach of a globe with the "data-first" approach of the cube would strengthen the educational argument.
4) While true for the data structure (array), geographically, the Earth is not a cube. Projecting a continuous sphere onto a cube creates discontinuities at the edges. Could you add a brief discussion on this and other limitations/constraints of the proposed tool?
5) The validation of the tool reported in the manuscript is anecdotal ("we personally interacted with approximately 150 attendees at the cube over the week"). Could you report some specific qualitative assessments of feedback? For example, did users comment specifically on the speed of interaction or the clarity of the temporal dimension, among other aspects?
Citation: https://doi.org/10.5194/egusphere-2025-5632-RC1 -
AC2: 'Reply on RC1', Maximilian Söchting, 23 Jan 2026
Thank you very much for your positive review and helpful comments on how to further improve the quality of the paper. This is highly appreciated. Please find below a point-by-point response to your comments.
1) Thank you for bringing up reproducibility. Due to its position as a perspective paper, we originally chose to omit some technical details to keep the paper brief. However, you make a good point in the case of reproducibility. We have added a (short) description of hardware requirements as an appendix as well as a description of the connection of the overview monitor.
2) Thank you for this point. We have added additional discussion on why we believe current 2D visualizations are limited in understanding spatiotemporal patterns and how the physical shape may be beneficial.
3) Thank you for the comment. We added some further discussion on the geometry-first vs. data-first approach at the end of chapter 1. In practice, we found the most effective way of communicating the side faces being Hovmöller diagrams and grasp the data cube visualization is to show an animation of precipitation data, as the high-variance patterns on the front face effectively "draw their way through time" on the side faces (like here: https://www.lexcube.org/?!esdc-3.0.2/precipitation_era5 and press the “Play” button in the top right to start the animation).
4) Thank you for this comment. We added a brief discussion on the limitations of the cube shape (distortions, overrepresenting poles, alternative projections) as well as other limitations of our tool (not being suited for sparse, vector or non-gridded data).
5) Thank you for your concern on the user feedback. Yes, it is anecdotal and has not been systematically collected or quantified. However, from our interactions, users specifically noted the speed of the interaction (being built on Lexcube, it is virtually the same or even faster as https://www.lexcube.org as no network is involved in the physical cube - fractions of seconds as benchmarked in our previous publication: https://ieeexplore.ieee.org/document/10274107). Users also liked the spatiotemporal side faces, once understood. This way, one user found a new spatiotemporal pattern in data they have already worked with in the past. We added and changed some sentences in the manuscript to better reflect this.
Citation: https://doi.org/10.5194/egusphere-2025-5632-AC2
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AC2: 'Reply on RC1', Maximilian Söchting, 23 Jan 2026
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RC2: 'Comment on egusphere-2025-5632', Anonymous Referee #2, 24 Jan 2026
Overall quality of the preprint:
This is a preprint that is worth of publication. It is well written and clearly describes a novel new technology.This paper introduces an interesting tool for the display of multidimensional data, allowing user to interact with the data in three dimensions. The rightly observe that these kinds of interactions have become more critical as the size and complexity of datasets has increased. They build upon the developments in Lexcube (a 2-D visualization of datacubes) to crate a fully three dimensional physical data cube. The physical cube is novel and fit for purpose. While the paper focuses on the describing the details of the cube, they also describe the responses of users when they took the cube to a scientific meeting and touch briefly upon preliminary discoveries supported by the cube. The level of detail is appropriate for a short communication.
Specific comments:
In a longer presentation of the cube a number of questions could be addressed:
1. What are the specifications for the supporting PC, monitors etc. of the cube?
2. What are the specifics of the size and complexity of datasets that could be visualized?
3. Are there ways to output the slices being visualized to allow for analysis beyond the visual analysis enabled by the cube?
4. While the strengths of the cube for education and outreach are clear, how might it be further developed to support scientific analyses?
Technical corrections and comments:
No notable corrections needed.Does the paper address relevant scientific questions within the scope of ESD?
Give this is more of a technical paper, it answers important technical questions about the visualization of multidimensional scientific data clearly in a unique tool.
Does the paper present novel concepts, ideas, tools, or data?
Yes, the cube is definitely novel.
Are substantial conclusions reached?
The reactions of users of the cube show substantial benefits and clear understanding of how to use the cube.
Are the scientific methods and assumptions valid and clearly outlined?
N/A
Are the results sufficient to support the interpretations and conclusions?
Yes, the system is clearly described and
Is the description of experiments and calculations sufficiently complete and precise to allow their reproduction by fellow scientists (traceability of results)?
N/A
Do the authors give proper credit to related work and clearly indicate their own new/original contribution?
Yes.
Does the title clearly reflect the contents of the paper?
Yes.
Does the abstract provide a concise and complete summary?
Is the overall presentation well structured and clear?
Yes.
Is the language fluent and precise?
Yes.
Are mathematical formulae, symbols, abbreviations, and units correctly defined and used?
N/A
Should any parts of the paper (text, formulae, figures, tables) be clarified, reduced, combined, or eliminated?
More detail on the technical specification of the cube would be helpful.
Are the number and quality of references appropriate?
Yes.
Is the amount and quality of supplementary material appropriate?
The video is helpful but could be expanded to describe actually data explorations, going beyond simply illustrating the capabilities of the cube.Citation: https://doi.org/10.5194/egusphere-2025-5632-RC2 -
AC3: 'Reply on RC2', Maximilian Söchting, 27 Jan 2026
Thank you very much for your positive review of our manuscript! Your comments have been very helpful in improving the paper, which we highly appreciate.
1) Thank you for mentioning hardware specifications. After referee #1 also brought up a similar point, we have included a short appendix detailing the hardware specifications of the physical cube.
2) Thank you for this comment. For the demo at the LPS conference, we ingested the same data sets as currently available on Lexcube.org and detailed in Table 1 in our previous publication on Lexcube (https://ieeexplore.ieee.org/document/10274107), i.e., in the order of magnitude of hundreds of gigabytes with dozens of parameters per data set. Even larger data sets might also be supported, but testing this has not been the focus of this project. We added a short comment in the manuscript regarding this.
3) Thank you for the comment. Right now, no further analysis is possible and the physical cube is a visual-only tool. However, we foresee various potential extensions for analytical use beyond visualization. We added a remark in the manuscript to reflect these possible plans.
4) Thank you for the remark. We believe that analytical tools such as proposed in 3) as well as deeper integration into scientific workflows, e.g., to easily allow exploration of in-progress data sets, possibly from a running computation, will further strengthen the scientific use cases. We added a short remark in the discussion concerning this point.
Citation: https://doi.org/10.5194/egusphere-2025-5632-AC3
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AC3: 'Reply on RC2', Maximilian Söchting, 27 Jan 2026
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View the video demonstration of the interactive physical data cube here: https://speicherwolke.uni-leipzig.de/index.php/s/KimtpaG4e7PEj49