Simultaneous Multiprojection Graph Visualization

When we look at a 3D item on our computer screens, we are actually looking at the 2D projection of the item, which is projected onto the bi-dimensional surface of our screen. Because we experience most 3D items through 2D screens, we believe that the visualization of these items should be optimized for their 2D projections. Our proposed concept of "simultaneous multiprojection" involves optimizing multiple projections concurrently. Although previous studies have focused on individual projections, our research sets its sights on being the first to simultaneously optimize multiple projections for network visualization. This approach opens up exciting possibilities in graph drawing and network visualization, potentially leading to the development of innovative graph layout algorithms. Imagine looking at a graph from different viewpoints, gaining unique insights into its features due to the optimized projections, while still perceiving the same underlying structure. Picture a graph that dynamically adapts to your perspective as you move around it, always maintaining clarity and readability by avoiding occlusion. Moreover, imagine multiple individuals observing the same graph from various angles, each uncovering different insights, yet ultimately comprehending the same fundamental structure. A real-world analogy is Michelangelo`s statue of David in Florence, Italy. From the front, you can clearly see David`s face and the details of his torso and legs, where the precision of the chisel work in shaping features and muscles provides an impression of physical strength and determination. From the side, you can see the detail of David`s hands and the sling draped over his shoulder, giving an impression of David as a prepared and able warrior. From the back, you see the tension in David`s shoulder muscles, suggesting his readiness for the battle with Goliath and symbolizing the unseen efforts and burdens that he is prepared to undertake. In each case, the physical attributes of the statue remain the same; only the observer`s perspective changes however, these different perspectives can dramatically alter one`s interpretation and understanding of the artwork, emphasizing different aspects of the character and the overall narrative. Similarly, our multiprojection approach seeks to reveal diverse dimensions of graph visualizations, enabling a deeper understanding of the data they represent. To achieve our objective of optimizing multiple projections simultaneously, we will concentrate on the layout algorithm used to position nodes in space. Our research extends beyond 3D graphs to encompass 1D projections of 2D graphs, which will significantly impact how graphs are represented when they evolve over time. Furthermore, advancing the representation of 3D graphs will have profound implications for graph visualization in virtual reality, especially in collaborative spaces. In light of the increasing prevalence of remote work and collaborative VR environments, accessibility and collaboration around multidimensional graph representations are becoming crucial. Our goal, therefore, is to investigate the representation of graphs in 2, 3, or more dimensions, starting with their projections. Through this research, we aim to unlock the underused potential of multidimensional graph representation, ultimately enhancing the visualization of temporal networks and graph presentations in virtual reality.