# SINDVis: User-Centered Dynamic Interactive Visualization System for Space Information Networks
## 3 Theory and Methods
### TopoView Methods
#### 3.4.2 FAT Visualization  
Dynamic visualization plays a key role in network performance analysis, but due to the complexity of dynamic data, the evolution process visualization is difficult to determine. Overall, the realization methods of dynamic visualization are generally divided into two categories including animation and timeline [13], and they have also become the current mainstream form. Figure 7 shows a detailed list of methods for implementing dynamic visualization. As shown in Figure 7, the animation method maps time information to the time domain and user analyzes the dynamic network fluctuation mode by observing and analyzing the animation. This method requires the user to remember the differences between the network structure and time step, and then analyze the fluctuation mode of the dynamic network. Therefore, the key to the method is determining how to keep the user's mind map at the same time as the network mutation. Animation methods mainly include two aspects: online and offline [8]. The timeline method maps time to the space domain, and users need to observe several snapshots at the same time to determine the difference by comparing the differences between each other. As the scope of the screen is limited, when there are many time steps, it is difficult to display all of network information at the same time, and this is the main difficulty of this method. The timeline consists mainly of node-links, adjacency matrices, and lists three methods. As mentioned above, the development of visualization gradually highlights the application-driven characteristics. Only by fully considering the characteristics of SIN can the visualization be more effective. The local-world phenomenon edge-weight evolution of SIN is the key factor in studying the topological evolution of SIN [16], and the main objective of dynamic visualization is to analyze its topological evolution laws by a formal means. Therefore, we also need to focus on the analysis of the above-mentioned characteristics. Figure 7: List of visualization methods. Data transmission is different depending on the SIN transmission direction, so, we needed to consider the transmission directionality; this part is introduced in Section 4. The dynamic changes in SIN mainly include the addition and deletion of nodes, the addition and deletion of edges, and so on. Through analyzing the advantages and disadvantages of the above methods, combined with the characteristics of the topological evolution of SIN, we tried to achieve the dynamic evolution visualization of SIN by fusing the animation and the time line method named FAT. Figure 8 shows a schematic diagram of the evolution of the local-world and edge-weight of SIN. As shown above, Figure 8a-d are the evolutionary mechanisms for node increment, node deletion, edge increase, and edge deletion. Figure 8e represents the mechanism of the edge-weight evolution. The future sequence of SIN is unknown, forcing us to rely on online methods to determine its animation form. The use of gradual transition and other transitional technologies to protect the user's mind map does not allow violent shocks so achieves an effective animation display. For the local-world phenomenon of SIN, it is necessary to highlight the differences between the outside local-world and inside local-world, and there is a typical preferential connection mechanism in the local-world. Therefore, we need the constraint of double coding to highlight the similarities and differences between the factors outside and inside the local-world. Based on the relevant principle of centroid constraint in the community network [21], we produced a visual view of the local-world phenomenon in the SIN. The typical characteristic of the local-world is the preferential connection mechanism, and the centroid constraint is used to make the network nodes move closer to the centroid of their community and to realize the aggregation effect in the geometric space. Therefore, the above two aspects have the same effect on the display.