# A Methodology for Knowledge Discovery in Labeled and Heterogeneous Graphs
## 5 Case Studies
### Airports
This dashboard is designed to incorporate three tables. The initial table will present the names of airports and their respective countries, prioritizing the top 5 based on degree centrality. Similarly, the second table will feature the same information, arranged according to betweenness centrality, while the third table will be structured based on closeness centrality (Figure 9). In addition, a secondary dashboard will be accessible. Positioned on the left side of this dashboard is a bar graph featuring the top 5 countries with the highest number of registered airports. Upon selecting one of the countries on the right, the screen dynamically updates, showcasing the top 5 airports based on degree centrality, betweenness centrality, and closeness centrality (refer to Figure 10). Following the conclusion of Stage 5, a thorough verification of the information's adequacy precedes our progression to Stage 6. In Stage 6, completion of all tasks is mandatory. Our initial question was: What are the most important airports in our network of connections? To narrow down the answer, we define three subquestions. (1) What five airports have the most immediate connections with other airports? The chosen ones are Frankfurt, Paris, Amsterdam, Istanbul, and Atlanta. (2) What five airports could be vital to giving continuity to the following connections due to their connections with the others? Paris, Los Angeles, Dubai, Anchorage, and Frankfurt score best. (3) What are the five ideal airports for stopovers? Melbourne, Sao Felix do Araguaia, Victoria, Vancouver, and Itotoqtortoormiit are the highest. If we share the data, the airports that appear in more than one category are Frankfurt and Paris (task 6.1). Based on the results of Figure 9, we can see that the 17 most important airports in the connection network are Frankfurt, Paris, Amsterdam, Istanbul, Atlanta, Los Angeles, Dubai, Anchorage, Melbourne, Sao Felix do Araguaia, Victoria, Vancouver, Itotoqtortoormiit, Neerlerit Inaat, Windhoek, Noumea, and Unalaska. According to the centrality analysis, they are the ones that should be taken into account when investing or expanding. Finally, we can replicate this analysis in any country. If we take the United States as an example, which has the most significant number of registered airports, we can see in Figure 10 that the airports of Atlanta and Chicago stand out for having the most significant number of immediate connections, but they also appear among the airports with the highest flow. Of note, Seattle appears in two categories (task 6.1). If the information undergoes updates, the outcomes may vary. Considering that the analysis was conducted using data  
Figure 8: The general model of the airport graph is homogeneous, directed, and includes attributes. The nodes in the graph represent airports, while the relationships between nodes are of the connected-with type, indicating the connectivity between airports. Figure 9: The dashboard presents the following information: The top 5 airports with the most immediate connections and their corresponding countries. The top 5 critical airports for maintaining continuity, including their respective countries. The top 5 airports are recommended for layovers and their associated countries. extracted from a flat file within a specific timeframe, it is imperative to document the results tied to a particular date. This documentation enables us to carry out an analysis aligned with the timeline of airports (task 6.2). Furthermore, future endeavors could consider incorporating data on passenger traffic at each airport to enrich the analysis further and explore alternative datasets within the methodology (task 6.3). In conclusion, analyzing the airport dataset using the proposed methodology yields valuable insights into the network's structure and successfully identifies the most significant airports. By investing in improving and expanding these airports, we can enhance global connectivity, optimize travel routes, and stimulate economic growth.