Moreover, as a general observation, these studies have also omitted another parameter when it comes to analyzing design data and extracting correlations from historic trends: time. Table 1 summarizes the strengths and shortcomings of the studies shown above. Summing up, to the best of our knowledge, there is limited information concerning the impact of classification, region, mission type and evolution of the key design and performance parameters. After several decades of UAV development, the authors of this paper can find no obvious reason for omitting that type of information, i.e., time, size and weight classification and mission type. In the field of manned aviation, this information is considered fundamental knowledge and plays a key role in major research activities [18; 19; 23; 27]. More specifically, the weight classification is probably the most important and fundamental distinction that has to be made before expressing design data and trends [18; 23]. For example, when it comes to designing the commercial airliners of the future, it would be rather unwise to rely on \"aircraft data\" in general. The corresponding design expert, or team, will search for the trends and data that refer to their respective category, be it a regional, 70-PAX, or \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Research** & **Sample** & **Strengths** & **Shortcomings** \\ \hline [PERSON] [19] & N/A & Well-established design trends & Focused on manned aircraft \\ [PERSON] et al. [22] & 398 & Focused on layout specification & No mission classification/ lack of \\  & & and size & standardized size (NATO) classification \\ [PERSON] et al. [24] & 856 & Large dataset/focused on key & No mission or size classification \\  & & design parameter correlations & No information on platform classification \\ [PERSON] [25] & N/A & Detailed propulsion system & Limited dataset/lack of mission or size \\ [PERSON] et al. [26] & 41 & Novel AI-based approach & classification \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Previous UAV database studies. a double-aisle, commercial jet. This is the reason why, for example, almost all major EU research projects provide dedicated data for each platform category [28; 29; 30; 31]. In a similar manner, when a new UAV development project begins, it is highly likely that the design team will have an indication of its size beforehand. That is, they will not be looking for \"fixed-wing UAV design trends\" in general, but for the trends and data that apply to their specific design case. Similar arguments can be made for the mission type parameter, which, along with the size and weight classification, is a key variable used by well-established aircraft design textbooks and methods [19; 20; 32; 33] when it comes to expressing design trends data and charts. Region of origin can help to provide insight into the technology availability and design approach of various countries and continents, while identifying the trends in terms of design parameters and technology availability is a powerful tool, not only from a marketing point of view, but from a designer's perspective as well. Indicatively, when investigating future designs, a common practice in the commercial airliner industry is to project all values to a reference entry-into-service (EIS) year [28; 29; 30; 31] so that any new configurations, technologies and architectures can be assessed in equal terms. Introducing these critical parameters to unmanned aviation is the primary motivation for this work. Generating a fixed-wing UAV database that resembles the philosophy employed by manned aircraft designers will help to further advance the UAV design activities. Moreover, given that the tools of UAV layout design and performance are based on aircraft design textbooks and methods, the authors can find no reason to not establish a common approach on a database level. An in-house database based on 202 existing fixed-wing UAV platforms has been populated, including 38 different parameters.