# Augmented Reality in Cultural Heritage: An Overview of the Last Decade of Applications
## 2 Research Method  
The data used for the present study were retrieved from Scopus and Clarivate Web of Science (WoS). We selected these databases because they contain extensive peer-reviewed publications and provide effective tools for downloading data. The search was run in April 2022, using the search terms \"(Augmented OR Mixed) Reality AND (Cultur* AND Heritage)\". We selected the search query that ensures the relevancy of the results to the application of AR to cultural heritage. The period selected to accomplish the goal of this research was between 2012 and 2021. A filter search was used to reduce the number of articles to only those published in English, because in most cases, the results of this field of interest are available generally in English [22] (see Figure 1). A list of the selected documents and their key information was exported into the.csv (comma-separated value) format. Based on the chosen search terms, we obtained 835 documents from WoS and 883 documents from Scopus. Figure 1: The methodology used in this study. In the next step, the ScientoPy scientometric tool [23] was used for data reconciliation [24]. Both datasets were merged, and all duplicate documents were removed using ScientoPy (see Figure 2). Hence, through pre-processing, 504 documents were removed from Scopus and 13 from WoS. In addition, ScientoPy was used to simplify authors' names, accents, and abbreviations. The result contains 1201 unique entities from both datasets stored in.csv format and was used as input for further analysis of bibliographic data. We also used the Excel 360 software tool in the data analysis process. ScientoPy can categorize most prominent trends using the following topic growth indicators: average growth rate (AGR), average documents per year (ADY), percentage of documents in last years (PDLY), h-index of each topic [23]. In Table 1 we present the main topics of applying augmented reality to culture heritage. The following areas were the most prominent trends identified: (a) the 3D reconstruction of cultural artifacts; (b) digital heritage; (c) virtual museums; (d) user experience; (e) education; (f) tourism; (g) intangible cultural heritage; (h) gamification. Figure 3 shows the evolution of the current trending topics in the field of AR applied in CH. This plot is based on a query that returns the most popular topics according to the cumulative number of documents versus the year of publication. The trend visualization includes all documents published in the last decade. A logarithmic scale is used on the \(Y\)-axis to facilitate visualization. This evolution plot provides information regarding the evolution of the trend for the past 10 years. It can be seen that topmost popular topics followed a similar pattern. The plot shows that most of the documents follow a consistent pattern of growth. In the right diagram in Figure 3, the AGR for each trending topic between 2020 and 2021 is represented on the \(Y\)-axis, and the PDLY is represented on the \(X\)-axis. The trending topic with the highest number of documents is \"3D reconstruction\" and the topic with the second highest relative growth is \"digital heritage\". \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Pos** & **Author Keywords** & **Total** & **AGR** & **ADY** & **PDLY** & **h-Index** \\ \hline
1 & 3D reconstruction & 155 & \(-\)6.5 & 14.5 & 18.7 & 12 \\
2 & Digital heritage & 107 & \(-\)2.5 & 14.5 & 27.1 & 11 \\
3 & Virtual museums & 78 & \(-\)5.0 & 8.5 & 21.8 & 14 \\
4 & User experience & 63 & \(-\)2.5 & 10.5 & 33.3 & 10 \\
5 & Education & 60 & \(-\)2.5 & 5.5 & 18.3 & 12 \\
6 & Tourism & 48 & \(-\)0.5 & 7.5 & 31.2 & 10 \\
7 & Intangible cultural heritage & 40 & \(-\)2.0 & 5.5 & 27.5 & 5 \\
8 & Gamification & 39 & \(-\)1.0 & 2.0 & 10.3 & 8 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Growth indicators of selected trend topics. Figure 2: The pre-processing data from Scopus and WoS databases.