## 5 A Case Study
Another solution to this problem would be to resort to another source of Linked Data, instead of DBPedia, and extract semantic items from datasets that have already been reviewed by experts such as those in Digital Libraries. For example, we could exploit the semantic information provided by the World Digital Library (World Digital Library programmatic API: [[http://api.wdl.org/](http://api.wdl.org/)]([http://api.wdl.org/](http://api.wdl.org/))) or Europeana (European Digital Library SPARQL endpoint: [[http://sparql.europeana.eu/](http://sparql.europeana.eu/)]([http://sparql.europeana.eu/](http://sparql.europeana.eu/))). However, the advantage of using DBpedia is that there are already several tools available that perform entity linking procedures against DBPedia's dataset. In case of using semantic data from Digital Libraries, we would have to program and train a model that would allow performing entity linking procedures on the dataset of choice, which can be more convenient, but would add increased complexity to the platform. Moreover, QR codes have been printed into hard cardboards. We prepared a list of 8 QR codes per cardboard, each of them complemented with an image of the exhibit and its name. The choice of format aims to encourage visitors interested in learning more about any museum object to take any of these cardboards and walk around the museum looking for the objects shown in the cardboard. They may scan objects whenever they desire and once they do so, the digital version of the given exhibit will display in-app. Not only can visitors play questions about scanned items but they are also provided with additional documentation about them. Hence, the visit shifts towards some kind of treasure-hunt experience. Figure 4 portrays the final aspect of these hard cardboards. \begin{table}
\begin{tabular}{c c c c c} \hline \hline  & **Sound and Image** & **Telephony** & **Radio and Telegraphy** & **Instrumentation** \\ \hline
**No. of objects** & 72 & 596 & 144 & 76 \\
**No. of extracted entities** & 82 & 490 & 213 & 68 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Breakdown of museum objects into four categories and summary of entities extracted per category. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & **Sound and Image** & **Telephony** & **Radio and Telegraphy** & **Instrumentation** & **Total** \\ \hline
**No. of templates** & 4 & 9 & 7 & 4 & 24 \\
**No. of questions** & 106 & 440 & 357 & 110 & 1013 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Number of templates and questions per category. The smartphone application has been styled and adapted for Joaquin Serna Telecommunications Museum. An example of the app interface is provided in Figure 5. Concretely, Figure 5a,b show the representation of an exhibit's documentation in the app. Figure 5c depicts the user interface of a multiple-choice question, where gamification elements can be seen, such as time left and remaining tokens. Finally, Figure 5d illustrates the use of tokens that act as lifelines to aid visitors with difficult questions. These helpers work by deleting two distractors, thus leaving the key and only one distractor to choose the answer from. Figure 4: Cardboard example template used to display QR codes. Figure 5: Screenshots of the smartphone application.