## 5 A Case Study  
The proposed platform has been implemented in the Telecommunications Museum _Professor [PERSON]_ located at _Escuela Tecnica Superior de Ingenieros de Telecomunicacion, Universidad Politecnica de Madrid_, Spain. The collection is constituted by 873 telecommunication devices. The platform has been adapted to present information and questions in Spanish. The smartphone app that enables visitors to interact with the designed smart object environment is available at Google Play Store (Smart Objects Android App: [[https://play.google.com/store/apps/details?id=com.gsi.objetosinteligentesmuseoetsit](https://play.google.com/store/apps/details?id=com.gsi.objetosinteligentesmuseoetsit)]([https://play.google.com/store/apps/details?id=com.gsi.objetosinteligentesmuseoetsit](https://play.google.com/store/apps/details?id=com.gsi.objetosinteligentesmuseoetsit))). When endeavouring to perform the entity extraction and annotation procedures outlined in Section 3, we came to the realisation that although DBpedia is a large structured dataset, there are many entities and domains regarding the subject of telecommunications that are missing documentation, not only in Spanish but also in English. This hinders the ability to produce more specific questions about a given object. An example to illustrate this drawback is that the corresponding DBpedia entry about voltmeters (DBpedia entry about voltmeters: [[http://dbpedia.org/page/Voltmeter](http://dbpedia.org/page/Voltmeter)]([http://dbpedia.org/page/Voltmeter](http://dbpedia.org/page/Voltmeter))) does not describe the different types of voltmeters available or the physical quantity that is being measured. Therefore, a solution to this inconvenience was to classify items into categories in order to generate additional questions related to the theme the object belongs to.As a result, exhibits were classified into four main categories: _Sound and Image_; _Telephony_; _Radio and Telegraphy_; and _Instrumentation_. Table 1 portrays the result of such classification. It must be noted that **some items belong to more than one theme**. A total of 853 relevant pieces of data could be extracted from items' descriptions and direct DBpedia queries to fill the question templates. The number of adequate question templates (and thus the number of questions generated) depends on the availability of information regarding a particular subject in DBpedia. Therefore, from this procedure, it is possible to evaluate the amount and quality of data relating to these four telecommunication categories in DBpedia. For instance, more templates on instrumentation could have been prepared if the information about measuring instruments were better annotated and structured. Given the limitation mentioned, the resulting number of templates and questions generated per category is portrayed in Table 2. A total of 1013 questions have been produced. As it has been illustrated throughout the paper, complementary data to produce questions rely strongly on the quantity and quality of data stored in DBpedia about the topics of the exhibits of interest. It is important to note that in the cultural heritage field, the information being dealt with can be peculiar and rather specific depending on the reference domain of the exhibit. This means that unless DBpedia (or similarly, Wikipedia) data related to the topics searched has been reviewed by experts, it is not possible to guarantee the correctness of the information retrieved about the questions produced. In contrast, the information about exhibits that is displayed via app has been written and reviewed by telecommunications experts. If this platform were to be implemented in a museum of bigger impact, the gamification system could exploit the Linked Data endpoint of that museum's holdings which would have been validated by experts (as in the case of Prado Museum mentioned in Section 2.1). Alternatively, cultural heritage experts might also take an interest in reviewing information stored in DBpedia.