## 3 Results  
### Identifying the Words to Command Maps  
For the first experiment, we used a questionnaire to determine the words used in the most common commands to manage a map: zoom in, zoom out, move according to different cardinal points, go to a specific place (a street or a city), rotate the map to the left/right, and change a layer. Figure 2: Age range of survey respondents. The main methodological challenge of this step was not to bias of respondents but instead trying to clearly define what command type of action we needed. For instance, we could not include a question such as, \"How do you zoom in?\" because the typical response from most people would be to \"zoom in\". Instead, we selected an approach for dealing with this conditioning by showing videos exemplifying the basic commands. We then asked in open-question form how the survey respondent would request (verbally) that the map to perform these actions (Figure 3). To cluster the answers, we asked about the user's experience with virtual assistants, digital maps' management, and digital competence, in general, in addition to the basic items of user modeling (age, sex, level of education). The level of technological literacy and attitude toward technology are relevant to users' acceptance and interaction with new technological products [35; 36; 37]. The collected results were sorted by the verbs, conjugation modes, and nouns used. Given the variety of responses in terms of spelling, abbreviations, and conjugations, several iterations of sorting were developed. We employed tools including TableauPublic (free SaaS version), Python's Pandas Database library, and the Notepad++ word processor to process the first automatic classifications. Then, we conducted two card-sorting [38] sessions with three experts from different disciplines (information, geography, and design). First, open card sorting was developed individually and blindly; second, hybrid card sorting was developed through a group dynamics session aimed at pooling and obtaining agreement between the categories determined by each expert and the machine. Once fully classified, the data were tallied and processed to identify profiles and emerging patterns between the vocabulary and user characteristics. The asymmetrical distribution that we obtained provided very informative results: despite the large variety of vocabulary, words, and synonyms mentioned before, the most frequent answers (in some cases 95%) used one of only three specific words. As shown in Figure 4, the most frequent verbs used to move the screen by voice were _desplazar_ (to move), _mover_ (to move), _ir_ (to go), and the directional verbs _subir_ (to move up) and _bajar_ (to move down). In the analysis, both directional verbs were combined because the use of either was directly related to the action presented in the video. Our grouping included  
Figure 3: Questionnaire using videos. their infinitive and imperative modes. Often, when conjugated in the imperative, the verb is accompanied by a pronominal particle (e.g., \"move yourself\" or \"move me\"). As anticipated, words for the zoom-in action had little variability, with only seven different verbs, three of which were used by 95% of users (Figure 5). The most frequently used verbs related to this action were _ampliar_ (to enlarge), _acrear_ (to zoom in), and \"zoom\" (Spanish Anglicism for zoom in, frequently used with the verb _hacer_). _Ampliar_ and _acrear_ can be conjugated in the second person imperative and accompanied by a direct complement \"map\" or \"image\", but the infinitive is more common. Figure 4: Verbs used to move the map. Figure 5: Verbs used for zooming in the map. Figure 6 shows the most commonly used verbs to display an orthophoto as an example of loading a new layer. They were _cambiar_ (to change), _mostrar_ (to display), _ver_ (to view), and _vista_ (view as a noun). Of note, the use of the term \"satellite\" occurred both as a noun with other instructions and as a complete instruction (without using a verb, \"_No verbo_\" in Figure 6).