## 2 Protocol Design and Equipment
### Labeling and Data Organization  
In order to be able to identify all of the many data components of the Recording and Questionnaire Stages and to associate these with their various corresponding data, the following labeling system is suggested. This system is focused on (1) relating all of the separate recordings and factors to specific questionnaire responses and (2) efficiency and consistency on site. A recent paper by [PERSON] et al. [14] demonstrated the importance of addressing multiple levels of factors which influence perception, form individual-, to session-, to location-level. The successful pleasantness models building incorporating these information levels showed a marked improvement over the equivalent individual-level or location-level only models. The data organisation system proposed here was designed in order to maintain this important information, and the levels of information for the data collected on site are shown in Table 1.  
At the top level is the **Location** information. This includes information about the location which does not change day-to-day, and generally characterizes the architectural character of the space, or typical climate conditions for the area. As described in Section 2.2, each 'environmental unit' should be considered a new location. Therefore, if researchers want to investigate the differences in soundscape assessment in the middle of a small urban park and along the road next to the same park, these would be considered different locations since they would (typically) have different environmental factors, and should be given different names. The name chosen should be concise, but it should be obvious what location is referred to.  
The next level is information which is specific to each session, labeled with a **SessionID**. This SessionID should contain the name of the location and a numerical index which will increase with each repeated session at that location. The SessionID is associated with the data collected during the Recording Stage, and with the data which are continuous throughout the Questionnaire Stage, SLM, and ENV data. For easy automatic processing, correct spelling and consistency with the format is crucial so that data can be filtered according to the SessionID or the location, as is often necessary.  
In addition, for ease of automatic processing, it is recommended not to include spaces in the SessionID to avoid string splitting issues in analysis code.  
Underneath each SessionID will be a set of **GroupIDs**. One GroupID is assigned for _each group of participants_. This should correspond to a single binaural recording and a single 360\({}^{\circ}\) photo. This will be used to (1) relate multiple surveys taken simultaneously and (2) link the recording and photo with the surveys. The GroupID is particularly crucial as it allows commonly missing data to be shared across multiple collection methods. For instance, occasionally paper questionnaires will be missing start and end time information. In this case, this information can be pulled directly from other questionnaires with the same GroupID. Where no questionnaires have the times, it is possible to extract an approximate start time from the binaural recording or 360\({}^{\circ}\) photo and then estimate an average end time.  
The GroupID should have the following format: [a set of letters representing the location name][the SessionID index number][an incrementing index for each group]. For example, for the second session at Regent's Park Japanese Garden, the location name is RegentsParkJapan, the GroupID letters might be 'RPJ'; the SessionID would be 'RegentsParkJapan2' so the GroupIDs for that session would start at '201'. Therefore, for example, the tenth group of participants for that session would be labeled 'RPJ210'. This format ensures that, if the location or SessionID are not recorded for a questionnaire, it is still obvious which session it belongs to.