# Evaluating Schematic Route Maps: Experiment result analysis and aggregated data frames
This folder includes files necessary to run the result analysis. It is composed of four data frames and a R script in markdown format that performs all statistical analysis presented in the article.
## 1 ResultAnalysis.rmd
This file is a R script in markdown format that includes all statistical analysis performed and described in the paper Results sections. In order to facilitate its consultation, the statistical models in this script contain a direct reference to the paper section where the results are presented.
The file ResultAnalysis.html is the generated report markdown script.
## 2 Data Frames used in the analysis
We include the data frames in two formats. The “.RDS” files store the data object for the correct interpretation of the R script, the “.CSV” files contain the same data in comma separated format for human readability.
### 2.1 df_rio_tidy_by_participant
This data frame contains data of the RIO task map application aggregated by participants and summarizes the panning and zoom interactions.
#### Descriptions of the fields:
"File_id": id of the file generated by the RIO map application
"Participant_id"
"Route_name": route1 or route2
"Schematic": Map type. TRUE is the map used was schematic, FALSE if it was the non-schematic
"Route_dir": Direction of the route route (outward;backward)
"Total_time": Total map use time
"Total_interactions": Total number of interactions (zoom and panning)
"Zooms": Total number of zoom interactions
"Mean_scale": Mean of the zoom levels used during the task
"Total_pan_px": Total of panning interactions in pixel (length the of the translations)
"First": which route direction was performed first in the RIO task
"Route_full": Combination of the “route_name” with the “route_dir”
### 2.2 df_navi_tidy_by_participant
This data frame contains data of the Driving task map application aggregated by participants and summarizes the panning and zoom interactions.
#### Descriptions of the fields:
"Participant_id"
"Route_name": Route used in the Driving task. Route1 or route2
"Schematic": Map type. TRUE is the map used was schematic, FALSE if it was the non-schematic
"Route_dir": Direction of the route route (outward;backward)
"Task_time": Total driving time
"Total_time": Total map use time
"View_map_count": How many time the driver stopped the car to view the map
"Zooms": Total number of zoom interactions
"Mean_scale": Mean of the zoom levels used during the task
"Total_pan_px": Total of panning interactions in pixel (length the of the translations)
"Route_full": Combination of the “route_name” with the “route_dir”
"Lm_recalled": Total number of recalled landmarks
"Distance": Distance traveled
"Wrong_turns": Total number of wrong turns
"Set_backs": Total number of set backs
"Total_pan.cm": Total of panning interactions in centimeters (length the of the translations)
### 2.3 df_placement_rio_short
This data frame contains the data of the recall and placement of landmarks (memorability test) after the RIO task.
#### Descriptions of the fields:
"Participant_id"
"Route_name"
"Route"
"Schematic" :Map type. TRUE is the map used was schematic, FALSE if it was the non-schematic
"Lm_short": Landmark name
"Lm_id": Landmark id
"Shape": Polygonal or point-like
"Rio_mentioned": is the landmark mentioned in the rio textual instruction
"Visible_from_route": is the landmark visible from the route
"Type.y": Global or local landmark
"isFake": Is this landmark a foil in the recall test?
"Recalled": Was the landmark recalled by the participant
"correctRecall": Was the recall correct?
"Confidence": Confidence of the placement
"pixDistance": Distance of the placement to the landmark original position
"Right_region": Was the landmark placed in the right region
"Visible_time": How long was the landmark visible (lied inside the map viewport)
"Total_time": Total map use time
"Percent_time": Percent of the total map use time that the landmark was visible
### 2.4 df_placement_navi_short
This data frame contains the data of the recall and placement of landmarks (memorability test) after the Driving task.
#### Descriptions of the fields:
"Participant_id"
"Route_name"
"Route"
"Route_dir": Driving direction of the route route (outward;backward)
"Schematic" :Map type. TRUE is the map used was schematic, FALSE if it was the non-schematic
"Lm_short": Landmark name
"Lm_id": Landmark id
"Shape": Polygonal or point-like
"Rio_mentioned": is the landmark mentioned in the rio textual instruction
"Visible_from_route": is the landmark visible from the route
"Type.y": Global or local landmark
"isFake": Is this landmark a foil in the recall test?
"Recalled": Was the landmark recalled by the participant
"correctRecall": Was the recall correct?
"Confidence": Confidence of the placement
"pixDistance": Distance of the placement to the landmark original position
"Right_region": Was the landmark placed in the right region
"Visible_time": How long was the landmark visible (lied inside the map viewport)
"Total_time": Total map use time
“Task_time”: Total drive time
"Percent_time": Percent of the total map use time that the landmark was visible
“Route_full”: Combination of the route name with the route_dir