# 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