Workshop B4. The Collection and Processing of Survey Data Using Mobile Technologies.

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Presentation transcript:

Workshop B4. The Collection and Processing of Survey Data Using Mobile Technologies

Workshop Participants Workshop Chair: Jean Wolf, United States Resource Paper Author: Peter Stopher, Australia Discussant: Barbara Noble, United Kingdom Rapporteur: Sean Doherty, Canada Contributing Authors Stephan Krygsman, South Africa Maat Kees,The Netherlands Nadine Schüssler, Switzerland Other Participants Tracy AndersonRobert FollmerRoger MackettJuan de Dios Ortuzar Patrick BonnelMartin KagerbauerSteve MacFeelyMatthew Roorda Andrew ClarkeNina KarasmaaFabrice MarchalDaniel Sauter Kelly CliftonThipphaphone Khenmingmongkhon Philippe MarchalYuan Shuning Susan Swain Eric CornelisNick LanyonMichael MeschikLiva Vagane Notes: Sizable group (n=28) High attendance and participation rates No incentives offered

Workshop Scope  Really did focus on data collection and processing using mobile technologies  Tried to stay away from non-response  Limited discussion on broader study design

State of the Art - Devices & Data Collection  Device evolution is heading to wearables, but vehicle-based studies may still have a role  Most studies include GPS and diary, but trend towards GPS only  Interview and delivery deployment methods vary  Viable alternatives to GPS are being evaluated Mobile/cell phone options (now) Also used for CAPI Bluetooth / WiFi / RFID / smartcard / RDS (in research)  Alternatives have different levels of detail, precision, cost, coverage  Mixed modes (tech and non-tech) could be used  Select methods and solution(s) based on purpose / need

 Various algorithms developed to identify key diary elements stops, trips – OD / route / distance / start time / duration travel mode trip purpose  Use of GIS datasets important (road network, transit network, points of interest, land use, etc.)  Still largely in exploratory phase Some implementing rule based, others using fuzzy logic  Little validation and little ‘ground truth’ to do it  Prompted recall interfaces developed and implemented, but burden is an issue  Mobile/cell phone research showing promise State of the Art – Data Processing

 Deploying/retaining devices  On/off switch desirable ?  Logging rules (e.g., frequency, speed screen)  Missing data / messy data  Age cut off for deployment (practicality and ethics)  Reducing bias  Encryption/security  Ethics  Avoiding lawsuits  Retaining/archiving raw data  Cost of cell-based location for large samples  Practicality of large scale location-enabled mobile phones (commercial considerations)  How best to recruit and communicate with subjects Issues - Devices and Data Collection

 Lack of available software – commercial, share/free ware  Are we ready to standardize? Data Collection (NMEA parsing) Data Storage (XML desirable) Algorithms  Calibration/validation data essential, but challenging to acquire Prompted recall offers some potential Direct observation may be needed  Assessing respondent burden from prompted recall  Different methods used, e.g., fuzzy logic, AI, rule-based,… Issues - Data Processing

Research Needs – Data Collection  Continued improvements in mobile technology devices Functionality, cost, power capacity, storage capacity, etc.Functionality, cost, power capacity, storage capacity, etc.  Deployment method analyses with respect to study purpose, cost, response rates  Continued research on mobile phone ‘tower location’ traces for travel surveys  Feasibility study for deployment of custom software for population-based mobile phone user sample  Possible joint venture research – government, private, university (e.g., health or tourism research)  How young should or could participants be?  Impact of Galileo on accuracy and coverage?

Research Needs – Data Processing  Standard data, standard processing software, or perhaps algorithm modules  Commercial or free processing software (are we ready?)  Comparative analysis of accuracy of mode and purpose identification  Development of travel companion (who) / party size estimators (and is this really needed?)  Development of validation datasets  Development of algorithms / software independent of GIS  Overall methodology (GPS/CATI, GPS/PR, GPS only) tradeoff analysis (burden, quality, bias, cost). Same for mobile phones.  Pushing the modelling paradigms (e.g., number of travel days, number of persons per household, data elements, travel time measurements)