sharing experiences with mobile devices data collection in uganda 0

SHARING EXPERIENCES WITH MOBILE PHONE DATA COLLECTION IN UGANDA FLAVIA KYEYAGO OUMA UGANDA BUREAU OF STATISTICS 14th October 2015 REGIONAL WORKSHOP & CONFERENCE ON THE USE OF MOBILE TECHNOLOGIES FOR STATISTICAL PROCESSES; UNITED NATIONS CONFERENCE CENTER, ADDIS ABABA, ETHOPIA; 13-16 OCTONER 2015 CONTENTS   Introduction  Pre Mobile CIS issues  Design & Methodology  Data collection and Extraction  Lessons  Benefits  Challenges  Conclusions INTRODUCTION  Mobile Data Collection (MDC) - use of mobile phones, tablets or PDAs for data collection  Many platforms that can be used to design surveys to collect specific data i.e statistical data, photographs, data from a preselection, voice recordings, GPS coordinates, etc  Platforms vary in ease of use, cost, and features  Some requirements that must be defined  sample sizes, budgets, technology services  data quality requirements  Variances in the interfaces, server side components like databases, data reporting and management interfaces and available technology services and infrastructure  Mobile Data Collection Application Trends:  Development of Native applications installed on the data collection device  Use of USSD as the messaging framework to send the data to server via SMS  The use of the browser based software to collect and send data to an Application server INTRODUCTION  In 2008 , GOU, started a programme called the Community Information System (CIS)  The main objective was to  collect Administrative data  empower communities to make informed decisions using readily available up to date information  The CIS was first implemented in 2009 in about 50 districts  Multisectoral approach and UBOS was in charge of data processing  used paper based questionnaire and  a system for data entry was developed  However, there were many challenges experienced that included technical and non technical issues that led to the exercise stalling Pre Mobile CIS issues      Infrastructure limitations no - In 2011, the growing use of mobile electricity and room at Sub- phones pushed the IT team to innovate and experiment the use pf counties mobile phones on the CIS project Limited HR for entry even at -The developed a web based solution both Sub county & district level which could be accessed through the web browsers that are native on the Entry required long term employment not sustainable mobile phone Data delays and data obsolete yet wanted real time data for planning at that level lack of integration of the data -Was done with the objective of introducing the alternative of MDC -Reduce on some infrastructural limitations of the Design & Methodology  The Web application was designed by the IT Team at UBOS using previous experience  This web interface is accessed through phones with web browsers  Why Web - web is ubiquitous in nature and can be accessed by any device, anywhere, anytime  Scope: Modules with about 25 questionnaires, that included administrative data on health, education, financial institutions, general operations  Technology and Application: mobile device phones with sim cards, Designed using HTML5, CSS, PHP and Java Script for the front end & Mysql for the back end  Server was configured at UBOS § IT team monitored data transmission, aggregation and extraction  Design & Methodology  The conceptual stages involved  designing the form,  deploying the Form on the server,  deploying the form on the device,  collecting data, sending data to the server and  downloading the data from the server and analyzing the data  the Client module - functionalities of getting blank forms from the web server to a mobile phone and also filling the forms and sending the forms to the server  allows for setting logical question flow– thereby making non-applicable questions hidden from enumerator,  Administration Module : for data management , data reports, data exportation, data visualization Data collection & Extraction  Testing : Districts (Urban/Rural)  Training : Done at the Sub county level are able to submit the data and get a notification  Staffing message that the data has been submitted   Enumerators – CDOs – Parish and Village  Supervisors – District Planners & Population  Supervisors – UBOS  Rolled out to date in about 12 districts  access to the application is done through the browser, with user name & Password   No data is stored on the phone  Set validation checks are programmed into the system for answers entered ( logic skips)  some data cleaning is already completed due to these features built into the system  system is real time it allows for prompt review of data quality and makes auditing much easier  Data can be exported to different formats: CSV, Ms Excel Data is captured via the mobile client and sent via the internet using mobile data transmission technologies (edge or GSM) to a central server at UBOS Validation is done on the phone before the data is sent to the server Officers  Once a user has filled in the questionnaire, they MCIS Project planning Tasks Project Planning Duration months Proof of Concept (3 districts) weeks Design & Testing by the UBOS IT team 10 weeks Deployment and Training days Data Collection 10 days Generate Draft Data Collection Report days Lessons Piloting and iteration are critical     Security  Decide on the course of actions   target data collection efforts to the needs and  Project planning  The team should plan way in advance in usage the CIS  eliminated the fears of the government order to loose any time factors officials  Technology and Team   Composition of the team ( IT & Statisticians)  System should be fully developed  before the actual data collection exercise where possible  Training and Support      days of In-depth training of enumerators Data integrity and security  Learning curve and supervisors (questionnaire/System/Trial )  enumerators using the phone for data entry and continuous support  For the development team Benefits/ Results Reduced time   Faster, received in real time  of data collection impacting on presentation of findings  the combination of Data extraction and data entry Processes  Provision of real time data and improved data monitoring process  Reduced cost  More innovation which has lead to more capacity built and Adoption     More support from management, more awareness, training support Sustainable system that can obtain data on a regular basis    reduced paper use , storage space and paper waste Challenges  Fears to move from PAPI to CAPI – keep adopting and improving  Lack of Policy on Mobile phone use -  Training the CDOs – slow learning curve, emphasize key point & give support  Internet Connectivity  Poor network coverage - change sim cards to the network that is available/ adding an offline mode  Battery life  Phone batteries would not last the whole day  – charge with the local area centres and also some have backups and others would use their phones   using the in-built touch keypad  size of keypad especially for a very long questionnaire was seen a problem  Errors  small keys -correcting mistakes -decimal point  Data sharing to other MDAs is not yet very feasible Conclusions Policy Issues With the increasing data demands, NSOs should put in place policies that support mobile phones usage Budgeting and planning such projects is important Capacity building benchmarking encouraged for and should Infrastructure issues  Expand the use of Mobile phones to  Push for more support and collaboration from developing partners and TRIs  Do more research on the best platforms (Cross sectional and long term surveys)  Distinguish factors responsible for error rates  Measure the CBA by carrying out the same survey with both Paper & Mobile for comparison purposes Data Management issues   Network connectivity shortcomings – consider using off line platforms  Research on mobile GSM Terminals that can expand network coverage (PPPs) Management of the full data production cycle to dissemination and archiving stages should considered [...]... received in real time  of data collection impacting on presentation of findings  the combination of Data extraction and data entry Processes  Provision of real time data and improved data monitoring process  Reduced cost  More innovation which has lead to more capacity built and Adoption     More support from management, more awareness, training support Sustainable system that can obtain data on... their phones   using the in- built touch keypad  size of keypad especially for a very long questionnaire was seen a problem  Errors  small keys -correcting mistakes -decimal point  Data sharing to other MDAs is not yet very feasible Conclusions Policy Issues With the increasing data demands, NSOs should put in place policies that support mobile phones usage Budgeting and planning such projects... move from PAPI to CAPI – keep adopting and improving  Lack of Policy on Mobile phone use -  Training the CDOs – slow learning curve, emphasize key point & give support  Internet Connectivity  Poor network coverage - change sim cards to the network that is available/ adding an offline mode  Battery life  Phone batteries would not last the whole day  – charge with the local area centres and also... Capacity building benchmarking encouraged for and should Infrastructure issues  Expand the use of Mobile phones to  Push for more support and collaboration from developing partners and TRIs  Do more research on the best platforms (Cross sectional and long term surveys)  Distinguish factors responsible for error rates  Measure the CBA by carrying out the same survey with both Paper & Mobile for comparison... carrying out the same survey with both Paper & Mobile for comparison purposes Data Management issues   Network connectivity shortcomings – consider using off line platforms  Research on mobile GSM Terminals that can expand network coverage (PPPs) Management of the full data production cycle to dissemination and archiving stages should considered  ... not sustainable mobile phone Data delays and data obsolete yet wanted real time data for planning at that level lack of integration of the data -Was done with the objective of introducing the... decisions using readily available up to date information  The CIS was first implemented in 200 9 in about 50 districts  Multisectoral approach and UBOS was in charge of data processing  used...  Variances in the interfaces, server side components like databases, data reporting and management interfaces and available technology services and infrastructure  Mobile Data Collection Application