SHARING EXPERIENCES WITH MOBILE PHONE DATA

COLLECTION IN UGANDA

FLAVIA KYEYAGO OUMA

UGANDA BUREAU OF STATISTICS14th 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

electricity and room at Sub-counties

Limited HR for entry even at both Sub county & district level

Entry required long term employment not sustainable

Data delays and data obsolete yet wanted real time data for planning at that level

lack of integration of the data

- In 2011, the growing use of mobile phones pushed the IT team to innovate and experiment the use pf mobile phones on the CIS project

-The developed a web based solution which could be accessed through the web browsers that are native on the mobile phone

-Was done with the objective of introducing the alternative of MDC

-Reduce on some of the infrastructural limitations

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: 5 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 : 3 Districts (Urban/Rural)

Training : Done at the Sub county level

Staffing Enumerators – CDOs – Parish and Village

Supervisors – District Planners &

Population Officers

Supervisors – UBOS

Rolled out to date in about 12 districts

access to the application is done through the

browser, with user name & Password

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.

Once a user has filled in the questionnaire,

they are able to submit the data and get a

notification message that the data has been

submitted.

Validation is done on the phone before the

data is sent to the server.

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

MCIS Project planning

Tasks Duration

Project Planning 6 months

Proof of Concept (3 districts) 3 weeks

Design & Testing by the UBOS IT team 10 weeks

Deployment and Training 5 days

Data Collection 10 days

Generate Draft Data Collection Report 2 days

Lessons Piloting and iteration are critical

Decide on the course of actions

target data collection efforts to the needs

and usage the CIS

eliminated the fears of the government

officials

Technology and Team

Composition of the team ( IT & Statisticians) .

 Training and Support

4 days of In-depth training of enumerators

and supervisors (questionnaire/System/Trial )

and continuous support

 

.

  Security

Data integrity and security

Project planning

The team should plan way in advance in

order to loose any time factors

System should be fully developed

before the actual data collection exercise

where possible

Learning curve

enumerators using the phone for data entry

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

reduced paper use , storage space and paper waste

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

.

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

ConclusionsPolicy Issues

With the increasing data demands, NSOs should put in place policies that support mobile phones usage

Budgeting and planning for such projects is important

Capacity building and benchmarking should encouraged

Infrastructure issues

Network connectivity shortcomings – consider using off line platforms

Research on mobile GSM Terminals that can expand network coverage (PPPs)

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

Management of the full data production cycle to dissemination and archiving stages should considered

.