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
electricity and room at Subcounties

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
infrastructural limitations
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: 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
notification message that the data has been
submitted.
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
Validation is done on the phone before the
data is sent to the server.
Supervisors – UBOS


Once a user has filled in the questionnaire,
they are able to submit the data and get a

Officers



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 transmission
technologies (edge or GSM) to a central server at
UBOS.
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 Project planning

the CIS



Composition of the team ( IT & Statisticians) .

.
4 days of In-depth training of enumerators and
Data integrity and security
The team should plan way in advance in order to
loose any time factors
System should be fully developed

Training and Support



eliminated the fears of the government officials
Technology and Team


Security
before the actual data collection exercise where
possible

Learning curve
supervisors (questionnaire/System/Trial ) and

enumerators using the phone for data entry
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

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
Conclusions
Policy Issues

With the increasing data demands, NSOs  Expand the use of Mobile phones to
should put in place policies that support  Push for more support and collaboration from
mobile phones usage
developing partners and TRIs

Budgeting and planning for such projects  Do more research on the best platforms (Cross
is important
sectional and long term surveys)

Capacity building
should encouraged
and
benchmarking  Distinguish factors responsible for error rates

Infrastructure issues


Network connectivity shortcomings
consider using off line platforms
–
Measure the CBA by carrying out the same
survey with both Paper & Mobile for
comparison purposes
Data Management issues
Research on mobile GSM Terminals that  Management of the full data production cycle
can expand network coverage (PPPs)
to dissemination and archiving stages should
considered