1. KWAME NKRUMAH UNIVERSITY OF SCIENCE AND TECHNOLOGY
Geomatic Engineering Department
A GeoWeb Service for Managing
National Statistical Data
Festus Amoo Mensah & Henry Kwabena Asante
May 2016
Supervisor: Dr. Samuel Ato Andam-Akorful
A Research Project submitted in partial fulfilment of the Requirements for the Award of the
Degree of BSc Geomatic Engineering in the College of Engineering of Kwame Nkrumah
University of Science and Technology
2. i
DECLARATION
We declare that this is our own work and we submit this towards the award of the Bachelor of
Science degree in Geomatic Engineering in Kwame Nkrumah University of Science and
Technology. Except for references made to people’s work and piece of information sourced from
the internet, this study which is supervised by Dr. S. A. Andam-Akorful, is the result of our own
research. It has not been presented for another degree in this University or elsewhere.
Festus Amoo Mensah (7728812) .......................... ...........................
Student’s Name and ID Signature Date
Henry Kwabena Asante (7723412) .......................... ...........................
Student’s Name and ID Signature Date
Certified by:
Dr. Samuel Ato Andam-Akorful ........................... ...........................
Supervisor Signature Date
3. ii
ABSTRACT
In spite of limited availability, data from the GSS is not readily accessible, presenting challenges
to users of national statistical data. Additionally, not even all the freely available datasets from
GSS can be found on its website. Moreover, data from GSS, which is normally stored in tabular
forms, are mostly presented as either PDFs or hardcopy formats making general and particularly,
spatially referenced queries challenging. However, national demographic data should be readily
available to users for decision making and all sorts of analyses. This calls for the need of a
system that readily provide access to statistical data, allows querying, visualisation and
exploratory analyses. To this end, the present study aims at designing a web service that
enhances accessibility to national statistical data and can be used to query and visualise this data.
To achieve this, tabular demographic data obtained from the GSS were spatially referenced at the
regional and district levels to create a GIS using QGIS. Further, a web service was developed
using Joomla, PHP and JavaScript. This web service allows easy access to freely available
national demographic data, as well as, querying and geo-visualisation. With such a service,
national demographic data will be more readily available and interpretable to interested parties.
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ACKNOWLEDGEMENTS
This thesis could not have been performed without the help of several persons.
Special thanks to:
God Almighty.
Our supervisor Dr. Andam-Akorful for guidance, discussion and support. With his help, this
project was initially formed.
Ghana Statistical Service for providing us with our initial data.
Rev Michael of Lighthouse Chapel International, Ayeduase, also for discussion and support.
Stylish Amankwah of Maptech Logistics Ltd, whose help, we could not have finished this
project without.
Edem Agbo whose knowledge in IT and programming was of great benefit to us.
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TABLE OF CONTENTS
DECLARATION .................................................................................................................................... i
ABSTRACT......................................................................................................................................... ii
ACKNOWLEDGEMENTS ..................................................................................................................... iii
LIST OF FIGURES ...............................................................................................................................vii
LIST OF TABLES................................................................................................................................viii
1.0 INTRODUCTION.............................................................................................................................1
1.1 Background to the Study............................................................................................................1
1.2 Problem Statement...................................................................................................................2
1.3 Justification...............................................................................................................................2
1.4Aims and Objectives of Study......................................................................................................3
1.5 Research Questions...................................................................................................................3
1.6 Scope of Study ..........................................................................................................................3
2.0 POPULATION AND THE WEB ..........................................................................................................4
2.1 Introduction..............................................................................................................................4
2.2 Concept of Population...............................................................................................................4
2.3 Definitions and Terminologies....................................................................................................7
2.3.1 Population census...............................................................................................................7
2.3.2 Individual enumeration .......................................................................................................7
2.3.3 Universalitywithin a defined territory..................................................................................8
2.3.4 Simultaneity .......................................................................................................................8
2.3.5 Defined periodicity..............................................................................................................8
2.4 Role of the Census.....................................................................................................................8
2.5 Mapping and Census ...............................................................................................................11
2.6 Sharing and Accessing Census Data ..........................................................................................13
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2.7 Software and Web Service for Censuses ...................................................................................17
3.0 METHODOLOGY..........................................................................................................................19
3.1 Introduction............................................................................................................................19
3.2 Study Area..............................................................................................................................20
3.3 Research design ......................................................................................................................21
3.4 Data Collection........................................................................................................................21
3.5 Data Pre-processing.................................................................................................................23
3.5.1 Factor Analysis..................................................................................................................24
3.5.2 Age Structure....................................................................................................................25
3.5.3 Sex Distribution/Ratio .......................................................................................................25
3.5.4 Ethnicity...........................................................................................................................25
3.5.5 Nationality........................................................................................................................25
3.5.6 Religious affiliation............................................................................................................26
3.6 Geodatabase Creation.............................................................................................................26
3.7 Creating a Web Service............................................................................................................28
4.0 ANALYSIS OF RESULTS .................................................................................................................30
4.1 Introduction............................................................................................................................30
4.2 The Geodatabase ....................................................................................................................30
4.3 The Geo-Web Service ..............................................................................................................31
5.0 SUMMARY, CONCLUSIONSAND RECOMMENDATIONS..................................................................34
5.1 Introduction............................................................................................................................34
5.2 Summary of the Results...........................................................................................................34
5.3 Limitations..............................................................................................................................35
5.4 Recommendations ..................................................................................................................36
6.0 REFERENCES ...............................................................................................................................37
8. vii
LIST OF FIGURES
Figure 3.1 Flowchart.........................................................................................................................19
Figure 3.2 District Map of Ghana.......................................................................................................20
Figure 3.3 Original Format of Population Data....................................................................................22
Figure 3.4 Excel Format of the Population Data ..................................................................................23
Figure 3.5 Layer Properties................................................................................................................27
Figure 3.6 Export to Web Map...........................................................................................................28
Figure 4.1 Map Displayed Online .......................................................................................................30
Figure 4.2 Web Service Interface .......................................................................................................32
Figure 4.3 Contact Us form................................................................................................................33
Figure 7.1 Distribution of Age Structure at the Regional Level .............................................................44
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LIST OF TABLES
Table 7.1 Distribution of Sex Structure at the Regional Level ..............................................................41
Table 7.2 Distribution of Age Structure at the Regional Level...............................................................42
Table 7.3 Distribution of Nationality at the Regional Level...................................................................42
Table 7.4 Distribution of Religion at the Regional Level.......................................................................43
Table 7.5 Distribution of Ethnicity at the Regional Level......................................................................43
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1.0 INTRODUCTION
1.1 Background to the Study
The Ghana Statistical Service is the main authority for undertaking national censuses in Ghana.
The 2010 Population and Housing Census (PHC) is the fifth census conducted since
independence (PHC, 2012). Previous post-independence censuses were conducted in 1960, 1970,
1984 and 2000. According to the 2012 Population and Housing Census (PHC) report, Ghana’s
population stood at 24,658,823 at the time of the 2010 census. The country has ten administrative
regions and 170 districts. Ghana has one of the highest GDP per capita in West Africa and is
ranked as a Lower-Middle Economy by the World Bank (Ghana Statistical Service (GSS),
2013). At the last census in 2000 the total population in the country was 18.9 million, with an
average growth rate of 2.7% (Ghana Statistical Service (GSS), 2013). Ethnically, the people of
Ghana belong to one broad group within the African family, but there is a large variety of
subgroups. It is possible to distinguish at least 75 of these on the basis of language.
Ghana has in the last two decades experienced a phenomenal growth in Information
Communication Technology (ICT) penetration in every facet of the economy - business,
education, governance, agriculture etc. The speed with which ICT is developing and its impact
on socio-economic activities cannot be overemphasized as it is constantly growing in importance
in terms of its contribution to GDP, and employment (mostly the youth). The drivers of the ICT
industry currently are the mobile phones and internet services. According to the 2010 PHC,
internet subscription per 100 populations stood at 5.3. Internet usage in Ghana has not been
maximized to its full potential. Technological advancements have necessitated a need for a
transition from paper records to electronic records to make life easier for everyone. This research
project will give an overview of how this may be addressed.
Although the GSS is the main statistical body of the country, it is stressful acquiring data from
them. It is also not easy to acquire geospatial information from their website as found on other
websites such as the US Census website. The information on the GSS website is quite difficult to
appreciate.
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1.2 Problem Statement
Statistical data from the Ghana Statistical Service (GSS) is not readily accessible, thus interested
parties face difficulties acquiring data for usage. Acquiring census data from the GSS regional
offices can be quite problematic at times. Interested parties may have to pass through some
bureaucratic procedures before getting access to the data or dataset they need. Also, not every
dataset is allowed for public viewing. Some files may be restricted.
Additionally, not even all the freely available datasets from GSS can be found on their website.
Even with those datasets that are available, not all of them have been posted on the website for
individuals to access. Ghana has conducted five censuses since independence but it is only the
2010 population census data that can be found on the website.
Data from GSS is normally stored in tabular forms and mostly presented as either PDFs or
hardcopy formats which makes general and particularly, spatially referenced queries challenging.
There is no visual display of queries made because the dataset has no spatial information. There
is evidence of this on the GSS website http://www.statsghana.gov.gh/socio_demo.html.
1.3 Justification
The purpose of this research is to establish a web service for managing national statistical data
which unlike a website provides services to the user. The web service will display population
data and the various statistical interpretations that have been applied to the data that would be of
significance to the lay person. The web service will also help business executives, researchers
and students make analyses with the data available. It is sometimes difficult to access statistical
data for analysis. At times, an individual is required to visit the regional GSS office to be able to
acquire relevant data. This may tend to be stressful and inconvenient. Hence, an easier and
convenient method is needed. This web service would benefit every individual who has access to
a computer or hand-held device with internet service. The benefits of the web service are:
Improved business processes through faster access to and retrieval of information.
Better-informed decision-making through quicker access to all of the right
information.
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Better service delivery because relevant information can be located easily.
Less staff time looking for information. There are fewer information silos.
More info sharing across the agency and between agencies.
Lower compliance costs and enhanced ability to provide accurate, timely and
transparent responses to legislative and regulatory requirements.
Mitigation of business and reputational risk and improved business continuity.
Cost savings from less creation, storage, retrieval and handling of paper records.
Digital records management will better support disaster recovery and business continuity.
Managing your info digitally allows off-site back-up of records which a paper-based system
cannot easily offer. It also safeguards vital corporate info from loss, misuse, tampering and
physical damage.
1.4Aims and Objectives of Study
The main aim of this study was to design a web service that enhances accessibility to national
statistical data and can be used to query and visualise this data. The objectives are:
a) To create a geodatabase from the collected statistical data.
b) To design a web service to enable querying and visualization of the data.
1.5 ResearchQuestions
a) How can a spatially-intelligent database, where all statistical data regarding the
2010 population census can be accessed, be built?
b) How can it be hosted online so that it can be accessed by everyone?
1.6 Scope of Study
The focus of this study was based on the demographics of Ghana from the regional level down to
the district level. This study sought to display information in all these locations and the
breakdown of the population figures in these locations. The dataset used was the 2010 population
census which was acquired from the GSS website. The 170-district shapefile of Ghana that was
also used as acquired from the internet.
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2.0 POPULATION AND THE WEB
2.1 Introduction
This chapter presents already existing literature relevant to our topic in the field of population
data and web services including theoretical and conceptual frameworks. The sample data used
for this study is based on the population census conducted in the year 2010. This study seeks to
examine theoretical and conceptual frameworks about population; the demographic analysis that
can be made on this population data and how best these results can be displayed and accessed
using web services.
2.2 Concept of Population
According to the 2015 UN Population and Housing Censuses Report, human capital is the most
critical capital for contemporary societies’ wellbeing and advancement. It is essential to provide
an exact and true judgment of this capital at small area, regional and national levels of evidence-
based governing, civil societies, faculty members and researchers.
Aside from the answer to the question “How many are we?” there is also a need to provide an
answer to “Who are we?” in terms of age, sex, education, occupation, economic activity and
other crucial characteristics as well as access to the Internet. The responses to these questions
offer a mathematical profile of a country which is the sin qua non of evidence-based decision-
making at all tiers, and are indispensable for monitoring universally recognized and
internationally adopted post- 2015 Development Agenda Goal (United Nations, 2008).
Population Censuses have played a key part in the evolution of modern socioeconomic
techniques. The data collected has been used as evidence in much policy making and socio-
economic research. Nevertheless, it is unlikely that the entire potential of population censuses
has ever been made. With the increasingly potent data processing power available to users of
statistics it is becoming critical to ensure as comprehensive exploitation of census data as
potential. Detailed small area statistics are imposing themselves as irreplaceable in pointing to
the segments of everyday life that necessitate to be amended in terms of enduring conditions,
access to services, adequate infrastructure and fulfilment of essential human rights, such as the
right to be registered or the right to vote, for instance. Their depth of coverage and completeness,
which is their chief attraction, makes the datasets, large and complex to handle, making it
14. 5
difficult to use them to the full. In the Bond article (2001), it is noted that modern statistical
techniques and theories that have, generally, been developed to assist in the reduction of large
amounts of primary and secondary data into seemingly useful and manageable information
would seem ideal to handle such a dataset.
The traditional census is among the most complex exercise a nation undertakes. It demands that
the whole country be mapped, mobilizing and training an army of enumerators, conducting a
massive public campaign, canvassing all households, collecting individual information,
collecting vast amounts of completed questionnaires, and analysing and disseminating the
information.
A census is defined as an operation which produces an official count of a country’s population,
right down to the lowest level of geographical detail, at regular intervals (Baffour, King, &
Valente, 2013). In this definition, the essential characteristics which differentiate a census from
other exercises: individual enumeration, simultaneity, universality and defined periodicity are
stated. Therefore a census obtains information on everyone, at the same time, in the entire
country, and is conducted periodically. Baffour et al. (2013) said that this definition disguises a
wide variation in approach, context and quality of outcome. By reviewing these, we aim to show
that there are common themes in quality which apply to the modern census, even as more
variation develops in practice.
The modern census is regarded to have emerged in the period after the 18th century, when it is
widely accepted that nations started conducting censuses in line with proven statistical
methodologies and, later on, internationally agreed definitions and good words. Missiakoulis,
Vasiliou, & Eriotis (2010) say that the first actual census took place in the 16th century BC in
ancient Athens; earlier studies had included only adult males with the specific purpose of
evaluating military potential. Historically, these censuses developed from the idea of a
numbering, or enumeration, using processes as simple as counting a pile of rocks where each
individual added one to the pile (Missiakoulis et al., 2010).
In the eighteenth century, the premise that “the true measure of the power of a state is in its
population” (Hacking, 1990) led to principal statistical offices being established to produce
population statistics in Western countries. Thus, the first censuses were implemented well before
15. 6
the advent of sampling theory, meaning that counting the whole population was the only reliable
method of getting any demographic statistics (Bethlehem, 2009). This developed to an approach
which identified households as the primary units where individual enumeration would be done
and the recording of characteristics, for instance, age, and became as necessary as the
enumeration. This allowed comprehensive, coherent and simultaneous enumeration to be made
rather than the aggregation of numerous idiosyncratic local records (Higgs, 2003). Census
enumeration spread from European nations to their colonies around the world (Hooker, 1894),
and they also developed independently in some American nation (Baffour et al., 2013).
The United Nations recommends that all countries or areas of the world produce detailed
population and housing statistics for small area domains at least once in the period 2015-2024,
around the year 2020. The population and housing census is part of an integrated national
statistical system, which may include other censuses, surveys, and registers. It furnishes, at
regular intervals, the benchmark for population count at national and local levels.
The purpose of a census is to provide relevant population data to users in context, but it traces
that this data must meet users’ expectations in terms of character, appropriately defined. Hence
the judgment (and evaluation) of quality in a census is important, in the first place in fostering
confidence in the information produced by the census but also for planning for future data
collection. Population data are thrown forward from census day and are used to underpin
surveys, for instance, in drawing samples and making statistically representative of the whole
population. Therefore, the census acts as the baseline for comparison when users go on to collect
their own data. The census is also the best, if not the only, source of information on small
population groups in terms of area or membership. Finally, a country’s census information is
used by international organisations in projections of the world population, and relatedly, it
underpins national accounts which allow the understanding of international credit risk. The
census has a unique role in both the national and international statistical system (Baffour et al.,
2013).
16. 7
2.3 Definitions and Terminologies
2.3.1 Population census: The Free Dictionary Online defines census as “the process of collecting
demographic, economic, and social data characterizing each inhabitant of a country or territory at
a definite time or period” and also states that “the concept of the census sometimes also refers to
the summarizing, processing, and publishing of these data. Censuses are conducted to obtain
information on the size, composition, and location of the population”. The Merriam-Webster’s
Legal definition of census states that “a census is a complete count of a population (as of a state);
especially a periodic governmental count of a population that includes social and economic
information (as occupations, ages, and incomes)”. Censuses should re regularly taken and it is
the official counting of a country’s population.
The United Nations population census as “the total process of planning, collecting, compiling,
evaluating, disseminating and analysing demographic, economic and social data at the smallest
geographical level pertaining, at a specified time, to all persons in a country or in a well-
delimited part of a country” and recommends that the census be taken every 10 years.
A country’s population is fundamental to the production and distribution of material wealth. It is
necessary to receive dependable and detailed information on the size, distribution and
composition of the population in order to plan for, and implement, economic and social growth,
administrative activity or scientific inquiry. The population census is a primary root of these
basic benchmark statistics, handling not only the settled population but also homeless persons
and mobile groups. Data from population censuses should allow analysis in terms of statistics on
persons and households and for a spacious variety of geographical elements, taking into
consideration the nation as a whole entity to the smaller localities.
2.3.2 Individual enumeration: According to the United Nations, the term census “implies that
each individual and each set of living quarters is enumerated separately and that the
characteristics thereof are separately recorded”. The demand of individual enumeration can be
fitted by the assembling of data in the field, by the usage of data contained in an appropriate
administrative register or set of registers, or by a combination of these method (Commission,
2015).
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2.3.3 Universality within a defined territory: The census should cover an accurately defined
region and the census should include every individual present at the time and/or residing within
its range, depending upon the type of population count being carried out (Commission, 2015).
2.3.4 Simultaneity: A population census should be carried during a specific period and the data
collected should be referenced to that period should be well-defined. The census does not,
however, need to be identical for all of the data collected. For most of the data, it will be the day
of the census. (Commission, 2015)
2.3.5 Defined periodicity: Censuses should be conducted at regular intervals so that data that is
related is made available in a specified sequence. A series of censuses makes it possible to
evaluate the past, accurately identify the present and estimate the time to come. According to the
UN, it is recommended that a national census be taken at least every 10 years. Some countries
may have do this more regularly due to high rate of change in the population size (Commission,
2015).
It is indicated in the UN Population and Housing Censuses Report (2015), that, the census data
of any country are of greater value nationally, regionally and internationally if they can be
compared with the results of censuses of other countries that were taken at approximately the
same time. Therefore, countries should make all efforts to undertake a census in years ending in
“0” or at a time as near to those years as possible. It is obvious, however, that legal,
administrative, financial and other considerations often make it inadvisable for a country to
adhere to a standard international pattern in the timing of its censuses. In fixing a census date,
therefore, such national factors should be given greater weight than the desirability of
international simultaneity (Commission, 2015).
2.4 Role of the Census
The role of the population census is to collect, process and disseminate in depth statistics on
population, its composition, characteristics, spatial distribution and organization. Censuses are
conducted periodically in most countries; they have been conducted since the International
Statistical Congress recommended that all countries in the world conduct them.
18. 9
The roles of the population census are many have been elaborated in detail throughout the
present revision of the UN Principles and Recommendations for Population and Housing
Censuses (2015). Several of the essential roles are listed below:
(a) The population and housing census plays an essential role in public administration. The
results of a census are used as a critical reference to ensure equity in distribution of wealth,
government services and representation nationwide: distributing and allocating government
funds among various regions and districts for education, health services, delineating
electoral districts at the national and local levels, and measuring the impact of industrial
development, to name a few. Establishing a public consensus on priorities would be almost
impossible to achieve if it were not built on census counts. A wide range of other users,
including the corporate sector, academia, civil society and individuals, make use of census
outputs.
The fundamental purpose of the population census is to provide the facts essential to
national policymaking, planning and administration. Information on the size, distribution
and characteristics of a country’s population is essential for describing and assessing its
economic, social and demographic circumstances and for developing sound policies and
programmes aimed at fostering the welfare of a country and its population. The population
census, by providing comparable basic statistics for a country as a whole and for each
administrative unit, locality and small areas therein, can make an important contribution to
the overall planning process and the management of national affairs. Counts of the
population overall, or of sub-groups within the population, by geographic region are often
used for the distribution of government funding and services. Population censuses in many
countries represent the very foundation of their national statistical systems, with census data
providing important baseline data for policy development and planning, for managing and
evaluating programme activities across a broad range of sectorial applications, and for
monitoring overall development progress. An emerging use for census data is the
assessment of good governance by civil society groups. The performance of a
democratically elected government in improving the welfare of its citizens can be
monitored from one census to the other by ordinary citizens through the widespread and
timely dissemination of census results.
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(b) The census also plays an essential role in all elements of the national statistical system,
including the economic and social components. Census statistics are used as benchmarks for
statistical compilation or as a sampling frame for sample surveys. Today, the national statistical
system of almost every country relies on sample surveys for efficient and reliable data collection.
Without the sampling frame and population benchmarks derived from the population and
housing census, the national statistical system would face difficulties in providing reliable
official statistics for use by the Government and the general public.
(c) The census results are used as a benchmark for research and analysis. Population projections
are one of the most important analytical outputs based on census data; future population
projections are crucial for all segments of the public and private sectors.
(d) A population and housing census may also serve as the starting point for construction of
computerized statistical services to serve continuing national and local needs.
(e) In addition to serving specific governmental policy purposes, the population census provides
indispensable data for the scientific analysis and appraisal of the composition, distribution and
past and prospective growth of the population. The changing patterns of urban/rural
concentration, the development of urbanized areas, the geographical distribution of the
population according to such variables as occupation and education, the changes of the sex and
age structure of the population, and the mortality and fertility differentials for various population
groups, as well as the economic and social characteristics of the population and the labour force,
are questions of scientific interest that are of importance both to research and for solving
practical problems of industrial and commercial growth and management.
(f) In addition to those uses given above, the census has many important uses for individuals and
institutions in business, industry and labour. Reliable estimates of consumer demand for an ever-
expanding variety of goods and services depend on accurate information on the size of the
population in subnational areas and its distribution at least by sex and age, since these
characteristics heavily influence the demand for housing, furnishings, food, clothing, recreational
facilities, medical supplies and so forth. Furthermore, the census can be used to generate
statistics on the size and characteristics of the supply of labour needed for the production and
distribution of such commodities and services in conformity with International Labour
20. 11
Organization statistical standards. Such statistics on the local availability of labour may be
important in determining the location and organization of enterprises.
(g) One of the basic administrative uses of census data is to support political and administrative
mapping. Detailed information on the geographical distribution of the population is
indispensable for this purpose. Certain aspects of the legal or administrative status of territorial
divisions may also depend on the size and characteristics of their populations, for example,
whether a previously rural area is now to be declared as urban.
A compelling use of census data is in the redrawing of electoral constituency boundaries in most
countries. This is often enshrined in the country’s constitution and provides a legal basis for
census taking. The current distribution of a country’s population is thereby used to assign the
number of elected officials who will represent people in the country’s legislature.
2.5 Mapping and Census
The UN report (2015) goes on to say that the census mapping programme should be developed at
a very early stage of census planning considering the conditions and available resources of the
country. Countries should evaluate available mapping options by considering the following
factors: i) available geographic resources , ii) requirements for new technologies and
approaches, iii) available funds and the allocated time frame , iv) staff capacity needed for new
approaches, and v) requirements for developing an ongoing geographic system.
A number of mapping techniques may be employed. There are still a few countries which still
use traditional mapping techniques due to their relevance in those countries. However, with the
recent technological developments, countries are now motivated by new technologies to develop
digital mapping techniques and improve the quality of census operation. Application of new
technologies requires more careful and long term functional and management plans based on a
realistic appraisal of costs and human resources needed. In the case where the human resource
available is not able to carry out the census, the activities that are needed to be outsourced should
be critically examined before deciding the likely options for census mapping programmes.
Major technological advancements include the extensive availability of PC’s, hand- held devices,
global positioning systems (GPS), geographic information systems (GIS) software and low-cost
21. 12
aerial and satellite imagery. These advances have put new tools in the hands of national
statistical organizations to collect more accurate and timely information about their populations.
There is prevalent school of thought that it is important for national statistical agencies to
develop a continuing mapping capability to serve their specialized mapping needs. This would
contribute to the analysis and presentation of census results.
At both the global and regional levels there is a continuing initiative to ensure a complete
integration of statistical and geospatial information as a critical piece of national systems for
providing comprehensive overview of many social, economic and environmental phenomena.
The ultimate goal is to develop a global statistical-geospatial framework that would make
accurate, authoritative, reliable geospatial information readily available to support national,
regional and global development (Commission, 2015).
Maps serve as support in the census process to help present aggregate census results in
cartographic form. Many censuses have been done with the help of detailed maps.
In general terms, mapping serves several purposes in the census process, according to the UN
Report (2015), as follows:
(a) Maps ensure coverage and facilitate census operations. The census bureau needs to insure
that every household and individual in the country is counted and that no households or
individuals are calculated double. For this use, census geographers partition the national territory
into small data-collection units. Maps showing enumeration areas, thus provide an essential
control device that ensures coverage of the census; (b) Maps support data collection and can help
supervise census activities (during enumeration). During the census, maps ensure that
enumerators can easily identify their assigned geographic areas, in which they will enumerate
households. Maps are also come forth to the census supervisors assigned to enumerators to
support preparation and command tasks. Maps can thus also take on a part in monitoring the
progress of census operations. This allows supervisors to strategically design, work assignments,
identify problem areas and carry out remedial action quickly; (c) Maps make it easier to present,
analyse and disseminate census results (post- enumeration). The cartographic presentation of
census results provides a potent means for seeing the consequences of a census. This confirms
22. 13
the recognition of local forms of important demographic and social indexes. Maps are thus an
integral piece of policy analysis in the public and private sectors.
2.6 Sharing and Accessing Census Data
Demographic analysis offers an approach for assessing the character of a census and countries
are encouraged to utilize it as part of their overall census evaluation approach. A full diversity of
demographic techniques that have been developed and used, ranging from visual inspection of
census information to comparative analysis of two census age distributions (Commission, 2015).
Stable population theory has also been applied in the past to measure the quality of census
distributions by age and gender. It is based upon measuring the reported age-sex distribution
against that of an appropriately chosen stable population, striking that the population is not
touched on by significant international migration. Nevertheless, today there are few states where
the other two conditions assumed under the model, namely constant fertility and constant or
recently declining mortality, are met. Recent falls in fertility render the technique less useful as
an evaluation tool, since the technique is sensitive to changes in fertility levels.
It is of overriding importance that census data and information produced are widely passed
around and communicated, and that national statistical/census offices involved in this process
have a pronounced customer/client and stakeholder focus. That implies that national
statistical/census offices should place more emphasis on supplying a service and creating
partnerships than on merely providing products, and should be guided by user-relevance and
user-friendliness in all their operations, rather than by tradition in creating tables, graphs and
reports that they have invariably made.
Given its importance and widespread use, the web has emerged as the main means of providing
universal access to census statistics. Many national statistical/census offices have utilized the
internet as the principal channel for information communication, positioning their websites into
comprehensive census data repositories, enabling users to deliver entree to all published data
online. When developing new census products, and when reviewing existing products, national
statistical/census offices should consider all ways and means of making census statistics
accessible, giving high priority to dissemination on the internet. The advantages of online
dissemination are primarily in terms of velocity, flexibility and cost as well as in providing
23. 14
accessibility to census results to a broad reach of data users and permitting the delivery of data to
be tailored to the degree of sophistication of the user.
Taking in a census database available online along with integrated searching, tabulating,
graphing, mapping and analysis capabilities is an important means to improve the effectiveness
of census data dissemination. Most national statistical/census offices provide user access to
electronic databases and data files through their websites, satisfying the broad range of needs of
internal and external data users. This is a valuable service that allows users to access and display
census data instantaneously and interactively. The formation of such databases can enhance the
dissemination of census results as well as increase their utility by allowing user interaction with
census information. User interaction is a key concept whereby users are enabled and empowered
to access and explore census data themselves, and make their own customized tables or spatially
configure data outputs according to their own demands.
Interactive web-based data tools provide a user-friendly entry-point to the entire range of census
outputs disseminated by national statistical/census offices. Basic design considerations of
network- based interactive tools should factor issues such as identification of the dissimilar types
of users, their information requirements and the types of data to be stored in the database.
Capacity should be organised so that it can be easily seen and found, with an overview presented
to provide orienting information to users about the data that can be accessed utilizing the
interface. Context should always be catered for all outputs through metadata, links to related
information, and cross-referencing to glossaries, publications and other background stuff.
In pragmatic terms, interactive web-based data tools should enable users to access census data
themselves, and make their own customized tables or spatially configure data outputs according
to varying spatial requirements. The instruments should allow users to envision and explore the
data in column charts, line graphs, maps, and scatter plots. The table building functionality
should also hold the ability to classify and order tabular results, and more easily select survey
years and indicators. Tools should also be provided for downloading, conducting analysis or for
retrieval for use in other software. Design considerations to improve the interactivity of data
interfaces should include the preparation of user documentation. It is extremely urged to assist
users to anticipate, interpret and assess outcomes. Support to users should include presentations
24. 15
and tutorials intended to describe how to do the various occasions related to the interactive web-
based instruments.
Bond (2001) says, in his article, that, in an increasingly globalised world most socioeconomic
activities do not stop at national borders so there is a need to share information across
international boundaries. He goes on to say that despite this, the problems of sharing data are
many and range from the issues of compatibility of formats and comparability of coverage to
issues of commercial development. At the urban and regional level many of these effects are
more acute than at the house level. For example when comparing small area data minor
definitional differences can result in major problems.
In Worrall & Bond (1997) it was indicated that the commercial or quasi commercial nature of
much of the attribute data taken for the successful growth of GIS is a major hindrance in many
GIS implementations. This thing be a special problem when trying to add value to Census data
by connecting it with other spatially referenced secondary data sets. The secondary data used is
often at a resolution and detail that it of use in the commercial sector for such matters as
marketing, utilities management, etc. and is the main origin of non-public revenue for the public
body collecting the data. With the increasing requirement in many lands that their public sectors
to move to cost recovery models this has a serious implication the further funding of Population
Censuses (Bond, 2001).
Improvements in data and communication technologies have gone both to an increase demand
for spatially reference data, such as Population Censuses and also to its availability, dependent to
the claim martial and confidentiality problems discussed above. Whilst being part of the catalyst
for this increased demand for data, GIS has come to be regarded as part of the answer to the
problem of developing effective access to heavy amount of spatially referenced information.
Very large spatial datasets, such as Population Censuses, are becoming available through such
issues as digital libraries (Smith & Frew, 1995), data archives (Lievesley, 1992) and data
warehouses (Jarke, Quix, & Calvanese, 2000). Users are confronted with the problem of
detecting and correctly using relevant information from such beginnings. This task can be a bit
intimidating.
25. 16
In recent years there has been a increase in interest in the use of metadata to help search such
data roots (Bond, 2001). The trouble is that there are no harmonized standards for metadata,
though in the social science community attempts are being established to standardize on the
'Dublin Core' (Lee-Smeltzer, 2000). Several tasks, such as NESSTAR/FASTER
(http://www.faster-data.org) in the European academic community, are attempting to provide
user-friendly interfaces to attribute information using metadata-based interfaces. The problem
facing researchers and other users of the data sets is lack of detailed knowledge of the data that
can be gained from the data held in these complex databases. The visual component of GIS has
always played a big division in its popular appeal and research has shown (Smelcer & Carmel,
1997) that, provided the project is relatively simple, a map can provide an ideal starting point for
information discovery. This has led to increase in GIS based interactive information seeking
software. The purpose of this software is to replace traditional text-based data retrieval strategies
with ones based on visualisation and knowledge discovery in databases (Fabrikant, 2000).
Knowledge Discovery in Databases (KDD) has been defined as 'the non-trivial process of
identifying valid, novel, potentially useful, and ultimately understandable patterns in data'
(Fayyad, Piatetsky -Shapiro, & Smyth, 1996). KDD is closely related with data mining and uses
the computational ability of innovative IT to explore data sets rather than banking on data
reduction techniques. Central to this debate is the fact that with the increasing performance and
passing costs of ICT the reliance on mainly parametric based data reduction techniques for
analysing Censuses is being disputed. It is becoming increasing cost-effective for end-users to
handle the large-scale datasets themselves. One of the main areas where this trend is most
pronounced in the manipulation and analysis of spatially referenced data using Geographic
Information Systems (GIS). The Census of Population is a major spatially reference data set and
its analysis has played a central part in the popularisation of spatial techniques in the economic
and social sciences. The controversy is however somewhat more complex. Many of the original
dreams and prospects of what GIS could offered do not seem to have been realised. In many
cases doing little more than replacing paper maps and records with digital equivalence. The
purpose of GIS and spatial analysis at the strategic and policy related levels are presently set.
Diverse perspectives on this have been put forward covering aspects such as accessibility of tools
to management issues for example Worrall & Bond (1997) indicate that the primary issues are
organizational.
26. 17
With the decreasing price of ICT society is going towards a data rich environment. In such an
environment Censuses should play a key role ensuring that the data carried in such data is
effectively realised. This introduces new challenges to those affected in all stages of the
solicitation and analysis of Census information. Central to this is the role of Censuses as major
spatial data sets and the special value of seeing them as such in all stages of maturation and
execution.
2.7 Software and Web Service for Censuses
It is therefore expedient to move away from static map data facility to a more dynamic,
distributed and collaborative environment in this age of modern technology. Geo Web Services
can bring together a wide range of data from various sources, along with geospatial services that
can interact in a loosely coupled environment and be used to create more suitable information for
different stakeholders.
According to Maiyo, Kerle, & Köbben (2010) here exists a range of patented Geo Web Services
in the market. A few are Google Earth/Maps, Yahoo Maps and Microsoft Virtual
Earth/MultiMap. The data can be viewed through these services using free geo-browsers and are
available in both 2D and 3D. In addition to this, non-proprietary Open Standards have been
developed in an open and sharing process, and are owned in common. Examples of Open
Standards for Geo Web Services are the Open Web Services (OWS) specifications of the Open
Geospatial Consortium (OGC). There are OWS specifications for parts of the spatial data
storage, analytic thinking and delivery process: for geographic data encoding in that respect are
the Geographic Markup Language (GML), and for spatial data delivery the Web Coverage
Service (WCS) and Web Feature Service (WFS), for querying and retrieving raster and vector
data, respectively. For processing of spatial data the Web Processing Service (WPS) has been
defined, and Web Map Service (WMS), for data visualization in the form of maps. An emerging
specification is GeoDRM, specifying Digital Rights Management of geodata.
Geo Web Services allows fast collation and analysis of distributed dataset with high intelligence
and expert knowledge, leading to a wide range of services for a long term, comprehensive
system in population services. Thus a Geo Web Services approach can connect the various
population census datasets, allowing more customized delivery of data and information, and
27. 18
allow users to add value by providing their own information and getting a result, creating new
interactions in a loosely coupled environment.
The difference between a web site and a web service is that a web site presents data in a way that
is viewable by a browser. It allows for user interaction of some kind.
A web service supplies a number of services, typically accessed by other software elements. On
the other hand, web service receives a request, possibly containing some input data, performs
some processing and, optionally, returns a result (CodeRanch, 2016).
28. 19
3.0 METHODOLOGY
3.1 Introduction
This chapter was focused on the research design, the study area, methods for collecting data, and
the procedure for data analysis. This project was taken through various stages before arriving at
the completion stage. This work did not require direct collection of field data. Therefore the
2010 census data was collected from the GSS and the shapefiles used were collected from other
sources on the internet. The collected data was passed through some pre-processing analysis to
be able to segregate the relevant information from the irrelevant ones. In instances where the pre-
processing did not meet quality specifications, the process was repeated until it was successful.
Then, shapefiles were created from the analysed data and organized into a geodatabase. Finally,
a web service was developed using Joomla.
Figure 3.1 Flowchart
29. 20
3.2 Study Area
Ghana is located on the coast of the Gulf of Guinea in West Africa. It has a land area of 240,000
km2
. Ghana is one of the most densely populated countries in West Africa. The majority of the
population is black African, where the major tribes are Akan, Moshi-Dagomba, Ewe and Ga. The
official language is English, and the neighbouring French speaking countries are Cote d’Ivoire to
the west, Burkina Faso to the north and northwest, and Togo to the east. In 1957, Ghana was the
first nation in sub-Saharan Africa to achieve independence. Ghana is mainly a lowland country.
Exceptions are a range of hills that lie on the eastern border and Mt. Afadjato (884 m asl), which
is to the west of the Volta River. The climate is tropical, but temperatures and rainfall vary by
distance from the coast and elevation. The average annual temperature is about 26ºC. There are
two distinct rainy seasons, April to June and September to November. Generally, rainfall
decreases from the tropical south‐western part of the country (2,000 mm/year) towards the
savannah area that covers the northern and eastern part (950 mm/year). The driest area is the
south east‐coastal plain (800 mm/year) (Norström, 2009). Accra, the capital of Ghana is the
financial, economic and administrative centre of the country. Spatially, Accra is generally
unplanned and characterized by overcrowding and substandard housing, especially in low-
income areas. The problem of urban growth in Ghana has escalated during the last decades and
the capital has a growth rate of 3.2% compared with 2.8% for the rest of the country (Acolor &
Kariuki, 2000).
Figure 3.2 District Map of Ghana
30. 21
3.3 Researchdesign
This study applies a library research method. Population data from the 2010 population census
was collected from the Ghana Statistical Service Department for analysis. Data was collected by
visiting the regional branches of the GSS and their website as well. Other sources were also used
to acquire data, for instance, the shapefiles of the districts and towns, which was not be found on
the GSS website.
3.4 Data Collection
The goal for all data collection is to capture quality evidence that then translates to rich data
analysis and allows the building of a convincing and credible answer to questions that have been
posed. According to Masters & Ela (2008), data collection consists of direct and indirect
methods. Direct data come from vital statistics registries that track all parameters of population;
births, changes in marriage, divorce, and migration. In the developed countries with good
registration systems (such as the US and Europe), registry statistics are the best method for the
collection of data. In developing nations such as Ghana, registry statistics cannot be used because
full data is not available. A technique that is prevalent is indirect estimation in for instance, birth
or death rates, for the entire population. There are a variety of demographic methods for
modelling population processes, including models of mortality, fertility and marriage models.
This study will focus on collection of population census of 2010. The government department
which will be involved is the Ghana Statistical Service Department.
31. 22
Figure 3.3 Original Format of Population Data
Figure 2 shows the original format in which the data was collected. The data found on the GSS
website is in PDF. This format makes spatial querying impossible since it does not have a spatial
component, and even makes editing and updating very difficult.
32. 23
Figure 3.4 Excel Format of the Population Data
The data that was collected was organized in MS Excel according to the various categories such
as age, sex, religious affiliation, nationality and ethnicity.
3.5 Data Pre-processing
1. Data Management: the documents were accumulated and organized into folders as texts.
2. Description: using data from multiple sources - Ghana Statistical Services and other internet
sources - a rich depiction of contexts were declared under investigation.
3. Pre-processing: the data was influenced by creating and applying abstract categories and then
use those categories to compare, contrast, sort, and refine distinguishable trends in Ghana’s 2010
population data.
4. Interpretation: informed by descriptions and analysis, the researcher then proceeded to make
inferences by connecting the data with the theoretical structure that frames the study. The
essence is to develop an expressive, multi-dimensional category, which form an initial structure
for analysis.
33. 24
3.5.1 Factor Analysis
The following features were the variables that were extracted from the 2010 GSS Analytical
Report. From these variables, age structure, sex distribution/sex ratio, ethnicity, religion, and
nationality were selected because they are the variables that had spatial information related to the
districts.
DEMOGRAPHIC FEATURES
1 Age structure *
2 Sex distribution *
3 Life expectancy
4 Fertility rate
5 Population density
6 Urban-rural distribution
7 Ethnicity *
8 Religion *
9 Education
10 Net migration
11 Dependency ratio
12 Housing conditions
13 Growth rate
14 Median age
15 Sex ratio *
16 Birth rate
17 Death rate
18 Infant mortality
19 Nationality *
* The demographic features under study (Gbogbo, 2011)
34. 25
The factors used for the analyses were chosen based on the availability of data from the
analytical reports provided by the GSS. Some of these information were available up to the
district level while others had only up to the regional level available.
3.5.2 Age Structure
Total census figures have one significant demographic element, national age distribution. The
table above reveals a pre-dominantly large dependency group made up of people below the age
of fifteen (<15) and above sixty-five years of age (>65). In 2010, Ghana's population was
24,658,823. About 38.32% fall below age 15. The large population of young people represents
economically unproductive individuals. Besides, 4.73% were in the above sixty-five (> 65) age
group. We need to emphasize here that the under-fifteen group and those above the age of sixty-
five are regarded as the dependent group.
3.5.3 Sex Distribution/Ratio
The gender ratio of the population, 95.2 males to 100 females, was reflected in the 2010 figures
of 12,024,845 males to 12,633,978 females. About 48.76% of the total population were males
while 51.24% were females. More than half of Ghana’s population are female. This statistic
should affect the policies that are made and should also affect affirmative action.
3.5.4 Ethnicity
From the 2010 census, the results were follows: Akan 45.91%, Mole-Dagbon 16.07%, Ewe
13.48%, Ga-Dangme 7.16%, Guan 3.57%, Gurma 5.53%, Grusi 2.41%, Mande 1.09%, other
tribes 1.39%.
3.5.5 Nationality
The highest proportion of non-Ghanaians was in the Greater Accra region (3.0%), where Accra,
the national capital, and Tema the leading port in the country, are located. These two cities are
where most of the economic and industrial activities occur. Upper East and Upper West followed
35. 26
Greater Accra, with 2.9 percent of their population registering as non-Ghanaians. This is due to
their proximity to the neighbouring countries of Togo and Burkina Faso. Eastern region recorded
the lowest proportion (1.7%) of non-Ghanaians. Volta recorded the highest proportion of
Ghanaians by naturalization (2.7%) (Ghana Statistical Service (GSS), 2013).
3.5.6 Religious affiliation
Seventy-one percent of the population (71.2%) reported to be Christians (Catholic, Protestant,
Pentecostal/Charismatic and other Christian) in 2010, followed by Islam (17.6%) and
Traditionalists (5.2%). About five percent (5.3%) indicated that they had no affiliation to any
religion (Ghana Statistical Service (GSS), 2013).
3.6 Geodatabase Creation
According to Baldridge (2012), geodatabase is an alternate way to store GIS information in one
large file, which can contain multiple point, polygon, and polyline layers. ESRI is pushing the
geodatabase idea, because it is a less “messy” way of organising data than having multiple
shapefiles in multiple folders.
During this work, QGIS was mainly used to display the data we collected into the various
thematic maps depending on the category while using ArcGIS to create the shapefiles, merge and
join different tables and delete fields.
According to Dodsworth (2008), Quantum GIS is an open source Geographic Information
System that supports most geospatial vector and raster file types and database formats. The
program offers standard GIS functionality, including a large variety of mapping features, data
editing, on-the-fly projection and GRASS digitizing. Its support for plugins expands its
functionality further by providing additional tools such as GPS data support, georeferencing, and
additional mapping elements.
The qgis2web plugin was downloaded. It generates a web map from the current QGIS project,
employing Leaflet. It replicates as many aspects of the project as it can, including layers, styles
(including categorized and graduated), and extent. The workflow is simple. Select the desired
36. 27
layers and popup settings, select some appearance extras, and then hit the Update preview
button anytime you make an adjustment to the settings otherwise it might look like nothing is
happening. Finally, the Open Street Map (OSM) option was selected to display the map,
superimposed on the world map. OSM is a project to create a free editable map of the world. The
maps are created using data from portable GPS devices, aerial photography, other free sources or
simply from local knowledge. The project was started because most maps have legal or technical
restrictions on their use, restricting people from using them in creative, productive, or
unexpected ways.
Figure 3.5 Layer Properties
Figure 3 shows the selection of the layer properties which determines the output of the layer. The
layers are age, sex, ethnicity, nationality and religion. The Style section is where most of the
adjustments are made. Column enables you to select the column of the attribute table that the
Graduation is going to be done by. Colour Ramp gives various colour schemes to select from.
Under Classes, the Mode that was selected was Quantile. Other modes included Equal Interval.
37. 28
Then the number of classes was selected depending on preference. Precision helps to trim the
values of the classes.
Figure 3.6 Export to Web Map
Figure 5 shows the next stage of the process which is to click on the Export to Web plugin. This
sends the user to a new page which enables manipulation of settings before the map is finally
exported. Layers and groups helps to check and uncheck the layers depending on the number of
layers displayed. Info Popup Content helps to determine which fields of the attribute table will be
shown on the popup. Export Folder shows which folder the web map files are saved in. Minify
GeoJSON (converts to JavaScript). Under Appearance, Add Address Search, Add Layers List,
Highlight on Hover were all checked. Leaflet and OSM were also selected. The map was
previewed by clicking Update Preview, then the map was exported to the web.
3.7 Creating a Web Service
Joomla was used in developing the web service. Joomla in itself is a content management system
(CMS), which enables websites and powerful online applications to be built. It has many
38. 29
advantages including its ease-of-use and extensibility. Most importantly, Joomla is an open
source solution that is freely available to everyone. In a web where content is being shared across
multiple networks, Joomla makes it easy to manage your content from a single location. With
APIs supporting several third party services and a connector enabling requests to anywhere on
the web, users and developers have a magnitude of power and data readily available to them. The
programming language that Joomla uses is PHP. PHP is a server-side scripting language. The
PHP codes are embedded into HTML codes. So basically, the web service was built using
HTML codes with PHP acting as the messenger.
39. 30
4.0 ANALYSIS OF RESULTS
4.1 Introduction
The purpose of this study is to establish a web service for managing national statistical data
which unlike a website provides services to the user. The web service will display population
data and the various statistical interpretations that have been applied to the data that would be of
significance to the lay person. The web service will also help business executives, researchers
and students make analyses with the data available.
4.2 The Geodatabase
A spatially-intelligent database was created using QGIS. The various data obtained from the
census were added to the attribute table of already existing shapefiles and organised into age
structure, sex and ethnicity. The qgis2web plugin was used to export the shapefiles to the world
map using a matching coordinate system. Leaflet and OSM enabled the data contained in the
attribute tables of the shapefiles to be visualised.
Figure 4.1 Map Displayed Online
40. 31
Figure 7 shows the finished map along with the legend against the backdrop of the world map
which was published online. The map is displayed and along with the data. When a region or
district is clicked, a popup appears giving information that was contained in the attribute table of
the shapefile. The same happens for the other regions and districts. This map s then overlaid on a
world map only as long as they are in the same coordinate system. When you click on a region or
district, a popup appears and gives you information depending on the variable (age, sex,
ethnicity) being considered. This is enabled by OSM and Leaflet.
4.3 The Geo-Web Service
After the geodatabase has been created, a system should be developed such that it can be easily
accessed and interpreted by every individual. Thus, a web service was developed using
JavaScript. An interface was created enabling the user to easily interchange between categories.
The web service was designed as simple as possible and the census variables were organised
according to region and district to make interpretation easy. A major function that was added was
the query function. This function enables queries to be made on the database so that any
individual can just type whichever district and/or variable they are looking for, then the web
service will produce a report of the items searched for.
41. 32
Figure 4.2 Web Service Interface
Figure 5 shows the home interface of the web service. There is a regional drop down button at
the top of the page which shows the variables that are available for regions. To demonstrate,
click on the Regional drop down and select Age. This will send the user to the global map which
was created using Leaflet and OSM. This map shows the Age Structure of the regions. The data
for each region can be viewed by just clicking on a particular region, then a popup appears
describing the data. This has been made possible because the Joomla interface has been linked to
the maps created earlier using QGIS. The district drop down button also has its variables and the
principles apply to it just as the regions drop down. There is also a button for posting new data
about other locations in Ghana and around the world to be displayed spatially. At the bottom of
the screen, there is a query search engine for a particular keyword, country (for future works),
districts and regions on the map. These are used to avoid the stress of searching through every
district to find a particular district on the map. This query engine is also used to skip a few steps
in locating, for instance, the age structure in a district in the Eastern Region of Ghana. All that
one has to do is to make an input in each of the fields in the query engine, then the location is
displayed on the map.
42. 33
Figure 4.3 Contact Us form
Figure 6 shows a form a user has to fill if they have enquiries about the functionality of the web
service and also when the user is facing any difficulties when using the services. The fields are
email, subject and description of the problem. This is an avenue for the developer to improve on
the quality of service.
43. 34
5.0 SUMMARY, CONCLUSIONS AND RECOMMENDATIONS
5.1 Introduction
This is the final chapter of the study comprising the under listed: Summary of the study,
Summary of findings, Conclusion and Recommendations.
5.2 Summary of the Results
Every year new total population figures and growth rates are published for Ghana by the Ghana
Statistical Service and Ghana National Population Council. These figures are taken in trust. But
are the numbers accessible enough or are the sources for the population figures accurate and up
to date? And can the figures be easily be updated when changes are made? The important issue
to remember with this figure is that they are estimates, for “it is impossible to have a true
population figure due to the fact that every second the population number changes, which is
mostly arise in numbers. The purpose of this quantitative research case study of Ghana is to
establish a web service for managing national statistical data, which unlike a website, provides
services to the user. The web service will display population data and the various statistical
interpretations that have been applied to the data that would be of significance to the lay person.
The web service will also help business executives, researchers and students make analyses with
the data available. Population Censuses have played a key part in the evolution of modern
socioeconomic techniques. The data collected has been used as evidence in much policy making
and socio-economic research. Nevertheless, it is unlikely that the entire potential of population
censuses has ever been made. With the increasingly potent data processing power available to
users of statistics it is becoming critical to ensure as comprehensive exploitation of census data
as potential. Detailed small area statistics are imposing themselves as irreplaceable in pointing to
the segments of everyday life that necessitate to be amended in terms of enduring conditions,
access to services, adequate infrastructure and fulfilment of essential human rights, such as the
right to be registered or the right to vote, for instance. The role of the population census is to
collect, process and disseminate in depth statistics on population, its composition, characteristics,
spatial distribution and organization. Censuses are conducted periodically in most countries; they
have been conducted since the International Statistical Congress recommended that all countries
44. 35
in the world conduct them. Demographic analysis offers an approach for assessing the character
of a census and countries are encouraged to utilize it as part of their overall census evaluation
approach. A full diversity of demographic techniques that have been developed and used, range
from visual inspection of census information to comparative analysis of two census age
distributions. It is therefore expedient to move away from static map data facility to a more
dynamic, distributed and collaborative environment in this age of modern technology. Geo Web
Services can bring together a wide range of data from various sources, along with geospatial
services that can interact in a loosely coupled environment and be used to create more suitable
information for different stakeholders.
The aim was to design a web service that enhances accessibility to national statistical data and
can be used to perform spatially intelligent exploratory analyses. This was to be accomplished by
creating a geodatabase from the collected data and designing a web service to allow exploratory
analyses of the demographic data. This work did not require direct collection of field data, so
data was collected from the GSS and from other sources on the internet. Some of the shapefiles
were also acquired from the Internet. Therefore the data was collected from secondary or indirect
sources. The collected data was passed through some analysis to be able to segregate the relevant
information from the irrelevant ones. At this stage, it was determined what variables could be
used that would not conflict with the properties of the shapefiles going to be used. Then
shapefiles were created from the analysed data and organized into a geodatabase. Finally, a web
service was developed. The unique thing about this web service is its ability to make queries.
This web service has been designed in such a way that when you query a particular location or
variable, a report is generated of the variables that you made a search for.
5.3 Limitations
1. A system was not provided to enable spatial update on the web service whenever a new
district is created or collapsed or there is a change in name of the district.
2. Some variables were not available for districts like they were for the regions. This made
the two datasets unequal and incomparable.
3. The only accessible data that was made available on the GSS website was the 2010
Population and Housing Census (PHC).
45. 36
5.4 Recommendations
1. Population census data should be available down to the town level.
2. In this research, some inconsistencies were discovered. For instance, during this work,
the main variables that were used were age, total population, religious affiliation,
ethnicity and nationality. For the regions, there was sufficient data available for all the
variables but not so for the districts. Not all the variables were used for the districts
because either was incomplete or was not there at all. The data must be consistent for all
variables at both regional and district level.
3. More sophisticated and efficient software, which may have increased functionality and
may be more efficient with exploratory analyses, can be used for upgrades on the web
service.
4. A system should be created for notification on the creation of new districts. A code could
be written to enable spatial update on the web service whenever a new district is created
or collapsed or there is a change in name of the district.
46. 37
6.0 REFERENCES
Acolor, G., & Kariuki, M. (2000). Delivery of water supply to low-income urban communities
through the Teshie tankers owners association: A case study of public-private initiatives in
Ghana, Conference on Infrastructure for Development: Private Solutions and the Poor.
London, UK.
Baffour, B., King, T., & Valente, P. (2013). The modern census: evolution, examples and
evaluation. International Statistical Review, 81(3), 407–425.
Baldridge, J. (2012). What is a Geodatabase? Retrieved May 4, 2016, from
www.wikis.evergreen.edu
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7.0 APPENDIX
Table 7.1 Distribution of Sex Structure at the Regional Level
NAME CAPITAL
Total
Population
Male
Population Female Population
Ashanti Kumasi 4,780,380 2,316,052 2,464,328
Brong Ahafo Sunyani 2,310,983 1,145,271 1,165,712
Central Cape Coast 2,201,863 1,050,112 1,151,751
Eastern Koforidua 2,633,154 1,290,539 1,342,615
Greater
Accra Accra 4,010,054 1,938,225 2,071,829
Upper West Wa 702,110 341,182 360,928
Upper East Bolgatanga 1,046,545 506,405 540,140
Northern Tamale 2,479,461 1,229,887 1,249,574
Volta Ho 2,118,252 1,019,398 1,098,854
Western Sekondi 2,376,021 1,187,774 1,188,247
50. 41
Table 7.2 Distribution of Age Structure at the Regional Level
Regions
Total
Population Male Female
0-14
years
15-64
years
65+
years
Ashanti 4,780,380 2,316,052 2,464,328 1,803,918 2,772,001 204,461
Brong Ahafo 2,310,983 1,145,271 1,165,712 932,691 1,274,474 103,818
Central 2,201,863 1,050,112 1,151,751 871,834 1,213,660 116,369
Eastern 2,633,154 1,290,539 1,342,615 1,011,054 1,471,312 150,788
Greater
Accra 4,010,054 1,938,225 2,071,829 1,253,632 2,614,312 142,110
Upper West 702,110 341,182 360,928 292,698 367,065 42,347
Upper East 1,046,545 506,405 540,140 434,619 540,345 71,581
Northern 2,479,461 1,229,887 1,249,574 1,110,613 1,260,064 108,784
Volta 2,118,252 1,019,398 1,098,854 812,825 1,168,070 137,357
Western 2,376,021 1,187,774 1,188,247 926,514 1,359,590 89,917
Table 7.3 Distribution of Nationality at the Regional Level
Region Population Ghanaian
Nationality
by Birth
Ghanaian
Nationalityby
Naturalisation
Non-
Ghanaian
Ashanti 4,780,380 97.2 0.7 2.1
Brong
Ahafo
2,310,983 96.6 0.8 2.6
Central 2,201,863 97 0.6 2.4
Eastern 2,633,154 97.6 0.7 1.7
Greater
Accra
4,010,054 96 1 3
Upper
West
702,110 96.2 0.9 2.9
Upper
East
1,046,545 95.9 1.1 2.9
Northern 2,479,461 96.4 0.9 2.8
Volta 2,118,252 94.8 2.7 2.4
Western 2,376,021 97.4 0.6 2
51. 42
Table 7.4 Distribution of Religion at the Regional Level
Regions
No
Religion Catholic Protestant Pentecostal/Charismatic
Other
Christian Islam Traditionalist Other
Ashanti 5.4 12.7 19.7 30.1 15.3 15.2 0.7 0.8
Brong Ahafo 7.3 20.1 17.7 24.5 9.9 17 2.7 0.7
Central 6.6 11.1 21 29.8 21.4 8.7 0.6 0.9
Eastern 6.5 7.9 24.8 36.3 15.5 6.7 1.4 0.9
Greater
Accra 3.4 7.5 22.3 44.6 8.9 11.9 0.5 1
Upper West 3.5 35.7 3 4.3 1.3 38.1 13.9 0.3
Upper East 2.8 19.9 7.1 11.8 2.9 27.1 27.9 0.6
Northern 2.7 7.6 5 6.3 2.1 60 16 0.4
Volta 6.6 17.6 21.5 26.6 7.1 5.7 14.1 0.8
Western 6.7 16.2 21.1 29.5 15.2 9.4 0.8 1
Table 7.5 Distribution of Ethnicity at the Regional Level
Regions Akan
Ga-
Dangme Ewe Guan Gurma
Mole-
Dagbani Grusi Mande Others
Ashanti 74.2 1.2 3.8 1.5 2.8 11.3 2 2 1.1
Brong
Ahafo 58.9 1.3 3.7 4.1 6.9 18.2 3.9 1.8 1.3
Central 81.7 2.5 6.2 5.3 0.9 1.7 0.5 0.4 0.8
Eastern 51.1 17.9 18.9 5.3 1.6 3.2 0.8 0.3 0.8
Greater
Accra 39.7 27.4 20.1 1.9 1.6 5.2 1.3 0.7 2
Upper
West 1.4 0.1 0.4 0.8 1.2 73 20.6 0.3 2.1
Upper East 2.3 0.1 0.3 0.3 4.7 74.7 8.6 5.6 3.4
Northern 3.1 0.3 1.7 8.6 27.3 52.7 3.7 0.5 2.1
Volta 2.8 1.5 73.8 8.1 11.3 0.5 0.1 0.1 1.8
Western 78.2 3.1 6.2 0.8 0.9 8.6 0.8 0.8 0.6
