SPATIAL DATA INFRASTRUCTURES: IS AFRICA READY?
Chukwudozie Ezigbalike Qhobela Cyprian Selebalo
Department of Civil Engineering Chief Surveyor
University of Botswana Lands, Surveys & Physical Planning
Private Bag 0061 Box 876,
Gaborone, Botswana Maseru 100, Lesotho
Sami Faïz Sam Z. Zhou
Institut National des Sciences Appliquées et Survey Institute of Zimbabwe
de Technologie P.O. Box 6265
INSAT, BP 676 Harare, Zimbabwe
1080 Tunis, Tunisia email@example.com
Presented at the Fourth Spatial Data Infrastructure Conference, Cape Town, South
Africa, March 13-15, 2000.
There is general agreement that spatial data is crucial for environmental protection and sustainable
development, therefore the development of the spatial data infrastructure (SDI) ensures
accessibility of information for decision-making. The basic attributes for an SDI are well defined
and agreed, yet the achievement of this ambitious concept will not be easy, especially in the
developing world. The question is whether African countries are making the necessary provisions
to adapt the concept, thus ensuring that they are not left out in the information age.
Using examples from selected African countries, this paper reviews the state of the components of
SDI in Africa and assesses the countries‟ readiness to adapt the concept. This is done by first
defining the SDI concept and its components, analysing the likely problems related with the
introduction of some SDI components, and the status of the countries in adapting the concept. It
concludes that much of Africa is still not ready for a full on-line spatial data infrastructure and
recommends steps to be taken to ensure full participation when other communications and
physical infrastructures become available.
The Bathurst Declaration defines spatial data as “data/information relating to the land, sea or air
that can be referenced to a position on the earth‟s surface” (Bathurst Declaration 1999). It further
explains that it is “the key to planning, sustainable management and development of our natural
resources at local, national, regional and global levels”. Much of these spatial data have been
collected on an ad hoc basis. However, Phillips et al (1999) point out that much of the data are
transient and cannot always be collected when needed:
Such data could not be collected impromptu, as needed. For such transient data
sets, they are collected and stored for use and re-use, usually by many users. Thus
a data or information resource is created in the form of databases. Such resources
need coordination and cooperation, usually within an organisation or a
government setting. As more organisational units (government and
non-government) become involved, the cooperation becomes more complex and
the particular datasets start acquiring an “infrastructure” status.
The Bathurst Declaration defines spatial data infrastructure (SDI) as a term:
… that describes the fundamental spatial datasets, the standards that enable them
to be integrated, the distribution network to provide access to them, the policies
and administrative principles that ensure compatibility between jurisdictions and
agencies, and the people including user, provider and value adder who are
interested at a certain level of area that starts at a local level and proceeds through
state, national and regional levels to global level.
The whole concept of an infrastructure, SDIs included, is that certain services cannot be provided
to users as and when needed. Rather, these services are best provided as a foundation and fabric of
all other activities of the society or community. Ezigbalike and Nkwae (1999) explain that
infrastructures are taken for granted. Users are not conscious of their “ownership” and expect them
to always be available, even if they have to pay for the right to use them, for example vehicle
registration in the case of the highway infrastructure. The general user essentially does not care
how they work or who makes them work, as long as they work. Spatial data infrastructures are just
like other forms of better-known physical and tangible infrastructures, such as roads, power lines
and railways. It is made up of several components.
This paper reviews the components of SDI and evaluates the status of these components in Africa
in an attempt to answer the question posed in its title: Is Africa Ready? The 1998 edition of the
Oxford Advanced Learners‟ Dictionary defines being ready as “(of a person) fully prepared for
something or to do something …” A thing is ready if it is “completed and available for use.” Is
Africa fully prepared for SDI? Or put differently, is the SDI completed and ready for use in Africa?
The answer is either “yes” or “no”, depending on how lenient or strict one is with the evaluation of
the available components and the definition of preparedness. The paper concludes with
recommendations on steps towards preparing for SDI in Africa.
The paper does not present an exhaustive, country by country review of the components; rather
general observations are presented. It should also be noted that several coordinated data
harmonisation projects and programs, especially at (sub) regional levels, have not been considered
in our evaluation because the SDI concept is much more than data sharing. It is about providing
data as an infrastructure, a foundation or fabric of the society on which other activities are based. It
implies that spatial data should be provided in a standard and transparent manner so that the
community at large, not just a specialist segment, can simply use them.
COMPONENTS OF SDI
It is obvious that spatial data are necessary for the SDI. However, the Mapping Sciences
Committee (1993, 17) stresses that:
… they are not sufficient. Of equal importance are the individuals, institutions,
and technological and value systems that make it a functional entity, one that
serves as a basis for much of the business of a nation.
They list the various components as:
Data, databases and metadata: sets of organized spatial data and information about those
sets (e.g., directories), such as where it is located, how it was collected and is maintained, by
whom, how it can be accessed, and what the characteristics are (e.g., coverage);
Data networks: the communication highways in various forms (e.g., telephone lines, local
area networks, and broadband integrated service networks or BISDNs) linking databases,
sources and users;
Technology: the data conduits, and other equipment and procedure for optimising the
management of the databases at the source and maximizing the potential application of the
data by the user;
Institutional arrangements: the co-ordination of the many organizations involved in the
SDI development and maintenance;
Policies and standards: the data communication rules, common conventions, and
protocols, in addition to the broader and very critical policies addressing social and
economic issues such as privacy and pricing;
Users: the individuals and organizations that access and use the infrastructure to acquire
data to meet their requirements and add value by developing new information services and
STATUS OF SDI COMPONENTS IN AFRICA
While there are several initiatives in Africa that can be regarded as rudiments of a holistic SDI,
many of these initiatives have not really been conceptualised as SDIs as described above. Different
countries have focussed on different fragments of SDI. Therefore the level of development or
introduction of these components varies from country to country.
This is the aspect in which the most advance has been made, because we did not have to start from
scratch. Spatial data have always been available in various forms in all countries, especially in map
form. The biggest source of spatial data is the national mapping agencies, e.g., the Department of
the Surveyor-General in Zimbabwe and the Department of Surveying and Mapping (DSM) in
Botswana, Directorate of Surveying and Mapping in Namibia, Federal Surveys Department in
Nigeria and Surveys and Physical Planning in Lesotho.
Many municipal authorities have also gathered spatial data, mainly cadastral records. Some have
also been involved in mapping, for example in Zimbabwe. In Zimbabwe, other thematic data sets
are available from agencies like the Forestry Commission, Natural Resources Board, Department
of National Parks and Wild Life Management, the Department of Agricultural and Extension
Services (AGRITEX), the Environment and Remote Sensing Institute (ERSI), the Central
Statistics Office (which provides socio-economic data), and the Research Council of Zimbabwe.
Similar organisations also maintain thematic data in other countries. In Botswana, the Department
of Lands maintains records of all allocated plots in urban centres and the land boards maintain
textual inventories of allocation in non-urban jurisdictions.
Many of these data sets are maintained to support administrative responsibilities of the
organisations. The base maps for these data sets are usually sourced from the national mapping
agencies. These agencies have statutory mandates to oversee mapping in the countries and provide
topographic, cadastral and other thematic map products in the respective countries.
Databases and Metadata
Much of the available data are in the forms of maps and paper records. However, there has been a
realisation that the use of computers in spatial data management necessitates availability of such
data in digital format. Efforts are therefore underway to create digital databases through
conversion of existing maps into digital format and new production of digital information
products. In Tunisia, projects are on going to implement geographical databases (GDB),
especially in national organisations such as Agriculture and Environment. These specific GDB are
very important and serve real preoccupations of users. Also as part of the National Director
Diagram (see below under Institutional Arrangements), a Geographical Repository and Spatial
Data Warehouse are planned. This will provide the framework for a Federated Research Project,
called SIG-ATM (global information system relative to the air, the earth and the sea). The
principal objective of this project is to offer the participants access to data, information and
knowledge in the most appropriate manner (Geographical Repository), to analyse, to understand,
to make complex decisions of global nature. This project will coalesce the various existent systems
into a meta-system of information (a Spatial Data Warehouse), that will have to be constantly
maintained, relevant and of high quality (Federated Research Project 2000).
In Botswana, DSM has an on-going project to produce digital cadastral and topographic databases.
The Department of Town and Regional Planning (DTRP) have digital databases to support, among
other functions, land use compliance monitoring in Gaborone. Computerised land inventory
projects have been going on since 1992, and the Department of Lands maintains a comprehensive
database of allocated plots in urban areas (Ezigbalike and Nkwae 1999; Manisa and Maphale
1999). In Lesotho, the Mapping Agency has recently introduced production of large-scale
(1:2,500) digital mapping for urban areas, and there is also a project to digitise the 1:50,000 map
There is however lack of capacity to effectively utilise the vast amounts of data generated in these
processes. The main problem is the lack of coordination in the efforts, discussed below. Data sets
produced by different departments are not always compatible, even though they relate to the same
territory. This lack of coordination causes duplication of data as well as in the distribution, and
limits strongly their exchange, consequently producing huge costs to the public (Ministère de
l'Environnement et de l'Aménagement du Territoire 1999).
Metadata systems are still in rudimentary stages, making it difficult for potential users to know
what data sets really exist and if they could satisfy their needs.
Data Networks and Technology
The most effective data conduits of our time are computer networks and the Internet. These
unfortunately are not yet well developed within the African continent. The information
infrastructure also depends on other utility infrastructures, such as electricity and
telecommunications. In many countries, electricity is only available in the urban centres, leaving
large portions of the country without service. These rural areas are also the subjects of the data in
the proposed spatial data infrastructure. In fact, much of the environmental and natural resources
data would be about these rural areas. Access to the infrastructure should therefore eventually be
provided from these centres.
In some countries, even when electricity is available, the supply is not constant and the frequent
power outages and associated surges result in damages to sensitive computer and other equipment.
The cost of computerisation therefore usually includes costs of ancillary equipment for stabilising
and standby generators, costs that are not incurred in developed countries.
Telecommunications infrastructure is also poorly developed. In many countries majority of the
citizens still do not have access to telephones, and the waiting lists for phone services are long.
Telecommunications agencies, which are still mainly government monopolies, are still struggling
to provide voice lines to more people. The provision of data-enabled high bandwidth lines is
therefore not yet a priority. Spatial data sets are usually large in volume, especially if they include
images and graphics.
General computer literacy is still low, and the value of electronic mail communication and the
World Wide Web is only beginning to be appreciated. Other relevant aspects of the Internet, like
File Transfer Protocols and remote computing, are still regarded with awe.
However there is hope for some countries in this regard, in the form of the Leland Initiative
(USAID Bureau for Africa). This is a United States Government effort to extend full Internet
connectivity to approximately twenty African countries in order to promote sustainable
development. This Africa Global Information Infrastructure (GII) project has three strategic
Create an enabling policy environment by promoting policy reform to reduce barriers to
open connectivity. This is expected to result in affordable prices conducive to broad
expansion of the user base, delivery of Internet services by private sector providers and free
and open access to information.
Create a sustainable supply of Internet services by identifying appropriate hardware and
assisting with Internet connectivity. The expected results include indigenous ISPs trained to
offer full internet service and better communication between counterparts in Africa and the
world; country-wide access with special attention to extension to (rural) issues; and Internet
Society chapters serving as advocacy and support organizations.
Enhance Internet use for sustainable development by increasing he ability of African
societies to use the communication and information tools of the Internet. This is expected to
result in local and international partnerships sharing information related to sustainable
development in all sectors; indigenous partnerships to create and maintain new information
resources based in African experience which feed the GII; increased African capacity to use
information in decision-making and in managing scarce resources; broadened user base for
information systems and telematics services; and indigenous training capacity for users and
The project is currently limited to the following countries: Benin, Botswana, Cote d‟Ivoire,
Eritrea, Ethiopia, Ghana, Guinea-Bissau, Guinea-Conakry, Kenya, Madagascar, Malawi, Mali,
Mozambique, Namibia, Rwanda, Senegal, South Africa, Tanzania, Uganda, Zambia, Zimbabwe.
Lesotho is currently in the process of developing the Memorandum of Understating (MOU) in
order to take part in the project.
Most African governments recognise the need to manage their land as a resource or to optimise
land use. They also recognise the importance of having relevant spatial data in order to achieve this
objective. However, government departments are the major sources of spatial data. There are two
main reasons for this. First is the undeveloped nature of the geo-information industry in particular
and the information economy in general. Second are laws and administrative regulations that give
exclusive mandates to government departments, even when they lack the capacity to satisfy the
needs of the expanding user community. Government departments are not usually very responsive
to the needs of the private users. The onus is on the user to adapt to the available data, rather than
on the data producers to develop new products in response to the needs of the users.
Even within the government, data management is still a fragmented process with little
co-operation between different agencies. The flow of information between government ministries
and departments is poor. This is mainly because many countries are still living in the „mapping
era‟ with emphasis on map management. With this emphasis, the national mapping agency would
chair a „cartographic committee‟ or other such body of map users.
In the digital age, emphasis has shifted from the map to information. The map is only a graphical
presentation of the information, and mapping is only an information collection exercise. The focus
should now shift to information management. Information management requires a dedicated
function charged primarily with managing the corporate information resource for the good of all.
This management mandate should not be given to one of the major producers or consumers of the
information resource. When this is done, the system over time would evolve to the cater more for
the needs of this agency or person. The recommended practice is for the dedicated management
function to be independent of the users, and also be high enough in the organisational structure to
participate in policymaking and be able to enforce rules and standards. This information
management paradigm can be compared with financial management arrangements. The major
creators of wealth in many countries are departments responsible for mineral resources, tourism
and agriculture. The major spending departments are defence, education, health and welfare. Yet
none of these creators and spenders is given the mandate to manage the funds of the country.
Usually a very independent and very powerful Department of Finance is the funds manager.
However there seems to be tentative steps towards establishing appropriate spatial data
management organs in African countries, and developing relevant indicators. In Tunisia the
adopted steps consists of the elaboration of a National Director Diagram in Geomatics. This
Diagram will identify general orientations that will be concretised by a set of plans, and geomatics
programs and actions in the short to medium term. This is part of the process of implementing an
information infrastructure in Tunisia, with the objective of making the geomatics industry an
important economic basis and registering it as an activity, which participates in the durable
development of the country (Ministère de l'Environnement et de l'Aménagement du Territoire
Another example of efforts to establish some sort of dedicated information coordination is in
Lesotho where an inter-sectoral body, the Committee on Environmental Data Management
(CEDAMA), has been established. The terms of reference of CEDAMA include:
To promote a culture of environmental data exchange,
To advise National Environmental Secretariat (NES) on issues of environmental database
To establish data quality standards,
To advise NES on the formulation of relevant policies on management data,
To advise NES on measurable environmental quality indicators for different sectors of the
To assist with the analysis of trends in the environmental quality indicators, and recommend
Policies and Standards
The availability and accessibility of data through the relevant SDI components is not necessarily
the end. There should be policies and standards with enforceable legal status for addressing
technical, social and economic issues as follows:
Policies should be developed for technical issues including data formats and standards,
communication rules, protocols and conventions for combining diverse information
Social values should be respected and the policy should ensure privacy of information
relating to individuals and protection from commercial misuse.
Economic issues include availability of copyright protection, value additions on data, use
rights custodianship versus ownership, transparent pricing and distribution mechanisms,
confidentiality of commercially sensitive information, and liability on errors.
This is the most crucial component which requires participation of all stake holders and the strong
political support for enforcement. The required policies are not so much on collection but mostly
on dissemination, standards for data quality and rules for sharing and exchange. The reality in
African countries is that these issues have not yet been addressed formally. Where they have been
addressed, they are not usually adhered to. The value of information has not yet been realised, and
it will not be if policies and standards are not in place. National efforts to date have been
undertaken by the national mapping agencies, sometimes with assistance from the donor
community and regional agencies.
At SADC regional level, SADC-ELMS has produced a background report for the development of
a SADC Environment Information Systems data policy, within a broad regional policy and
strategy for Environmental and sustainable development. A data Policy in the context of SADC is
an agreement between parties to collaborate on issues relating to data with a view of developing
SADC Environmental Information System (EIS).
The SDI will be of no value if there are no users. This is therefore an important component of the
SDI. The user component is not limited to natural persons. Users include organisations. Also
included in the user component are individuals, groups and organisations that produced the data
sets in the system and maintain various aspects of it. There are also the group of users who add
value to the original data sets to produce new data and information products, which then become
part of the data and information infrastructure.
It is not enough to have individuals and organisations classified as users. They should possess
appropriate knowledge and skills to perform their roles in the infrastructure effectively, be it
providing data, transforming data, managing data or exploiting the resource.
Africa is not short of individuals and organisations with assigned or assumed roles as described
above. However, the skill base is still very low. Computer permeation is still low in organisations
and homes, and so is computer literacy. The result is that operations that should be computerised
are still being performed manually. These include operations on/with spatial data. The ability to
participate fully in the operations of the infrastructure, and realise the full potential of the data
resources is therefore limited.
Associated with this is the state of our educational institutions. Some institutions have not been
able to keep up to date with advances in concepts and technology in this area. They are therefore
unable to perform their role in the operation of the SDI, which is to produce the skill and
knowledge base for the relevant activities. This is due mainly to scarce financial resources, and the
fact that benefits from investments in spatial data projects are long term rather than immediate.
Politicians and administrators would rather commit the scarce resources to projects that will yield
results in time to affect their electoral fortunes and performance appraisal targets.
So, Are We Ready for SDI?
The answer to the central question of this paper depends on the semantic emphasis of the
evaluation. Table 1 summarises the state of readiness for the various components, based on two
versions of the question. If the emphasis were placed on our state of willingness, the answer would
be a qualified “yes”. We are willing to make some of the required changes, but reluctant to give up
other „tried and tested‟ ways of doing things. On the other hand, if the emphasis is on components
of the SDI itself being complete and available to use, then the overall assessment will be “no”. The
overall state of Africa‟s readiness for SDI is therefore a reluctant “no”.
Table 1: Evaluation of Africa’s readiness for SDI
Component Readiness Question 1: Is Readiness Question 2: Is Africa
the component complete fully prepared to develop the
and available for use? component?
Data No. Yes.
Databases and No. Not fully, the concept is still not
metadata. fully understood and appreciated.
Data networks and Still rudimentary. Willing but not able.
Institutional Fragmented arrangements. Reluctant to change existing
Policies and No. Declared intentions but little
This paper has evaluated Africa‟s readiness for spatial data infrastructures and found that we are
still not fully prepared for its introduction. The three main reasons for our poor state of
the overall poor state of information and communication technologies,
lack of full appreciation of the advantages of SDI, and
reluctance of the key actors to move from the „mapping era‟ to the „geo-information era‟.
SDI cannot be introduced in a vacuum. It depends on other technologies to work, notably
information, communications and knowledge (ICK) technologies. These technologies are still at
rudimentary stages in much of Africa and the spatial data management community do not have
direct control over them.
While our policy makers know about maps, the concept of spatial data that is different from, and
subsumes maps, is not yet understood. In the mapping era, there were cartographic committees or
similar bodies of map users who set priorities and oversee mapping in the country. While mapping
provides the base data for the spatial data infrastructure, there are other core data sets in an
infrastructure environment and we have to restructure the information management arrangements
to include them.
The shortcomings in our preparedness can be regrouped into external factors outside our control
and internal inadequacies, completely within our control. Our preparations for SDI should
therefore emphasise this internal component. This will ensure that when the external components
are in place, we can start implementing the SDI proper. Concrete and immediate actions in this
regard should include the following:
We, members of the spatial data management community, especially the surveying and
mapping community, should inform ourselves on the concepts of SDI. We shall find that
some of our operations are already in line with SDI, even though it has not been described in
While we do not necessarily have to change our terminology to use SDI terms, we should
ensure that all spatial data collection projects (including surveying and mapping) are
henceforth planned for an SDI environment. However, since we do not yet have the SDI in
place, we should then translate the plans into „transitional‟ arrangements.
We should spearhead the restructure of cartographic committees or mapping councils. The
surveying and mapping community usually chair these committees and councils. It may be
necessary to restructure their compositions, and it may be strategic to voluntarily relinquish
the chair if the need arises.
It is our duty to educate our colleagues to new developments in the spatial data management
industry. A guest speaker could be invited to make a presentation to the meetings of these
committees. The academic community can assist in this aspect.
Similar to the above point, heads of national mapping agencies (NMA) are usually highly
regarded in government and would normally be members of high-level consultative
councils or similar advisory bodies of the government. The next request for mapping
products at such forums should be gently corrected to spatial information, presented as
maps at some times. Also, special briefings of such bodies should be arranged through the
Metadata and information flow projects should be initiated. We do not need full networks to
start documenting descriptive data about our data sets. Manual metadata forms can be
designed to collect the information where there are no computers. The metadata projects
should include entries about producers and known users of the data sets, thereby creating a
data flow document.
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