Spatial Data Infrastructures in Africa: A Gap Analysis

Abstract

ABSTRACT. The need for spatially explicit thematic data is currently increasing in parallel to the development of observing, storing and processing capabilities. This requires an integrated data management structure in which human and institutional aspects play a key role as part of a Spatial Data Infrastructure (SDI). We focus in this study on the African continent to evaluate the status of its SDI implementation. Because assessing SDI at a continental scale in a traditional way (i.e. following methods developed for national assessments) requires financial resources and mechanisms only affordable to developed countries (e.g. European Union), alternative ways have been explored based on fourteen key SDI indicators that were validated by SDI experts in a previous study. Data was collected for each African country through the African leading SDI institution (UN Economic Commission for Africa) and through Internet searches. We found relatively weak scores of the fourteen SDI indicators for African countries compared to the rest of the World, but with notable differences within Africa. We discuss the implication of the lack of information available on the Internet to assess SDI status in Africa. We conclude that it is necessary to improve statistical information in most African countries. This requires an agreed-on geospatial data structure and organization between concerned institutions that is only achievable through a shared global vision on geospatial data governance. To this end, we suggest a few quick wins and several new mechanisms that would enhance the flow of SDI statistical information and improve data management structure in Africa.

Technology Trends for Spatial Data Infrastructure in Africa

“…As at 2016, many African countries did not have mature and functioning SDIs: critically, they still lacked strong inter-agency coordination requisite for SDI development. Furthermore, Africa was still characterized by slow SDI development [8], which can be corroborated by the low number of NSDI geoportals on the continent.…”

Challenges and Opportunities for Spatial Data Infrastructure Development in Mozambique

“…Recently SDI emerged for social sciences (Schweers et al 2016). However, environmental protection and natural resources management have been presented as one of the main reasons for implementing national and global SDI (Guigoz 2015;Foster and Ryttersgaard 2001). Environmental issues rarely conform with national, or even regional borders and their management often requires the integration of multiple data and sciences to be effective (UNECA 2017).…”

“…In Africa, there is a fast-growing list of countries at an advanced stage of implementation of SDI such as South Africa, Senegal, Rwanda, Nigeria (Ayanlade et al 2008), Cape Verde (República de Cabo Verde 2010), Namibia, Ghana (Sinvula et al 2017), with many others on their way. However, many African countries still have insufficient or inadequate infrastructures to manage and disseminate spatial data (Guigoz 2015) as is the case of Mozambique.…”

“…The lack of updated spatial data has been reported in several studies for Mozambique (Cabral et al 2017;Niquisse et al 2017) To assess the potential contribution of these institutions for the development of the SDI in Mozambique, a questionnaire (Annex 2) was developed focusing on the existing capabilities of the different organizations concerning the main SDI components (Mansourian et al 2006;Guigoz 2015): organization, legal and technical frameworks and accessibility (Table 1). Table 1.…”

Authoritative and Volunteered Geographical Information in a Developing Country: A Comparative Case Study of Road Datasets in Nairobi, Kenya

“…This lack of current data is common in developing countries and is reflective of the data poverty associated with such nations, with African nations being particularly disadvantaged in that regard [73]. Considering spatial data availability in Kenya, in particular, studies have captured the poor state of the Kenyan spatial data infrastructure and spatial data availability overall [74,75]. Therefore, it is not uncommon for the 'most current data' available in countries, such as Kenya, to be slightly outdated.…”