National Spatial Data Infrastructure Building Blocks: The Status Quo in Ethiopia

Abstract

In Ethiopia, geospatial data silos are common due to the absence of a proactive and collaborative geospatial sharing platform. A national sharing platform, Ethiopian National Spatial Data Infrastructure (ENSDI), is in its pre-implementation phase. It is now of crucial concern to identify and prioritize areas of investment. However, we lack information on what is already available and where, and what is still required to deliver ENSDI building blocks. The purpose of this work is to assess status quo of these building blocks. 110 organizations were addressed based on a sampling procedure that is free of personal bias. Data was collected through semi-structured interviews, on-site inspections, and a review of secondary sources. The analysis revealed that many national geospatial information and other enabling policies, laws and strategies are already available. Although they do incorporate the value of sharing and accessing information, it appears that they lack details regarding interoperability, inclusiveness, and implementation. This work reveals complex institutional challenges that require better definitions of roles and responsibilities in order to overcome existing overlaps of mandates; and improved coordination of efforts with the geospatial industry. Furthermore, most legacy data sets are available in digital form, but they are neither ready to be shared on the Web nor accessible for the wider Geographic Information Systems (GIS) community. This is largely due to the absence of standardization, negligence of metadata, extended use of proprietary software, absence of clear data models and definitions, and poor (file based) data organization. The absence of Internet connectivity or low band width remains a fundamental obstacle for any web-based sharing of geospatial data. We also identify a lack of expertise in spatial data management, processing and programming. GIS and Remote Sensing specialist remain hard to find. Last but not least, this study recommends further study on data quality and data management issues.