SDI Reality in Uganda: Coordinating between Redundancy and Efciency
Walter T. de Vries and Kate T. Lance · 2011
Activities ......................................................................................... 110 5.5 Analysis-Based on Axial Coding Categories ...................................... 110 5.5.1 Redundancy and Efciency ......................................................... 110 5.5.1.1 Causal Conditions ........................................................... 110 5.5.1.2 Context .............................................................................. 111 5.5.1.3 Action Strategies ............................................................. 111 5.5.1.4 Consequences .................................................................. 112 5.5.2 Power and Uncertainty ................................................................. 112 5.5.2.1 Causal Conditions ........................................................... 112 5.5.2.2 Context .............................................................................. 113 5.5.2.3 Action Strategies ............................................................. 113 5.5.2.4 Consequences .................................................................. 113 5.6 Interpretation-Linking Power and Uncertainty Factors to Redundancy and Efciency ................................................................. 114 5.6.1 Power as a Cause for Redundancy or Efciency ....................... 115 5.6.2 Uncertainty as a Cause for Redundancy or Efciency ............. 116 5.7 Conclusions ................................................................................................. 116 References ............................................................................................................. 117 Coordination of spatial data infrastructures (SDIs) is a balancing act between technological efciency objectives and public sector inefciency realities. SDI technological advocates typically promote that SDI coordination should aim for national, seamless, standardized, and nonredundant data sets. This would increase operational efciencies when organizations need to share spatial data and would avoid the additional work and transaction costs of data duplication (Rasmussen 1993; Buogo and Chevallier 1995; Fonseca et al. 2000; Astle et al. 2006; Baker and Chandler 2008). Yet existing public sector contexts can have inherent drivers toward maintaining inefciency and redundancy. These include the need to construct backup mechanisms in case of organizational uncertainties such as the lack of public sector resources, and the need to be ¯exible in case of political uncertainties, such as government failure and political transitions (Landau 1969; Miranda and Lerner 1995; Ting 2003).