Goodchild wrote his 1992 article Geographical Information Science at a time when GIS was still relatively new and undeveloped as an academic field. Despite this he manages to pinpoint several problems in GIScience which have remained unsolved or unaddressed over the decades. Of course, many of the issues that make up the topics of discourse of GIScientists are inherent in spatial data collection and analysis and simply cannot be resolved due to a process Goodchild refers to as discretization. Discretization is the generalization of data such that it can be recorded and reproduced. Considering that most spatial data is approximated and cannot be recorded with 100% accuracy and precision, it is in good practice to always consider factors affecting spatial data uncertainty.
Goodchild mentions issues that can and have been resolved, such as the need for better frameworks for geographical data modelling, better integration of GIS and spatial analysis, a taxonomy of spatial analysis, and easier means of passing data between GIS and spatial analysis modules. I found it amusing that he comments on the obscurity of spatial analysis compared to other forms of GIS, given that spatial analysis is a core part of GIS today. Goodchild also expresses a desire for GIS meetings to become more science-focused rather than based around novelty and innovation, a problem in GIS that still seems prevalent given that many major GIS events are focused on showing off new tools and applications. In that sense he seems to be wrong when he says that GIS will be a short-lived practice if it is primarily used as a software used in applications. The use of GIS has become essential in any pursuit that takes spatial data into consideration, and I believe that this phenomenon has actually benefited GIScience through giving it exposure.
-yee
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