High-quality geographic information is the result of thorough, appropriate analysis of accurate underlying data. This highlights perhaps the most important potential constraint of GI: the availability of data.
Commercial availability of potentially sensitive datasets is only part of the issue. A key strength of the approach is the ability to overlay multiple datasets and understand their interplay, but this depends upon the comparability of those data (in terms of scale, age, type of spatial representation, etc).
It is vital for analysts to respect fundamental rules about combining such data and drawing conclusions from the results; in-depth spatial statistical expertise is critical if we want reliable results.
Where data availability is a problem, there is a risk of omitting data because it is difficult to collect or purchase, even though it might be the most relevant. This is probably more likely to be true of data indicating more qualitative, social variables, and it is important that the analysis takes any such omission into account.
These issues can be addressed to some extent through effective use of GI tools, and Geofutures offers comprehensive experience of obtaining data from both private and public sector sources. It is a key priority when planning any GI-enabled project to consider first how to gather data of sufficient quality.
