| Context is an important driver in decision-making processes and problem-solving. It provides opportunities and constraints that must be considered when decisions are made. However, context is also difficult to define due to limits to knowledge and understanding of previous, current and future conditions. Context is dynamic, emergent, subjective and specific to individuals or groups at a particular place and time. However, context is often relegated to static representations of environmental properties with little consideration for the relationships between an actor (or actors), their task and the environments in which they are situated. This research introduces a new perspective for context in spatial decision-making in Geographical Information Science (GIScience). In addition, this research contributes to GIScience by 1) introducing a theoretical definition of context, 2) the development of methods to bound context into relevant and non-relevent categories, 3) introducing graph-based context models to capture and store relevant context, and 4) demonstrating how context models can be used in spatial decision-support systems. |
