| id |
ijac201412405 |
| authors |
Gómez Zamora, Paula and Matthew Swarts |
| year |
2014 |
| title |
Campus Information-and-knowledge Modeling: Embedding Multidisciplinary Knowledge into a Design Environment for University Campus Planning |
| source |
International Journal of Architectural Computing vol. 12 - no. 4, 439-458 |
| summary |
This article gives an overview of our research approach in collecting specific information and multidisciplinary knowledge with the aim of integrating them into a model for the planning of a university, supported by a design environment. Our goal is to develop a strategy for modeling raw information and expert knowledge for the Georgia Tech Campus. This research was divided into three stages: First, we identified a variety of written sources of information for campus planning, extracting and distinguishing raw information from disciplinary knowledge. Second, we selected the elicitation methods to gather knowledge directly from experts, with the objective of performing qualitative assessments –effectiveness,efficiency,andsatisfaction–ofcertainfeaturesof the Georgia Tech Campus. Third, we interpreted the information and knowledge obtained and structured them into Bloom’s taxonomy of factual, conceptual, procedural and meta-cognitive, to define the specific modeling implementation strategies. Currently, we are implementing a Campus Landscape Information Modeling Tabletop in two phases. First, constructing an information-model based on raster and vector models that represent land types and landscape elements respectively, to perform quantitative assessments of campus possible scenarios. Second, embedding knowledge and qualitative aspects into a knowledge-model. The long-term goal is to include quantitative as well as qualitative aspects into a computational model, to support informed and balanced design decisions for university campus planning.This paper specifically focuses on the construction of the knowledge-model for Georgia Tech Landscape planning, its structure, its content, as well as the elicitation methods used to collect it. |
| series |
journal |
| full text |
 file.pdf (4,992,726 bytes) |
| references |
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