Scenarios are narratives that illustrate future possibilities or existing systems, and
help policy makers and system designers choose among alternative courses of action. Scenario-based decision-making crosses many domains and multiple perspectives. Domain-specic
techniques for encoding, simulating, and manipulating scenarios exist, however there is no
general-purpose scenario representation capable of supporting the wide spectrum of formality
from executable simulation programs to
free-form text to streaming media descriptions.
The claim of this research is that there is a computer readable scenario framework that can
capture the semantics of a problem domain and
make scenarios an active part of decision
making. The challenge is to define a representation for scenarios that supports a
wide range of discussion and comprehension activities while remaining independent of content and access mechanisms. This dissertation describes a scenario ontology derived by examining alternate
forms of narrative: thought experiments, mental models, case-based reasoning, use cases,
design patterns, screenwriting, film-editing, intelligent agents, and other narrative domains.
The scenario conceptual model was based on an analysis of forms of narrative and the activities of storytelling. This method separates what a narrative is from how it is used. The research contribution is the development of the hyperscenario framework. A hyperscenario
is a scenario representation containing link structures for navigation between scenario elements. The hyperscenario framework consists of the scenario ontology, scenario grammar,
and a scenario specification called Scenario Markup Language (SCML). The results of the
web-enabled simulation experiment validate the improvement on decision-making due to the
hyperscenario framework.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/7251 |
| Date | 20 July 2005 |
| Creators | Hobbs, Reginald L. (Reginald Lionel) |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Language | en_US |
| Detected Language | English |
| Type | Dissertation |
| Format | 3184338 bytes, application/pdf |
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