@conference {819,
	title = {A Domain Ontology for Task Instructions},
	booktitle = {KGSWC},
	year = {2020},
	abstract = { Knowledge graphs and ontologies represent information in a variety of different applications. One use case, the Intelligence, Surveillance, \& Reconnaissance: Mutli-Attribute Task Battery (ISR-MATB), comes from Cognitive Science, where researchers use interdisciplinary methods to understand the mind and cognition. The ISR-MATB is a set of tasks that a cognitive or human agent perform which test visual, 
 auditory, and memory capabilities. An ontology can represent a cognitive agent{\textquoteright}s background knowledge of the task it was instructed to perform and act as an interchange format between different Cognitive Agent tasks similar to ISR-MATB. We present several modular patterns for representing ISR-MATB task instructions, as well as a unified diagram that links them together.},
	author = {Aaron Eberhart and Cogan Shimizu and Christopher Stevens and Pascal Hitzler and Christopher W. Myers and Benji Maruyam}
}
