@conference {181,
	title = {ICBO_2018_77: Big Data Visualization},
	booktitle = {International Conference on Biomedical Ontology (ICBO 2018)},
	year = {2008},
	month = {08/06/2018},
	publisher = {International Conference on Biomedical Ontology},
	organization = {International Conference on Biomedical Ontology},
	address = {Corvallis, OR},
	abstract = {<p>Advanced computing and experimental technologies enable scientists to study complex phenomena at unprecedented precision, resulting in an explosive growth of data. The size of the collected information about the Internet and mobile device users is expected to be even greater, a daunting challenge we must address in order to make sense and maximize utilization of all the available information. Visualization transforms large quantities of, often multi-dimensional, data into graphical representations that exploit the high-bandwidth channel of the human visual system, leveraging the brain{\textquoteright}s remarkable ability to detect patterns and draw inferences. Visualization has thus become an indispensable tool in many areas of study involving large, complex data. In this talk, I will discuss designs and strategies for visualizing data generated by large-scale scientific simulations and network data derived from social media and cyber security applications.</p>
},
	keywords = {big data, data visulaization, Network Data, scientific discovery, Visual Analysis, Visualization},
	author = {Kwan-Liu Ma}
}
