Principles of Scientific Knowledge Engineering – YouTube

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Principles of Scientific Knowledge Engineering

Gully Burns, Research Lead at USC Information Sciences Institute, presents a webinar titled, “Principles of Scientific Knowledge Engineering.”

Video Description
Developing any sort of scientific informatics system requires a model of how the data is structured: a schema. In this talk, Gully will talk about go beyond simple methods of database design to discuss how you should think about scientific knowledge is engineered. Knowledge is crafted based on evidence. It is reported as natural language and images in scientific papers. It is constrained by domain specific theories and ontologies. In this talk, Gully will provide a walkthrough of these important elements and synthesize it into a coherent theory that you should be able to apply to your work in any subfield of biology.

About the Speaker
Gully studied physics as an undergraduate at Imperial College in London, when, half-way through a early-morning Friday lecture on detectors for sub-atomic particles, he had an epiphany that he wanted to study how the brain works. He started a D.Phil. at Oxford, only to find that the theoretical foundations of neuroscience were not the stringent, mathematically-defined coda that was the norm in physics. Subsequently, he began work on building knowledge engineering systems for biological systems, specifically targeting neuroanatomical questions. After completing his D.Phil. in 1997, he came to USC to work in the neuroanatomy laboratory of Professor Larry Swanson, building software solutions such as the NeuroScholar project and NeuARt II neuroanatomical viewer. In 2006, he moved to the Information Sciences Institute in Marina Del Rey to develop systems for Biomedical Knowledge Engineering: finding novel ways of applying cutting-edge AI technology from Computer Science to biomedical data. Gully’s main goal in his career is really to transform the way we work with scientific knowledge so that scientific discovery becomes commonplace, powerful and easy.

View slides from this lecture: https://drive.google.com/open?id=1vLK2RKYDm_fQxbONoFfgUTjqzUAO8KUX

Visit our webpage to view archived videos covering various topics in data science:
https://bigdatau.ini.usc.edu/data-science-seminars

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