Applied Ontology 2018

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PHI 598

An ontology is a structured collection of terms and definitions that is developed with the goal of making data deriving from heterogeneous sources more easily searchable, comparable or combinable. The course will provide an introduction to ontology from an application oriented point of view, including examples in the areas of data science and artificial intelligence. Examples will be drawn from biology and medicine, social science, law, and finance. The course will be of interest not only to philosophers but also to those interested in biomedical informatics and in the computer and information sciences.

Venue: 200G Baldy, UB North Campus

Faculty: Barry Smith and Werner Ceusters

Background reading:

August 27: Introduction to Ontology

What is an ontology?
Key elements of an ontology
What are ontologies useful for?

Class assignment: write a 2-page essay documenting which of the key elements identified in the lecture are considered (or not considered) in: Hoehndorf, Schofield and Gkoutos, 2015. Deadline: noon, September 6.

Advance reading (prior to September 10 lecture): 1. Scheuermann, Ceusters and Smith, 2009. 2. Haendel et. al., 2018

September 3: Labor Day – No class

==September 10: Ontology of Disease

Class assignment: write a 2-page essay discussing the extent on which the framework offered by Scheuermann, Ceusters and Smith, 2009 can (or can not) solve the issues discussed on pp. 16-21 of Haendel et. al., 2018. Deadline: noon, September 24


Advance reading (prior to September 17 lecture): Chapters 5 and 6 of Arp, Smith and Spear, 2016

September 17 Basic Formal Ontology

Advance reading (prior to September 24 lecture): SW Smith and Koppel, 2014

September 24: Ontology and Information Engineering in the Healthcare Domain

Class assignment: discuss in a 2-page essay the extent to which the Basic Formal Ontology can assist in dealing with the problems discussed in (Smith & Koppel, 2014). Deadline: noon, October 18


Advance reading (prior to October 1 lecture): Merelli, et al, 2014

October 1: Big Data and How to Overcome the Problems It Causes

Definition of 'Big Data'
Overview of machine learning and other approaches to the exploitation of Big Data
Role of ontology in Data Science

October 8: Protege Class (Brian Dononue)

October 15: Ontological Realism

Reading: https://www.ncbi.nlm.nih.gov/pubmed/21431244

October 22: Ontology of Organizations

October 29: Artificial Intelligence and Machine Learning

November 5: Building Ontologies: Examples and Worked Exercises

November 12: Finance Ontology

November 19: Ontology of Capabilities

November 26: Presentations of Student Projects 1

December 3: Presentations of Student Projects 2