Applied Ontology 2018: Difference between revisions
From NCOR Wiki
Jump to navigationJump to search
mNo edit summary |
|||
| Line 3: | Line 3: | ||
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. | 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. | ||
Faculty: Barry Smith and Werner Ceusters | Faculty: [http://ontology.buffalo.edu/smith/ Barry Smith] and [http://www.referent-tracking.com/RTU/ceusters_vita.html Werner Ceusters] | ||
:Background reading: | |||
*1. Arp, Spear and SMith, 2016: ''Building Ontologies with Basic Formal Ontology'', MIT Press, 2016 | |||
*2. Please read in advance of August 27 class: [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4652617/ Hoehndorf, Schofield & Gkoutos, 2015] | |||
==August 27: Introduction to Ontology== | ==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 on the extent to which the key elements of ontology as identified in the lecture are considered (or not considered) in: Hoehndorf, Schofield and Gkoutos, 2015. Deadline: noon, September 6 | |||
==September 3: Labor Day – No class== | ==September 3: Labor Day – No class== | ||
==September 10: Big Data and How to Overcome the Problems It Causes== | ==September 10: 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 | |||
Reading (prior to September 17 lecture): Chapters 5 and 6 of Arp, Smith and Spear, 2016 | Reading (prior to September 17 lecture): Chapters 5 and 6 of Arp, Smith and Spear, 2016 | ||
| Line 18: | Line 32: | ||
==September 24: Ontology and Information Engineering in the Healthcare Domain== | ==September 24: Ontology and Information Engineering in the Healthcare Domain== | ||
Reading (prior to October 1 lecture): 1. [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3041577/ Scheuermann, Ceusters and Smith, 2009]. 2. [https://www.annualreviews.org/doi/pdf/10.1146/annurev-biodatasci-080917-013459 Haendel ''et. al.'', 2018] | |||
==October 1: Ontology of Disease== | ==October 1: Ontology of Disease== | ||
==October 8: Protege Class (Brian Dononue)== | ==October 8: Protege Class (Brian Dononue)== | ||
| Line 29: | Line 45: | ||
==November 26: Presentations of Student Projects 1== | ==November 26: Presentations of Student Projects 1== | ||
==December 3: Presentations of Student Projects 2== | ==December 3: Presentations of Student Projects 2== | ||
Revision as of 15:08, 28 May 2018
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.
Faculty: Barry Smith and Werner Ceusters
- Background reading:
- 1. Arp, Spear and SMith, 2016: Building Ontologies with Basic Formal Ontology, MIT Press, 2016
- 2. Please read in advance of August 27 class: Hoehndorf, Schofield & Gkoutos, 2015
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 on the extent to which the key elements of ontology as identified in the lecture are considered (or not considered) in: Hoehndorf, Schofield and Gkoutos, 2015. Deadline: noon, September 6
September 3: Labor Day – No class
September 10: 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
Reading (prior to September 17 lecture): Chapters 5 and 6 of Arp, Smith and Spear, 2016
September 17 Basic Formal Ontology
Reading (prior to September 24 lecture): SW Smith and Koppel, 2014
September 24: Ontology and Information Engineering in the Healthcare Domain
Reading (prior to October 1 lecture): 1. Scheuermann, Ceusters and Smith, 2009. 2. Haendel et. al., 2018
