Ontology for Data Science: Difference between revisions

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'''Title: PHI 598: Introduction to Ontology for Data Science and Information Fusion (Special Topics Course in Ontology)'''
'''Title: PHI 598: Introduction to Ontology for Data Science and Information Fusion (Special Topics Course in Ontology)'''


'''Proposed Initial Offering: Spring 2019'''
'''Initial Offering: TBD'''


'''Faculty: [http://ontology.buffalo.edu/smith Barry Smith]'''  
'''Faculty: [http://ontology.buffalo.edu/smith Barry Smith]'''  
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:(2) ontology-building exercises to be completed within the first 2 weeks of the semester.  
:(2) ontology-building exercises to be completed within the first 2 weeks of the semester.  


An on-line version of the course will form part of the compulsory online ontology course in the CMIF [https://www.buffalo.edu/cmif/education.html Master of Engineering in Data and Information Fusion]. (It will constitute 1 of the 3 credit hours for this program.  
An on-line version of the course will form part of the compulsory online ontology course in the CMIF [https://www.buffalo.edu/cmif/education.html Master of Engineering in Data and Information Fusion]. (It will constitute 1 of the 3 credit hours for this program.)


'''Course Description:''' An ontology is a structured collection of terms used to tag data with the goal of making data deriving from heterogeneous sources more easily searchable, comparable. combinable, or analysable. Ontologies allow information to be shared across communities with different sorts of expertise. The course will provide an introduction to ontology for students of data science and information fusion. It is co-sponsored by the Department of Philosophy and the Center for Multi-Source Information Fusion.
'''Course Description:''' An ontology is a structured collection of terms used to tag data with the goal of making data deriving from heterogeneous sources more easily searchable, comparable. combinable, or analysable. Ontologies allow information to be shared across communities with different sorts of expertise. The course will provide an introduction to ontology for students of data science and information fusion. It is co-sponsored by the Department of Philosophy and the Center for Multi-Source Information Fusion.
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:3: 2000s: Lessons from the Human Genome Project
:3: 2000s: Lessons from the Human Genome Project
:4: 2010s: Current examples of uses of ontology in data science and information fusion
:4: 2010s: Current examples of uses of ontology in data science and information fusion
11:00


12:00 Lunch
12:00 Lunch
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9:00 Use of Ontologies in Intelligence Domains
9:00 Use of Ontologies in Intelligence Domains
:Ontology and Intelligence Analysis
:Ontology and Intelligence Analysis
:Ontology and Geospatial Intelligence
:Ontology and Information Fusion
:Ontology and Information Fusion



Latest revision as of 15:00, 2 June 2018

Title: PHI 598: Introduction to Ontology for Data Science and Information Fusion (Special Topics Course in Ontology)

Initial Offering: TBD

Faculty: Barry Smith

Venue: TBA

Course Details

Registration: Class# . Registration details for off-campus students are provided under Part Time/Graduate here.

An online version of this course will be offered. Details will be provided HERE {link to be inserted}.

Course Structure: This is a one credit hour course intended for beginning PhDs, Masters and advanced Undergraduate students in all departments. Assessment will be in the form of

(1) attendance in two full days of lectures,
(2) ontology-building exercises to be completed within the first 2 weeks of the semester.

An on-line version of the course will form part of the compulsory online ontology course in the CMIF Master of Engineering in Data and Information Fusion. (It will constitute 1 of the 3 credit hours for this program.)

Course Description: An ontology is a structured collection of terms used to tag data with the goal of making data deriving from heterogeneous sources more easily searchable, comparable. combinable, or analysable. Ontologies allow information to be shared across communities with different sorts of expertise. The course will provide an introduction to ontology for students of data science and information fusion. It is co-sponsored by the Department of Philosophy and the Center for Multi-Source Information Fusion.

Schedule: The class will be taught over two consecutive days in the week before the beginning of the Spring semester.


Schedule: Day 1

8:30 Registration and Coffee

9:00 Introduction to Ontology, Data Science and Information Fusion

Ontologies and Their Applicatoins
Data Mining
Natural Language Processing
Explainable Artificial Intelligence

10:30: Coffee

10:45 Ontology Time-Line

1: 1970s: Strong AI, Robotics, PSL
2: 1990s: The Semantic Web, Linked Open Data
3: 2000s: Lessons from the Human Genome Project
4: 2010s: Current examples of uses of ontology in data science and information fusion

12:00 Lunch

12:45 Use of Ontologies in Data Fusion and Data Analysis

Examples from Biology
Examples from Environmental Sciences
Examples from Medicine

14:00 Use of Ontologies in Military Domains

Joint Doctrine Ontology
Ontology for Command and Control
Ontology and Military Logistics
Systems Engineering Ontology
Space Ontology

16:00 Close


Schedule: Day 2

8:30 Registration and Coffee

9:00 Use of Ontologies in Intelligence Domains

Ontology and Intelligence Analysis
Ontology and Geospatial Intelligence
Ontology and Information Fusion

10:30: Coffee

10:45: Ontology of Terrorism

Defining Terrorism
Terrorism and Crime
Predicting Terrorist Radicalization

12:00 Lunch

12:45 Ontology Technology

The Web Ontology Language (OWL)
Ontology Repositories
The Protégé Ontology Editor

14:00 Introduction to Ontology Building

Simple Guide to Building Ontologies with Protégé
Examples
Interactive Ontology Building Session


Further readings are provided here: http://ontology.buffalo.edu/smith/

Requirements: This course is open to all persons with an undergraduate degree and some relevant experience (for example in data scientists, information engineers, terminology researchers).

Grading will be based on:

1. class participation (50%)
2. completion of

For policy regarding incompletes see here

For academic integrity policy see here


Student Learning Outcomes

Program Outcomes/Competencies Instructional Method(s) Assessment Method(s)
The student will acquire an introductory knowledge of current ontology methods in areas relating to data science and information fusion Class lectures Attendance registry
The student will acquire experience in ontology development Ontology-building exercise Review of submitted Protégé file

Grading

Grading will be based on two factors: class participation and Protégé ontology-building exercise; the former will be assessed on the basis of attendance lists which will be circulated at on both days at non-preannounced times,

Grades will be weighted according to the following breakdown:

Weighting Assignment

50% - class attendance
50% - completion of Protégé ontology-building exercise

Students whose presence is not recorded in both lists will receive 0% for attendance. Details of requirements for the ontology-building exercise will be provided in class.

Final Grades

Grade Quality Percentage

A 4.0 93.0% -100.00%
A- 3.67 90.0% - 92.9%
B+ 3.33 87.0% - 89.9%
B 3.00 83.0% - 86.9%
B- 2.67 80.0% - 82.9%
C+ 2.33 77.0% - 79.9%
C 2.00 73.0% - 76.9%
C- 1.67 70.0% - 72.9%
D+ 1.33 67.0% - 69.9%
D 1.00 60.0% - 66.9%
F 0 59.9% or below

Related Policies and Services

Academic integrity is a fundamental university value. Through the honest completion of academic work, students sustain the integrity of the university while facilitating the university's imperative for the transmission of knowledge and culture based upon the generation of new and innovative ideas. See http://grad.buffalo.edu/Academics/Policies-Procedures/Academic-Integrity.html.

Accessibility resources: If you have any disability which requires reasonable accommodations to enable you to participate in this course, please contact the Office of Accessibility Resources in 60 Capen Hall, 645-2608 and also the instructor of this course during the first week of class. The office will provide you with information and review appropriate arrangements for reasonable accommodations, which can be found on the web here.

Background Reading and Video Materials

Optional Background Reading Robert Arp, Barry Smith and Andrew Spear, Building Ontologies with Basic Formal Ontology, Cambridge, MA: MIT Press, August 2015