Ontology for Data Science: Difference between revisions
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'''Title: PHI | '''Title: PHI 598: Introduction to Ontology for Data Science and Information Fusion (Special Topics Course in Ontology)''' | ||
''' | '''Initial Offering: TBD''' | ||
'''Faculty: [http://ontology.buffalo.edu/smith Barry Smith]''' | '''Faculty: [http://ontology.buffalo.edu/smith Barry Smith]''' | ||
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=='''Course Details'''== | =='''Course Details'''== | ||
'''Registration:''' [http://www.buffalo.edu/cas/philosophy/grad-study/grad_courses/springcourses_grad.html#title_0 Class# ]. Registration details for off-campus students are provided under Part Time/Graduate [http://studentaccounts.buffalo.edu/tuition/spring.php here]. An online version of this course will be offered. Details | '''Registration:''' [http://www.buffalo.edu/cas/philosophy/grad-study/grad_courses/springcourses_grad.html#title_0 Class# ]. Registration details for off-campus students are provided under Part Time/Graduate [http://studentaccounts.buffalo.edu/tuition/spring.php 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 | '''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 | ||
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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 | ||
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 | ||
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| The student will acquire an introductory knowledge of current ontology methods in areas relating to data science and information fusion | | The student will acquire an introductory knowledge of current ontology methods in areas relating to data science and information fusion | ||
| Class lectures | | Class lectures | ||
| | | Attendance registry | ||
|- | |- | ||
| The student will acquire experience in ontology development | | The student will acquire experience in ontology development | ||
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
