Ontological Engineering: Difference between revisions

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This course is an on-line compilation of video materials from [[Ontological Engineering 2013]] and [[Ontological Engineering 2014]] taught in the University at Buffalo Departments of Philosophy and Industrial Engineering in 2013 and 2014. The course provides an introduction to the methods and uses of ontological engineering, focusing on applications in areas such as military intelligence, healthcare, and document processing. It provides an overview of how ontologies are created and used. It also addresses some of the human factors underlying the success and failure of ontology projects, including issues of ontology governance and dissemination.
This course is an on-line compilation of video materials from [[Ontological Engineering 2013]] and [[Ontological Engineering 2014]] taught in the University at Buffalo Departments of Philosophy and Industrial Engineering in 2013 and 2014. The course provides an introduction to the methods and uses of ontological engineering, focusing on applications in areas such as military intelligence, healthcare, and document processing. It provides an overview of how ontologies are created and used. It also addresses some of the human factors underlying the success and failure of ontology projects, including issues of ontology governance and dissemination.


The course is built out of 15 three credit hour sessions.
The course is built out of fifteen 3-credit-hour sessions.


== '''Background''' ==
== '''Background''' ==
Line 24: Line 24:
==2: Big Data and How to Overcome the Problems it Causes==
==2: Big Data and How to Overcome the Problems it Causes==


[http://ncor.buffalo.edu/2014/IE500/2-Big-Data.pptx Lecture]
We are living in a world of big data. To find our way around this world, we need to identify and integrate the data that is important to our needs. The problem is that data is collected always from different perspectives, with different levels of detail, different granularities for example of space and time, and different communities use different technologies and different terminologies when collecting their data. This session provides an introduction to the problems of data fusion.  


[http://ncor.buffalo.edu/2014/IE500/Labs/Ontology%20Engineering%20Lab%202%20September%208.pptx Lab]
*How to Integrate Data
*[http://ncor.buffalo.edu/2013/IE500/4-How-to-integrate-data.pptx Slides] &[http://ncor.buffalo.edu/2013/IE500/Videos/4-Integrating-Data.mp4 Video]  


We are living in a world of big data. To find our way around this world, we need to identify and integrate the data that is important to our needs. The problem is that data is collected always from different perspectives, with different levels of detail, different granularities for example of space and time, and different communities use different technologies and different terminologies when collecting their data. This session provides an introduction to the problems of data fusion. Strategies to address these problems:
*Ron Rudnicki: The CUBRC - US Army Ontology Collaboration  
 
*[http://ncor.buffalo.edu/2013/IE500/20-Ontologies-for-the-Intelligence-Community.pptx Slides]  
*Linked open data
*[http://ncor.buffalo.edu/2013/IE500/Videos/20-AIRS-ontologies.mp4 Video]  
*Mashups
*Crowdsourcing
*[http://en.wikipedia.org/wiki/Data_fusion Data fusion]
*More simple examples
*The Protege Ontology Editor
 
We outline some of the successes and failures of these different strategies, and introduce some of the features peculiar to the ontological approach underlying much of the work on data fusion taking place in UB, as a preparation for later sessions in this class.
 
*How to Integrate Data ([http://ncor.buffalo.edu/2013/IE500/4-How-to-integrate-data.pptx Slides] [http://ncor.buffalo.edu/2013/IE500/Videos/4-Integrating-Data.mp4 Video] from last year's class)
 
*Ron Rudnicki: The CUBRC - US Army Ontology Collaboration ([http://ncor.buffalo.edu/2013/IE500/20-Ontologies-for-the-Intelligence-Community.pptx Slides] and [http://ncor.buffalo.edu/2013/IE500/Videos/20-AIRS-ontologies.mp4 Video] from last year's class)


<!--*Lab 2: Protégé, building the taxonomy, introduction to defining classes with OWL [http://ncor.buffalo.edu/2013/IE500/Labs/Lab-2.pptx Slides] [http://ncor.buffalo.edu/2013/IE500/Videos/Labs/Ron-2.mp4 Video]-->
<!--*Lab 2: Protégé, building the taxonomy, introduction to defining classes with OWL [http://ncor.buffalo.edu/2013/IE500/Labs/Lab-2.pptx Slides] [http://ncor.buffalo.edu/2013/IE500/Videos/Labs/Ron-2.mp4 Video]-->

Revision as of 23:03, 22 May 2016

Instructor: Barry Smith

Office hours: By appointment via email at [1]

The Course

This course is an on-line compilation of video materials from Ontological Engineering 2013 and Ontological Engineering 2014 taught in the University at Buffalo Departments of Philosophy and Industrial Engineering in 2013 and 2014. The course provides an introduction to the methods and uses of ontological engineering, focusing on applications in areas such as military intelligence, healthcare, and document processing. It provides an overview of how ontologies are created and used. It also addresses some of the human factors underlying the success and failure of ontology projects, including issues of ontology governance and dissemination.

The course is built out of fifteen 3-credit-hour sessions.

Background

Ontologies are an important tool in all areas where data is collected and described by different groups in different ways. Ontologies provide taxonomy-based computerized lexica used to describe diverse bodies of data. They thereby help to aggregate and compare data, to make data more easily discoverable, and to allow large bodies of data to be more effectively searched and analyzed. Ontologies also play an important role in the so-called Semantic Web, where the Web Ontology Language (OWL) forms a central building block in the stack of web technology standards created by the World Wide Web Consortium (W3C).

UB ontologists are involved in a variety of national and international projects in the military, healthcare, bioscience, transport and financial domains. There is an acknowledged shortage of persons with ontological engineering expertise in all these fields, and in related fields such as journalism, manufacturing and government administration.


1: Introduction to Ontology

  • Ontology: A Brief Introduction Slides Video
  • Ontology: From Philosophy to Engineering Slides Video
  • Tanya Malyuta (CUNY): Ontologies vs. Data Models Slides Video
  • Tanya Malyuta (CUNY): Horizontal Integration of Intelligence Data Slides Video

2: Big Data and How to Overcome the Problems it Causes

We are living in a world of big data. To find our way around this world, we need to identify and integrate the data that is important to our needs. The problem is that data is collected always from different perspectives, with different levels of detail, different granularities for example of space and time, and different communities use different technologies and different terminologies when collecting their data. This session provides an introduction to the problems of data fusion.

  • Ron Rudnicki: The CUBRC - US Army Ontology Collaboration
  • Slides
  • Video



September 15 An Introduction to Basic Formal Ontology

  • Why a standard ontology architecture is needed
  • An introduction to Basic Formal Ontology (BFO)
  • BFO and its competitors
  • Building ontologies with BFO

Background

Lab


September 22: Use of Ontologies in Tracking Systems

Presenter: Werner Ceusters

A referent tracking system (RTS) is a special kind of digital information system that is designed to keep track of both (1) what is the case in reality and (2) what is expressed in other information systems about what is believed to be the case in reality. An RTS also keeps track of how changes in the information system correspond to changes in the reality outside that system. We will provide an introduction to referent tracking and its implementations. Reading: How to track absolutely everything?

Slides

Background

Lab


September 29: How to Build an Ontology

An overview of ontology research in Buffalo

Slides

How to build an ontology 1

Slides

Video

  • Military ontology
Slides1 Video1 Slides2 Video2

Lab

October 6: Creating Ontologies That Work Together

How to build an ontology 2 Slides Video

  • The Airs Suite of Ontologies
  • Annotating Intelligence Data
  • Information Artifacts: Publications, databases, passports, emails
  • The Email Ontology
  • Minimal Information Checklists

Background

Lab

October 13: Ontology and Information Engineering in the Healthcare Domain

Health care today rests increasingly on the proper use of data deriving from different sources (data pertaining to genes, diseases, symptoms, drugs, medical devices, procedures, hospital infections and other adverse events, hospital management, billing, reporting, and many more). We provide an introduction to the ontology of disease, with special reference to the phenomenon of aging.

Ontology for General Medical Science Slides Video

Background

Lab

October 20: The Science of Document Informatics

What is a document? Slides Video (to be edited)

What can we do with documents?

What can we do with digital documents that we can't do with paper documents?

What is a diagram?

How can we extend the technology of optical character recognition (OCR) to comprehend also the graphical content of documents?

Background:

Ontology projects to be discussed

Lab

Slides

October 27: The Semantic Web

Presentations by Alan Ruttenberg

  • Semantic Web Vision and History [shttp://ncor.buffalo.edu/2014/IE500/9-Vision-History.pptx Slides] [2]
  • Technology of the Semantic Web Slides Video

Background

  • The term "Semantic Web" was introduced by Tim Berners-Lee and others in the late 1990's (1, 2) and first popularized in a paper in 2001 in Scientific American (see below). Berners-Lee summarizes the idea as "a web of data that can be processed directly and indirectly by machines", an extension of the web of documents primarily intended for consumption by people.

November 3: Ontology Examples

Topics will include:

Background on Question Ontology
Background on Engineering Ontology

Lab

Slides

November 10: Finance Ontology

Background

  • Dennis E. Wisnosky: Video

November 17: The Ontology of Plans

The Ontology of Planning Slides

Background

Erik Thomsen, William Duncan, Tatanya Malyuta and Barry Smith, “A Computational Framework for Living Plan Specification, Execution and Evaluation”, Proceedings of the Conference on Semantic Technology in Intelligence, Defense and Security (STIDS), George Mason University, Fairfax, VA, November 18-20, 2014.

Kym S. Pohl and Peter Morosoff, "ICODES: A Load-Planning System that Demonstrates the Value of Ontologies in the Realm of Logistical Command and Control (C2)", InterSymp-2011, Baden-Baden, Germany, 2 Aug, 2011.

Jens Pohl, "An Intelligent Supply Chain Planning and Execution Environment" Proceedings of InterSymp-2011: Baden-Baden, Germany. Aug. 2011.

Austin Tate, Towards a Plan Ontology (1996)

Austin Tate Plan Ontology Page

Planning Initiative Shared Planning and Activity Representation - SPAR (1997)

Philip R. Cohen and C. Raymond Perrault, Elements of a Plan‐Based Theory of Speech Acts (1979). Summarized here

Massively Planned Social Agency

November 24: Presentations of Student Projects 1

1. Philip Odonkor: Energy Ontology for Net-Zero Buildings

Slides
Ontology
Report

2. Jeon-Young Kang: An Ontology for Capturing Change

Slides

3. Joana Monteiro: Victim Management Ontology

Slides
Ontology
Report

December 1: : Presentations of Student Projects 2

1. Lauren Madar: Retail Banking Ontology

Slides
Ontology
Report

2. Cameron Bosinski: Question Ontology

Slides

3. Fumiaki Toyoshima: University Ontology

Slides
Ontology
Report

4. Keith Fitzsimmons: Lathe Maintenance Ontology

Slides
Ontology
Report

Examples of Student Projects from 2013

  • Jordan Feenstra and Yonatan Schreiber: Music Ontology
Ontology
Slides
Report1
Report2
  • Yi Yang and Jeon-Young Kang: GIS Ontology
Ontology
Slides
Report
  • David Lominac: Customer Ontology
Ontology
Slides
Report
Video
  • Lucas Mesmer: Manufacturing Ontology
Ontology
Slides
Report
Video
  • Travis Allen: Twitter Ontology
Ontology
Slides
Report
Video
  • Chad Stahl: Chemical Manufacturing Ontology
Ontology
Slides
Report
  • Brian Donohue and Neil Otte: Personality Ontology
Ontology
Slides
Report
  • Kevin Cui: GIS Data Model Ontology
Ontology
Slides
Report
Video
  • Xinnan Peng: Manufacturing Ontology
Ontology
Slides
Report
  • John Beverley: Thermodynamic Equilibrium Ontology
Ontology
Slides
Report
  • Paul Poenicke: Gettier Problem Ontology
Ontology
Slides
Report
  • Adam Houser: Game Artifact Ontology
Ontology
Slides
Report
Video
  • William Hughes and Michael Moskal: Unmanned Aerial Vehicle Ontology
Ontology
Slides
Report
Video
  • Kanchan Karadkar: Supply Chain Management Ontology
Ontology
Slides
Report
Video
  • Norman Sung: Musical Genre Ontology
Ontology
Slides
Report

Guidance for Presentations and Reports

Examples of what to include
Statement of scope of the ontology
The true path rule
Identification of existing ontologies
Explanation of how your ontology differs from (or incorporates) these
Screenshots of parts of the ontology with some examples of important terms and definitions
Summaries of potential applications of the ontology
Evaluation
Completeness

Grading and Related Policies and Services

All students will be required to take an active part in class discussions throughout the semester. In addition they will be required to design and complete an ontology project, including written description, and brief presentation of the project in class. Students enrolled in the practical segment will be required to create a Protégé file to accompany their ontology project, and also to complete quizzes designed to gauge developing competence in the use of the Protégé Ontology Editor and SPARQL query language.

For 3 credit hour students, your grade will be determined in five equal portions deriving from:

1. class participation (1.5% per class attended),
2. results of two quizzes relating to the lab portion of the course
3. written description of ontology project (3000 words; deadline December 2),
4. Protégé ontology file (deadline November 25),
5. class presentation.

For 2 credit hour students, your grade is determined as follows:

1. class participation (1.5% per class attended),
2. written description of ontology project (4000 words; deadline December 2) (50%),
3. class presentation (30%).

For policy regarding incompletes see here

For academic integrity policy see here

For accessibility services see here

Preliminary Reading and Video Materials