Main Page

The goal of the National Center for Ontological Research is to advance ontological investigation within the United States. NCOR serves as a vehicle to coordinate, to enhance, to publicize, and to seek funding for ontological research activities. It lays a special focus on ontology training and on the establishment of tools and measures for quality assurance of ontologies. NCOR provides ontology services to multiple organizations, including the US Department of Defense.

Events

See here

For past events see here

News

Article on BFO in the Frankfurter Allgemeine Zeitung, September 28, 2022, p. N3. Translation of opening paragraph:

Industry standards are not usually associated with philosophy or the humanities. That is why the new ISO/IEC 21838 standard conceals a minor scientific-historical sensation. Because for the first time, a philosophical theory has now been declared an industry standard, namely: the "Basic Formal Ontology", BFO for short. When you try to pronounce this acronym, it sounds a lot like "Buffalo," and that's no coincidence. Because Barry Smith, the main brain behind this norm, is the Julian Park Professor of Philosophy at the University of Buffalo in northern New York State, not far from Niagara Falls ...

Courses

Barry Smith

Werner Ceusters

Defining 'Ontology'

An ontology is a representation of some part of reality, (e.g. medicine, social reality, physics, etc.). Smith states that: “Ontology is the science of what is, of the kinds and structures of objects, properties, events, processes and relations in every area of reality…Ontology seeks to provide a definitive and exhaustive classification of entities in all spheres of being.” To be an accurate representation of reality an ontology includes the types of entities and events in a given domain (along with their definitions) arranged in a hierarchical structure, along with relations (such as part-of, depends-on, caused-by, etc. where necessary). Ontologies enable the formulation of robust and shareable descriptions of a given domain by providing a common controlled vocabulary for doctrine writers, IT Developers, and war-fighters alike, thereby allowing these disparate communities to communicate with each other. An ontology should be a shared resource between communities, and its continued collaborative development should support the integration of information and facilitate knowledge discovery. These two goals are realized by ensuring wide dissemination of the ontology, so that it will be used by many stakeholders, and its terms will be correspondingly familiar and readily used for search.

Basic Formal Ontology 2.0

Basic Formal Ontology 2020

BFO 2020

Buffalo Toronto Ontology Alliance (BoaT)

Why Machines Will Never Rule the World

Interviews and Podcasts

Systems Conversation (with Dr Oliver Gao, Director, Systems Engineering, Cornell University, Ithaca, NY, September 2, 2022)

Blog of the American Philosophical Association: Interview with Charlie Taben, September 23, 2022

AI is here, but will it rule us? Wirkman Comments podcast with David Ramsey Steele (September 27, 2022). See also here.

NAS Podcast with Scott Turner: Will Machines Rule the World?, 4 October, 2022

Lecture to Philosophy and AI Research Group, University of Zurich, 14 October, 2022

Press Items and Notices

AI is cool, but will never reach human capability, Bert Gambini, August 25, 2022

Why AI will never rule the world Interview by Luke Dormehl on Digital Trends, September 25, 2022 (Recording)

UB Lecture, September 20, 2022

The Philosophome

Philosophome Website

Philosophome Wiki

Semantics of Biodiversity

Paper: Semantics in Support of Biodiversity Knowledge Discovery (PLoS ONE, 2013)

Video Presentations from: Semantics of Biodiversity Workshop (2012)

Ontologies as a method of viewing data

Basic Formal Ontology (BFO)

How to build an ontology with BFO

Tracking referents with Instance Unique Identifiers (IUIs)

Tracking Changes in Our Understanding of Reality: Reality vs. Beliefs

Darwin Core (DwC) and Basic Formal Ontology: Putting it All Together

Building Darwin Core top-down in BFO

Organisms, photographs, media

How to re-use ontologies

Principles of singular nouns, secondary use, understandability

Writing good definitions (DwC Examples)

Management strategies

Ontologies for reuse (BFO, EnvO, IDO, OBI, Plant Ontology , Uberon, IAO)

Educational resources (OBI, Protege, BFO)

Finance and Economics

An Application of Basic Formal Ontology to the Ontology of Services and Commodities, Institute for Business Informatics, University of Koblenz, Germany July 23, 2013

Barry Smith, Reference Data Integration: A Strategy for the Future, Financial Reference Data Management Conference (FIMA), New York, March 2012

The Wernicke Ontology Principle

Wernicke is an ontology-dependent AI system used to automate recurring business processes. Wernicke is based on formal logic developed by Jobst Landgrebe and co-workers at Cognotekt. Its ontologies do not have an Aristotelian taxonomic structure, but are fully axiomatised and logically describe the syntactic structure of recurring language patterns in the Prolog-subset of first order logic. The use of terms in two or more axiomatic definitions of ontological entities creates an implicit network structure within the ontology.

Examples (in German)

1. Implication relations for verbs and verb phrases. (There are hundreds of examples of such formulae in each Wernicke ontology.)

 ((zahlung(Y) AND nachkommen(Z) AND verb(Z,X,Y)) IMPL zahlen(Z))
 ((geld(Y) AND schicken(Z) AND (verb(Z,X) OR verb(Z,X,Y1))) IMPL zahlen(Z))
 ((kosten(Y) AND tragen(Z) AND verb(Z,X,Y)) IMPL zahlen(Z))
 ((überweisungsträger(Y) AND einwerfen(Z) AND verb(Z,X,Y)) IMPL zahlen(Z))
 ((bringen(Z) AND ausgleich(A) AND zum(B) AND mod(B,A,Z) AND verb(Z,X,Y)) IMPL zahlen(Z))
 ((möglich(A) AND mod(A,Z) AND sein(Z) AND (verb(Z,X) OR verb(Z,X,Y))) IMPL möglichsein(Z))  
 ((bitten(Z) AND mod(B,A,Z) AND möglichkeit(A) AND verb(Z,X,Y)) IMPL möglichsein(Z))

2. Temporal structures

 ((übermorgen(W) AND (Y=2)) IMPL zeitabstand(W,in,Y,tagen))
 ((morgen(W) AND (Y=1)) IMPL zeitabstand(W,in,Y,tagen))
 ((heute(W) AND (Y=0)) IMPL zeitabstand(W,in,Y,tagen))
 ((gestern(W) AND (Y=1)) IMPL zeitabstand(W,vor,Y,tagen))
 ((vorgestern(W) AND (Y=2)) IMPL zeitabstand(W,vor,Y,tagen))

3. Domain pattern formulae (ontologic entities)

 past payment a: ((zahlung(X) OR geld(X)) AND rausgehen(Z) AND (I=vergangen) AND verb(Z,X) AND vergangentemp(Z))
 past payment b: ((zahlung(Y) AND tätigen(Z) AND verb(Z,X,Y) AND (I=vergangen) AND vergangentemp(Z))
 past payment c: ((sein(Z) AND (betrag(X) OR forderung(X)) AND zahlen(A) AND mod(A,Z) AND (I=vergangen)
 AND verb(Z,X) AND NOT temp_mod(Z, praet, konj2)