Ontology(IT)

This document is a collection of definitions from different sources.
DiU - definition is unattainable. This means we have a URL to the source description, but not the definition itself!
DB - database.
KB - knowledge base.
PID - person ID. There are two person roles: presenting his own definition xor presenting a reference to the source of the definition.
bref - bibliographic reference. If not full, it keeps "???".
Every definition has a unique ID and is a separate unit of knowledge. If the definition is personal, "!" follows after the ID.
If there is no direct link to the source in the form of a URL, the ID of the person who provided the definition is provided to ask. If the person created the definition himself, the definition's ID is followed by "!".
End letter "G" in definition ID means that the definition is IN GENERAL i.e. not only for IT.
General abbr
ITSM - IT Service Management refers to the entire lifecycle of designing, delivering, managing, and optimizing IT services for users. URL:???

goto

Collector, please visit:
-DOL, TLO
-every onto language or family: DL, OWL2, CL, hets.eu
Points has been visited see [1]

Rules to keep collection and discussion

see DEFINITIONs. rules & tasks

Distinguishing properties

Here we collect various ways to distinguish whether a KB is an ontology. And any useful ideas.

+$+VERSION#1(JA)2

9. Reiterating criteria clearly
Based on ISO and ontology engineering literature, we can state:
A knowledge base becomes an ontology when:

2. Its vocabulary explicitly defines domain classes and relations (Gruber 1993; Studer et al. 1998).

3. Its assertions are intended as domain axioms expressing ontological commitment (Guarino 1998).

4. The representation language has formal declarative semantics independent of execution strategy (Tarski 1956; OWL 2 Direct Semantics 2012).

5. Inference derives from logical consequence under that semantics (Baader et al. 2003).

That does not require Hermit.
It does not exclude Prolog.
It does require logical formalization. The disagreement here is not about ISO being wrong.
It is about ISO defining a superset category.
Ontology, in the semantic-technology sense, is a stricter subclass of knowledge base.

COLLECTION

The years should be in order - the last two digits.

GRB93

An ontology is an explicit specification of a conceptualization.
URL PID:TG bref:Thomas R. Gruber. A Translation Approach to Portable Ontology Specifications. Knowledge Acquisition, 5(2):199-220, 1993.

(Z)NG98

An ontology is a logical theory accounting for the intended meaning of a formal vocabulary¹², i.e. its ontological commitment to a particular conceptualization of the world. The intended models of a logical language using such a vocabulary are constrained by its ontological commitment. An ontology indirectly reflects this commitment (and the underlying conceptualization) by approximating these intended models.
¹² Not necessarily this formal vocabulary will be part of a logical language: for example, it may be a protocol of communication between agents.
URL PID:NG bref: p(5) in Guarino, N. (1998). Formal ontology and information systems. In Guarino, N., editor, Proceedings of Formal Ontology in Information Systems (FOIS’98), Frontiers in Artificial intelligence and Applications, pages 3-15. Amsterdam: IOS Press.

Comments

<AS:This definition is not in a normal form, for example: "i.e." must be eliminated, description of models is not a part of definition, etc. BUT the text cited is a NG's way to define, as he wrote: "With these clarifications, we come up to the following definition, which refines Gruber’s definition by making clear the difference between an ontology and a conceptualization:" In such a case we need to get a "normal" or canonical form of definition.>

JS00

A catalog of the types of things that are assumed to exist in a domain of interest D from the perspective of a person who uses a language L for the purpose of talking about [the domain] D.
URL:??? PID:JS bref: John F. Sowa, "Knowledge Representation - Logical, Philosophical, and Computational Foundations", 2000, P.492.

Comments

AS:from IAOAcat[4]

WebONT03

In the contest of this work, we refer to what is sometimes called a "structural" ontology -- a machine readable set of definitions that create a taxonomy of classes and subclasses and relationships between them.
URL PID:WWW

canonical form

Ontology is a machine readable set of definitions that create a taxonomy of classes and subclasses and relationships between them.

Comments

JA:In the context of OWL (Web Ontology Language) an ontology is equivalent to a Description Logic knowledge base. (Horrocks, I., Patel-Schneider, P. F., and van Harmelen, F. From SHIQ and RDF to OWL: The making of a web ontology language. Journal of Web Semantics, 2003, 1(1):7. (paper)
AS:In this paper it's supposed that we know what ontology is. Paper has a URL to IT-ontology DEFINITIONs

BL04

The catalogue of concepts (constants, relations, functions, etc.) used to represent knowledge about a problem domain.
URL:??? PID:NA bref: (p.44, "KNOWLEDGE REPRESENTATION AND REASONING" by Ronald J. Brachman and Hector J. Levesque (2004))

Comments

AS:from IAOAcat[5]

SKSC06

An ontology is a representational artifact, comprising a taxonomy as proper part, whose representational units are intended to designate some combination of universals, defined classes, and certain relations between them.¹³
URL PID:NA bref: p.61(5) Smith, B., Kusnierczyk, W., Schober, D., Ceusters, W. Towards a Reference Terminology for Ontology Research and Development in the Biomedical Domain. KR-MED 2006 “Biomedical Ontology in Action”. November 8, 2006, Baltimore, Maryland, USA.

WIKIP

(1)an ontology encompasses a representation, formal naming, and definitions of the categories, properties, and relations between the concepts, data, or entities that pertain to one, many, or all domains of discourse.
(2)an ontology is a way of showing the properties of a subject area and how they are related, by defining a set of terms and relational expressions that represent the entities in that subject area.
URL

Comments

Citation:"In information science, an ontology encompasses a representation, formal naming, and definitions of the categories, properties, and relations between the concepts, data, or entities that pertain to one, many, or all domains of discourse. More simply, an ontology is a way of showing the properties of a subject area and how they are related, by defining a set of terms and relational expressions that represent the entities in that subject area."
+get defs from https://en.wikipedia.org/wiki/Ontology_%28information_science%29#Formal_ontology
+see also https://en.wikipedia.org/wiki/Formal_ontology

JA004! AS:🏅

A knowledge base whose artifacts constitute explicit axioms about domain entities and relations, expressed in a language with formal declarative semantics.
URL PID:JA

related terms

conceptualization

"A body of formally represented knowledge is based on a conceptualization: the objects, concepts, and other entities that are presumed to exist in some area of interest and the relationships that hold them (Genesereth & Nilsson, 1987). A conceptualization is an abstract, simplified view of the world that we wish to represent for some purpose. Every knowledge base, knowledge-based system, or knowledge-level agent is committed to some conceptualization, explicitly or implicitly." TG

formal language

AS: Chris Mungall has ontology on Python. Some Prolog programs are not ontology.

formal vocabulary

see in IT-ontology DEFINITIONs

model

see in IT-ontology DEFINITIONs

ontological commitment

see in IT-ontology DEFINITIONs
=== theory ===
, logical see in IT-ontology DEFINITIONs

DISCUSSION

(JA)2 IT-ontology intended to…

3. On Contradiction and Completeness
You raise an important philosophical question:

Is the IT-ontology complete and non-contradictory knowledge about the domain?

My answer is: no.
An IT-ontology is not complete knowledge. It is not guaranteed consistent in practice. It is not a total theory of a domain.
It is a formalized conceptual model intended to:

• Constrain interpretation,

• Enable logical consequence,

• Make commitments explicit.

It may be incomplete.
It may contain modeling errors.
It may require revision.
So I would not define IT-ontology as “complete knowledge.”
I would define it as:

A formally specified conceptualization expressed in a representation language with explicit semantics.

It is closer to a theory schema than to a complete theory.
Your formulation — “a theory or model for theory” — is actually very close to how ontology engineers think about it.

(JA)1 topics around

"That is why ontology engineers distinguish:

• Vocabulary (classes, properties)

• Axioms (subsumption, equivalence, restrictions)

• Rules (SWRL, production rules, etc.)

They are not the same category.

• Baader et al., The Description Logic Handbook (2003), distinguish TBox (terminological axioms: classes, subsumption, properties) from ABox (assertions about individuals), and separate these from rule systems.

• The W3C OWL 2 Structural Specification (2012) clearly distinguishes class axioms and property axioms from rule extensions such as SWRL.

" "So ontology status does not depend on Hermit accessibility. It depends on whether the representation language has well-defined declarative semantics.

• The OWL 2 Direct Semantics (W3C Recommendation, 2012) provides a model-theoretic semantics independent of any specific reasoner.

• Description logic semantics are formally defined in Baader et al. (2003).

• The model-theoretic tradition originates with Tarski (1956), Logic, Semantics, Metamathematics.

" "Some Prolog KBs can function as ontologies. But many do not. Why? Because they often:

• Mix domain knowledge with control strategy

• Use procedural constructs (cuts, ordering effects)

• Lack explicit ontological commitments (identity criteria, typing discipline, subsumption structure)

A clean, purely declarative first-order theory encoded in Prolog syntax could absolutely count as an ontology. A heuristic expert system implemented in Prolog typically would not. So the issue is not “Prolog vs OWL.”
It is declarative domain theory vs procedural problem-solving system.

• Mix domain knowledge with control strategy (Lloyd 1987).

• Depend on operational features such as ordering and cut (Kowalski 1979).

Lack explicit ontological commitments in the sense articulated by Guarino (1998). " "So again, the distinction hinges on logical formalization, not file format. Hets (Mossakowski, Maeder & Lüttich, 2007, TACAS) is grounded in institution theory (Goguen & Burstall, 1992 " "An ontology in IT is a formal artifact with explicit semantics. A conceptual model written in English may describe an ontology.
It is not an ontology artifact until formalized.
This is the same distinction between:

• Mathematical truth

• A formal proof in a specified logical system

Ontology engineering operates in the latter space.

• Noy & McGuinness (2001), Ontology Development 101, emphasize formal class and property specification.

• Smith (2003), “Ontology,” in Blackwell Guide to the Philosophy of Computing and Information, distinguishes philosophical ontology from computational ontology artifacts.

"

Consolidated Decision: Base Definition for IT-ontology

(AS)Starter: formal ontology is a KB where knowledge is fully structured and formalized as much as possible.

(JA) “Ontology is a knowledge base, but not every knowledge base is an ontology”

URL <AS:text has hints to definition sources>
This is not a rhetorical move. It is a distinction established in the ontology engineering community.
The differentiator is not:

• Whether inference occurs

• Whether rules exist

• Whether a reasoner like Hermit can process it

The differentiator is whether the artifact is a formal specification of a conceptualization, not merely a rule-based problem-solving system.
This distinction appears in:

• Gruber (1993)

• Guarino (1998)

• Studer, Benjamins & Fensel (1998)

• The W3C OWL specifications

The key issue is ontological commitment, not computational accessibility.

• Gruber (1993), “A Translation Approach to Portable Ontology Specifications,” Knowledge Acquisition.

• Studer, Benjamins & Fensel (1998), “Knowledge Engineering: Principles and Methods,” Data & Knowledge Engineering.

• Guarino (1998), “Formal Ontology in Information Systems,” FOIS 1998.

Person IDs

in ABC order.

AS Alex Shkotin

Alex Shkotin
Independent Computer Scientist
Linkedin ∘ RGate ∘ Academia.edu
Ontolog BoT

BL Ben Lutkevich

https://www.techtarget.com/contributor/Ben-Lutkevich

JA John Antill

MS KM, MCKM, CKS IA & KT, KCS
MS AI Student at Purdue
256-541-1229
djanteater@gmail.com

JS John Sowa

https://ontologforum.com/index.php/JohnSowa

KB Ken Baclawski

https://ontologforum.com/index.php/KenBaclawski

NG Nicola Guarino

(1998)National Research Council, LADSEB-CNR, Corso Stati Uniti 4, I-35127 Padova, Italy. guarino@ladseb.pd.cnr.it

TG Thomas Gruber

https://www.researchgate.net/profile/Thomas-Gruber-10
File:Vertopal e3dcf0d2d79e4a57a828e871a0b6a6e7/media/image1.png
https://tomgruber.org/writing/ontolingua-kaj-1993/

Appendix A. Collections used

Terms for Central General Notions(IAOA)

https://wiki.iaoa.org/index.php/Edu:Term_List

Towards a Reference Terminology for Ontology Research and Development in the Biomedical Domain

http://ontology.buffalo.edu/bfo/Terminology_for_Ontologies.pdf