F.27 ProtOn – PROTo ONtology 

F.27.1 Overview 

PROTON (PROTo ONtology) is a basic subsumption hierarchy which provides coverage of most of the upper-level concepts necessary for semantic annotation, indexing, and retrieval. 

From https://en.wikipedia.org/wiki/Upper_ontology#PROTON.

See also: https://ontotext.com/documents/proton/Proton-Ver3.0B.pdf

F.27.2Top-level 

F.27.3 Key characteristics 

A natural language ontology. 

F.27.4 Relevant extracts 

Extracts from: https://ontotext.com/documents/proton/Proton-Ver3.0B.pdf 

Extract 1 – Design principles 

The PROTON ontology contains about 500 classes and 150 properties, providing coverage of 

the general concepts necessary for a wide range of tasks, including semantic annotation, 

indexing, and retrieval. The design principles can be summarized as follows: 

• domain-independence; 
• lightweight logical definitions; 
• alignment with popular metadata standards; 
• good coverage of named entity types and concrete domains (i.e. modelling of concepts such as people, organizations, locations, numbers, dates, addresses, etc.); and 

good coverage of instance data in Linked Open Data Reasonable view Fact Forge. 

The ontology is encoded in a fragment of OWL Lite and split into four modules: System, Top, 

Extent, and KM (Knowledge Management). A snapshot of the PROTON class hierarchy is 

given on Figure 1, showing the Top and the Extent modules. 

Extract 2 – PROTON is relatively un-restrictive 

1. Design Rationales 

PROTON is designed as a lightweight upper-level ontology for use in Knowledge 

Management and Semantic Web applications. The above mission statement has two important 

implications: 

PROTON is relatively un-restrictive. It specifies only a hierarchy of classes and domain and range of properties defined within it, but it does not impose any other restrictions on the meaning of the classes and properties. 

PROTON is not precise in some aspects, for instance regarding the conceptualization of space and time. This is partly because proper models for these aspects would require using a logical apparatus, which is beyond the limits acceptable for many of the tasks to which we wish to apply PROTON (e.g. queries and management of huge datasets/knowledge bases); and partly because it is very hard to craft strict and precise conceptualizations for these concepts, which are adequate for a wide range of domains and applications. 

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