Words Used in Proposal

Words for specifying data

Data

An item of factual information derived from measurement or research.

Data Element

Field or column in a data-set or data-base that stores Data.

Data Dictionary

Specifies information about a Data Element. Information includes field name, field description, data type and constraint for Data Element.

Data Model

Representation of how to aggregate and interrelate Data defined by a Data Dictionary.

Entity-Relationship Model

Representation of how to aggregate and inter-relate information. An entity is a Thing capable of an independent existence and is uniquely identified. Entities are nouns. Examples: a food commodity, a food consumer, a recipe, or a food label calculation. A relationship specifies how entities are related to one another. Relationships are verbs, linking two or more nouns. Examples are: beneficial for, caused by, composed of, made from, produced by, used in. Entities and relationships have Properties, such as a distinguishing quality, a physical state, or a characteristic that is determined by a gene or group of genes.

Words for specifying information

Context

Discourse that surrounds a language unit and helps to determine its interpretation. For the USDA project, the Context of the language unit is Food. In other words, the Domain-of-Context is Food.

Vocabulary

A listing or grouping of words that are common to a Domain-of-Context.

Controlled Vocabulary

Authorized words that have been preselected for a Domain-of-Context. Contrasts with natural language vocabularies, where there is no restriction on the vocabulary.

Term

Word in a Controlled Vocabulary that references a Description. Term is described in a Thesaurus.

Taxonomy

Categorization of Things (entities). Categorization is based on discrete sets. Taxonomy may have multiple forms, such as lists and hierarchies.

Metadata

Same as a word in a Taxonomy.

Thesaurus

Provides information about a Term in a Controlled Vocabulary. Includes long name, short name or acronym, and description in form of Scope Notes and Additional Information.

Glossary

Defines words associated with a project. A word in a glossary is not necessarily a Term in a Controlled Vocabulary.

Encyclopedia

The services known as Wikipedia and DBpedia. Wikipedia disambiguation associates a word with a Domain-of-Context.

Words for specifying knowledge

Syntax

Rules for specifying Terms to create structures like phrases, sentences, and paragraphs.

Grammar

Rules for specifying a set of well-formed structures using Terms of a given Language.

Language

Set of Terms specified by a Syntax and sequenced according to a Grammar. Language is used to systematically define and aggregate knowledge.

Ontology

Combination of the above to express higher order activities, such as communications, translation, learning, understanding, teaching, and making decisions. More specifically, a formal way to represent entities, ideas, and events (Things). Things have Properties such as names and values. Things have Relations such as kinship and sequence of steps (ordinality) to perform a task. Things, Properties and Relations are organized by categories (Taxonomy). Knowledge - in a form that can be processed by a computer - is the categorical ordering of Things, Properties and Relations from Domain-of-Context into a Domain-of-Knowledge.

Words for specifying relations

IS-A relationship

Specifies relations between abstractions (e.g. types, classes), where one class A is a subclass of another class B (and so B is a superclass of A). In other words, type A is a subtype of type B when A’s specification implies B’s specification. More specifically, the IS-A relationship is defined by:

1. Hypernymy-Hyponymy (supertype-subtype) relations between types (classes) defining a taxonomic hierarchy, where a hyponym (subtype, subclass) has a type-of (IS-A) relationship with its hypernym (supertype, superclass)
2. Holonymy-Meronymy (container-part or member) relations between types (classes) defining a possessive hierarchy.

HAS-A relationship

Specifies part-whole relations. Meronym is the name given to a constituent part of, the substance of, or a member of something. ‘X’ is a meronym of ‘Y’ if an X is a part of a Y. A meronym may be:

1. Transitive - “Parts of parts are parts of the whole” - if A is part of B and B is part of C, then A is part of C.
2. Reflexive - “Everything is part of itself” - A is part of A.
3. Antisymmetric - “Nothing is a part of its parts” - if A is part of B and A !- B then B is not part of A.

Domain

Set of values for a Term declared in a Relation.

Range

Limits for the values of a Term declared in a Relation.

Symmetric relationship

Declaration that Terms are essentially the same and are interchangeable.

Words for implementing an Ontology

Ontology (continuing to add precision to the word “Ontology” previously used above)

Uses a Controlled Vocabulary to specify Things, Properties and Relations for a Domain-of-Knowledge. Defines a set of statements about a Domain-of-Knowledge. Statements in Ontomatica ontologies are implemented as Graphs.

Faceted Classification

Enables assignment of a Term to multiple categories in a Taxonomy. Faceted search (a.k.a. faceted navigation or faceted browsing) is the user-interface of a faceted classification system. Users explore a collection of information by applying multiple filters (a.k.a. facet terms).

Facet Tree

Hierarchy of Facets in a specific Domain-of-Knowledge.

Thing (continuing to add precision to the word “Thing” previously used above)

An entity capable of an independent existence that can be uniquely identified.

Subject

An observer; an entity that has a relationship with another entity that exists outside of itself (an “object”). A Subject is an observer and an Object is an entity observed.

Object

An entity observed by a Subject.

Item

A Thing - associated with a Domain-of-Knowledge - that is described by one or more Terms in one or more Facet Trees. Item is comparable to Data in a Data Model and to an instance of an Entity-type in an Entity-Relationship model.

Graph

Composed of vertices {nodes} and lines {edges} that connect vertices. Ontomatica graphs are Directed Acyclic Graphs (DAG) that represent Things and causal Relations between them.

Facet and Facet Term (as defined during Facet Classification and revealed in a Facet Tree)

Vertex {node} in a Graph. Logically, a facet is a noun. A class term (word identifying a collection of Facet Terms) is called a Facet. A type term (instances of members of a Facet) is called Facet Term. Code assigned to Facet Term (FT) is called Facet Term Code (FTC).

Facet Map

Pairing of an Item with one or more Facet Terms in one or more Facet Trees.

Relation (continuing to add precision to the word “Relation” previously used above)

Line {edge} expressing connection between Facets and Facet Terms in a Graph. Logically, a relation is a verb. Term that describes a Relation is a Predicate.

Predicate and Predicate Term

Type {single} or class {hierarchy} of Relations. A class term (word identifying a collection of Predicate Terms) is called a Predicate. A type term (instances of members of a Predicate Taxonomy) is called Predicate Term. Code assigned to Predicate Term (PT) is called Predicate Term Code (PTC).

Syntax (continuing to add precision to the word “Syntax” previously used above, but now specific to Ontology)

Web Ontology Language (OWL) that specifies the Syntax for creating structures like phrases, sentences, and paragraphs.

Grammar (continuing to add precision to the word “Grammar” previously used above, but now specific to Ontology)

Set of statements in the logical form: subject predicate object where subject and object are Facet Terms and predicate are Predicate Terms.

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