nancy lawler u.s. department of defense iso/iec 11179 part 2: classification schemes metadata...

Nancy Lawler U.S. Department of Defense

ISO/IEC 11179 Part 2: Classification ISO/IEC 11179 Part 2: Classification SchemesSchemes

Metadata Registries — Part 2: Classification Schemes The revision of 11179 Part 2 is not an ISO standard

because it is in draft status, a project of the ANSI/NCITS L8 committee.

Excerpts from the draft standard in this talk are copyright-protected by ISO

Editors aim at consistency with other standards:ISO 704 Terminology work –principles and methodsISO 11179 Parts 1,3,4, 5,6ISO 1087 Part 2: Computational aids in terminologyISO standards for monolingual and multilingual thesauriISO/IEC 19501-1:2001 UML

Clarity goals: – Guidance should be practical, with useful distinctions, and the

language should be translatable.


What is a Classification Scheme?What is a Classification Scheme? Clearly includes: Artifacts which support controlled

vocabularies for definitions, formal specifications and descriptions– Taxonomies – Terminologies, Thesauri– Ontologies: Generalization hierarchies of concepts or classes

Linguistic Ontologies Axiomatized Ontologies

– Keyword lists– Data models

Less obvious: Any Composite Element of a System– System documentation – Mappings between data models– Data types


Part of a registered Information Part of a registered Information System may be used as a System may be used as a Classification Scheme Classification Scheme

When a relationship is maintained between one of its parts and another administered item. – Examples:

a class in a data model is derived from a registered data element originally defined within another model

a data model is generated from a cluster or subdomain of an ontology.

– In practice: if you need classification scheme attributes for a diagram, documentation or value domain, you may register it as a classification scheme.


Why Include Classification Schemes in Why Include Classification Schemes in a Metadata Registry?a Metadata Registry?

Improve metadata quality by managing use of controlled vocabularies for definitions

Manage captured domain knowledge which persists independently of applications and IT trends, and is less compromised by such considerations as cost and performance. – The meaning of the sentence "a customer buys a book

from a sales clerk" could be conveyed in a variety of knowledge and data representations:

UML class diagram or use case IDEF entity relationship diagram or process diagram The formal specification standard Z, the logic

programming language Prolog, KIF, Conceptual Graphs, or even a labelled sketch.


11179 Part 2 does not 11179 Part 2 does not mandate utility or contentmandate utility or content

It provides a structure which supports the difficult work of semantic reconciliation, using 11179’s definitions, management of status, versions and authorities– Axiomatized ontologies represent an understanding of a part of the

world related to an information system. They may include business rules, theories, and constraints, and serve as formal specifications for automatically generated database schema and applications.

– Linguistic ontologies may support natural language interfaces for queries of structured and unstructured data, extraction of information from text, and translation systems

– Mappings between models are also models Support heterogenous database access, mediators, agents,

identification of re-usable components


Classification SchemeClassification Scheme

Definition: the descriptive information for an arrangement or division of objects into groups based on characteristics which the objects have in common.

Examples: a key word list, a taxonomy, a data model, a network, an ontology. A list of terms might be taken from the "leaf level" of a taxonomy or from object classes in a data model.

Attributes: classification_scheme_type_name– Definition: the name of the type of classification

scheme. (There is no standard list of structure types and it is possible that the type used to describe a scheme may vary).

Other attributes are those of any administered item.


Classification Scheme ItemClassification Scheme ItemThese represent individual items within Classification

Schemes. They are not required to be recorded. Attributes:

– csi_type_name Definition: the name of the type of classification scheme item. Example:

– Taxon term (if the value attribute is Drosophilae)– Taxon identifier (if the value attribute is 5411)

( Phylum, Class, Order, Family, Species are levels, not item types)

– csi_value A designator of a classification scheme item Value should be unique within a classification scheme. Together

with the administration_record_identifier, this provides a globally unique namespace for classification scheme items.

Example: Drosophilae OR: 5411


Classification Scheme Item Classification Scheme Item RelationshipsRelationships

– Classification_scheme_item_relationships are also not required to be recorded.

– Each classification_scheme_item_relationship requires exactly two distinct classification_scheme_items and they must both be recorded.

– Examples: Faculty is a specialization of Employee A Drug Order IS-A Pharmacy Order Component

Attributes:– csi_item_relationship_type_description

Examples: – Broader Than / Narrower Than– Hyponym / Synonym / Hypernym– Subclass / Superclass


Classification Classification Scheme RegionScheme Region

Classification_Scheme_Item_Relationship

csi_relationship_type_description [1..1] : String

Classification_Scheme

classification_scheme_administration_record [1..1] : Administration_Recordclassification_scheme_type_name [1..1] : String

Classification_Scheme_Item

csi_type_name [0..1] : Stringcsi_value [0..1] : String

0..n

0..n+association

0..n

classification_scheme_item_relationship

+association0..n

1..n

0..n

+containing1..n

+contained in0..n

classification_scheme_membership

Administration_Record

0..n

0..n

+classifying0..n

+classified_by0..n

administered_item_classification


Thank you for your attention and Thank you for your attention and hospitality!hospitality!

Reviews, experiences, issues and comments on 11179 Part 2 are very welcome.

Contact: [email protected]

Some Related Conferences: – KAWS Knowledge Acquisition Workshop– KRDB Knowledge Representation and Databases– ICCS International Conference on Conceptual Structures– FOIS Formal Ontology in Information Systems

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