57 Key Points in Chapter Eight

What is classification?

Classification is the systematic assignment of resources to a system of intentional categories, often institutional ones.

(See “Introduction”)

What is a classification system?

A classification system is foremost a specification for the logical arrangement of resources because there are usually many possible and often arbitrary mappings of logical locations to physical ones.

(See “Classification vs. Physical Arrangement”)

How does classification affect the potential interactions in an organizing system?

A classification creates structure in the organizing system that increases the variety and capability of the interactions it can support.

(See “Classifications Support Interactions”)

Why are classifications always biased in some way?

Classifications are always biased by the purposes, experiences, professions, politics, values, and other characteristics and preferences of the people making them.

(See “Classification Is Biased”)

According to Friedman and Nissenbaum, what are the three types of bias in technical systems?

Three types of bias in technical systems are pre-existing, technical, and emergent bias.

(See “Classification Is Biased”)

What are enumerative classification schemes?

Classification schemes in which all possible categories to which resources can be assigned are defined explicitly are called enumerative.

(See “Classification Schemes”)

What is a taxonomic classification scheme?

When multiple resource properties are considered in a fixed sequence, each property creates another level in the system of categories and the classification scheme is hierarchical or taxonomic.

(See “Classification Schemes”)

What is the relationship between classification and standardization?

Classification and standardization are not identical, but they are closely related. Some classifications become standards, and some standards define new classifications.

(See “Classification and Standardization”)

What is a standard?

A standard is a published specification that is developed and maintained by consensus of all the relevant stakeholders in some domain by following a defined and transparent process.

(See “Specifications vs. Standards”)

Why are standard semantics important?

Standard semantics are especially important in industries or markets that have significant network effects where the value of a product depends on the number of interoperable or compatible products.

(See “Institutional Semantics”)

What is literary warrant?

The principle of literary warrant holds that a classification must be based only on the specific resources that are being classified.

(See “Principles Embodied in the Classification Scheme”)

What is the uniqueness principle?

The uniqueness principle means the categories in a classification scheme are mutually exclusive. Thus, when a logical concept is assigned to a particular category, it cannot simultaneously be assigned to another category.

(See “Principles for Assigning Resources to Categories”)

How is the uniqueness principle followed when resources do not clearly fit in a single category?

The general solution to satisfying the uniqueness principle in library classifications when resources do not clearly fit in a single category is to invent and follow a detailed set of often-arbitrary rules.

(See “Principles for Assigning Resources to Categories”)

What motivates category change?

Categories sometimes change slowly, but they can also change quickly and radically as a result of technological, process, or geopolitical innovation or events.

(See “Principles for Maintaining the Classification over Time”)

What is the relationship among flexibility, extensibility and hospitality in a classification system?

Flexibility, extensibility, and hospitality are synonyms for the degree to which the classification can accommodate new resources.

(See “Principles for Maintaining the Classification over Time”)

What distinguishes bibliographic classification?

Bibliographic classification is distinctive because of a legacy of physical arrangement and its scale and complexity.

(See “Bibliographic Classification”)

What distinguishes faceted classification systems?

Faceted classification systems enumerate all the categories needed to assign resources appropriately, but instead of combining them in advance in a fixed hierarchy, they are applied only if they are needed to sort resources with a particular combination of properties.

(See “Faceted Classification”)

What is orthogonality in a faceted classification system?

Facets should be independent dimensions, so a resource can have values of all of them while only having one value on each of them.

(See “Design Principles and Pragmatics”)

What is semantic balance in a faceted classification system?

Top-level facets should be the properties that best differentiate the resources in the classification domain. The values should be of equal semantic scope so that resources are distributed among the subcategories. Subfacets of “Cookware” like “Sauciers and Saucepans” and “Roasters and Brasiers” are semantically balanced as they are both named and grouped by cooking activity.

(See “Design Principles and Pragmatics”)

What is scalability in a faceted classification system?

Facet values must accommodate potential additions to the set of instances. Including an “Other” value is an easy way to ensure that a facet is flexible and hospitable to new instances, but it not desirable if all new instances will be assigned that value.

(See “Design Principles and Pragmatics”)

What is the relationship between classification and tagging?

Most tagging seems insufficiently principled to be considered classification, except when tags are treated as category labels or when decisions that make tagging more systematic turn a set of tags into a tagsonomy.

(See “Classification vs. Tagging”)

What is a taskonomy?

A task or activity-based classification system is called a taskonomy.

(See “Classification by Activity Structure”)

What is the relationship between supervised learning and classification?

Supervised learning techniques start with a designed classification scheme and then train computers to assign new resources to the categories.

(See “Computational Classification”)