normalization pattern

Canonical form, equivalence, one-to-one.

Make equal data elements identical by choosing one preferred version, based on relevant distinctions only.

A set of data elements, one of them selected as normalized.

• Avoid ambiguity, redundancy and inconsistencies.
• Group multiple data elements with same characteristics.

• Avoid derivation and garbage in the data to be normalized.
• Define normalization rules in a schema.

• Database normalization is recommended to avoid redundancy and inconsistencies.
• Unicode defines several normalization forms (NFD, NFC, NFKD, NFKC).
• XML Schema Datatypes have a canonical lexical representation to establish a one-to-one mapping between value space and literal representations. For instance the boolean value false can be represented as 0 and as false but the latter is the canonical, normalized form.
• Approximate data types use a finite (or denumerable infinite) number of distinct values to represent an infinite number of values. The approximation normalizes the infinite set by mapping multiple values to one.
• Whitespace normalization replaces multiple and different whitespace characters by one simple whitespace character.
• An ISBN can have multiple forms (with or without hyphen, or space, as ISBN-10 or ISBN-13 etc.).

• Normalization depends on uniquely identifiable entities but an identifier or label is often missing.
• Normalization concentrates on the relevant aspects of a data element. It requires to define what variants are considered equivalent and what makes a difference. All these properties, however, may depend on context.
• Normalizing graph structures can be very hard both computationally and practically.
• Ordered values (numbers, coordinates…) can be treated as equal if they have a low distance, but they cannot be normalized because distance is not a transitive function.
• Despite its theoretical importance, for instance in database theory, normalization in practice is often applied incompletely or not at all.

• Normalization groups data elements based on sameness of their characteristic properties. More general methods of grouping are examples of the container pattern.
• Every normalization defines an identifier (the reverse does not apply).
• Normalization may also be virtual, resulting in the void pattern. For instance in some file systems file names are case insensitive but case preserving, so the normalized file name is not given directly.

Every normalization implies a form of encoding, as data elements can be encoded by the form they are normalized to. For instance XML documents are encoded by their document model, which gives a normalized form.