encoding pattern

Abstraction.

Data that stands for something else.

Any data element.

Hide complexity and irrelevant details.

One must define a mapping between each of the elements to be encoded and their particular encoding forms. The definition can make use of a schema.

• Unicode defines which characters exist and how to express them.
• The bit sequence 111000101010000010100001 in bytes encodes the sequence E2 A0 A1 in UTF-8 encodes the Codepoint U+2821 in Unicode 3.0 encodes the character BRAILLE PATTERN DOTS-16 in Swedish Braille encodes the character Á.
• Markup languages encode characteristics of text elements, for instance <b>...</b>, or **...** for bold.
• MARCXML encodes MARC21 in XML.
• APIs abstract from internal data expressions (for instance SQL) to public, encoded form (for instance in JSON or XML).
• Virtual file systems abstract from different file system access methods.
• Encoding allows mapping between entities and connections and between objects and documents by reification, objectification, and stringification.
• Different serialization forms of RDF define encodings of RDF graphs.
• When a specification of some data format talks about a relation between syntax and semantic, it usually refers to an encoding.

• An encodings is an arbitrary result of social convention: one could modify it (for instance replace angle brackets by square brackets in all specifications and instances of XML) but actual changes are difficult.
• Encodings can also add redundancy.
• The existence and use of an encoding does not ensure that complexity and details are actually hidden.
• Most encoded data elements are encodings by their part, leading to a chain of encodings (unlimited semiosis).
• Encodings are not always one-to-one or reversible at all.
• Encodings only translate from one form of data to another, but the selection of a particular encoding can also be relevant data.
• Any data structuring language can encode any other language by introducing additional rules or constraints, so the particular encoding system may not add any value.

• Atomicity does also aim at reducing complexity.
• An encoding can also be used as specification (schema) and as normalization.
• Embedding is an alternative to encoding if the relation between data elements more depends on its actual context.
• Encoding seems to bridge the semiotic gap between signifier (encoding form) and signified (encoded data element). The common view of encodings as ‘semantic’, however, hides the fact that encodings must be accompanied by the label pattern to make sense.

• An encoding implies a set of identifier but the latter does not include the idea of expressing something at another level.
• Given a full encoding, the referent can automatically be determined (derivation).

Normalization implies encoding.