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These properties obey all the usual scoping rules. They can appear on dfdl:format annotations so as to be part of named format definitions or even put into lexical scope over a schema file.

The meaning of the values of these properties, and any constraints on those values, are essentially specified by the layer transform algorithm. For example: for layerLengthKind 'delimited' and the base64 layer transform, we expect that the layerTerminator must be a string, and this string has constraints beyond those we see in the the regular dfdl:terminator property. In particular for base64, we expect that layerTerminator cannot contain DFDL character entities of any kind. This makes it impossible, for example, for a base64 'delimited' layer to be terminated by a string containing ASCII NUL (character code 0), as there is no way to express this without use of DFDL character entities. These limitations must be enforced by the algorithms themselves.

To show these new annnotations at work, a named format that specifies a layering is created via

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A data layer is conceptually a stream of bytes. It can be an input layer for parsing, an output layer for unparsing.
Use of the term "stream" here is consistent with java's use of stream as in java.io.InputStream and java.io.OutputStream. These are sources and sinks of bytes. If one wants to decode characters from them you must do so by specifying the encoding explicitly.

A layer transform is a transformation that creates one layer of bytes from another. An underlying layer is encapsulated by a transformation to create an overlying layer.

When parsing, reading from the overlying layer causes reading of data from the underlying layer, which data is then transformed and becomes the bytes of the overlying layer returned from the read.

The layer properties apply to the underlying layer data and indicate how to identify its bounds/length, and if a layer transform is textual, what encoding is used to interpret the underlying bytes.

Some transformations are naturally binary bytes to bytes. Data decompress/compress are the typical example here. When parsing, the overlying layer's bytes are the result of decompression of the underlying layer's bytes.

If a transform requires text, then a dfdl:format encoding must be defined. For example, base64 is a transform that creates bytes from text. Hence, a layer encoding is needed to convert the underlying layer of bytes into text, then the base64 decoding occurs on that text, which produces the bytes of the overlying layer.

We think of some transforms as text-to-text. Line folding/unfolding is one such. Lines of text that are too long are wrapped by inserting a line-ending and either a space or tab. As a DFDL layer transform this line folding transform requires an encoding. The underlying bytes are decoded into characters according to the encoding. Those characters are divided into lines, and the line unfolding (for parsing) is done to create longer lines of data, the resulting data is then encoded from characters back into bytes using the same encoding.

(There may be opportunities to optimize/shortcut these transformations if the overlying layer is the data layer for an element with scannable text representation using the same character set encoding. The recoversion back to bytes, only to have to then decode bytes to characters of the same encoding again is overhead that can be avoided.)

DFDL can describe a mixture of character set decoding/encoding and binary value parsing/unparsing against the same underlying data representation; hence, the underlying data layer concept is always one of bytes.

(Note: bytes suffices even for mil-std-2045 which can hold a compressed VMF payload. This payload element is always byte aligned even in mil-std-2045, a very bit-oriented format. As of this writing we have no examples of layer transforms that require bit granularity; hence, this is a byte-oriented proposal.)
Daffodil parsing begins with a default standard data input stream. Unparsing begins with a default standard output stream. These are the ultimate underlying layer-oriented proposal.)

Daffodil parsing begins with a default standard data input stream. Unparsing begins with a default standard output stream. These are the ultimate underlying layer.

When parsing, left-over data is possible. The decoded layer data may contain extra data that is not consumed by the parse. It is a Parse Error if there is not enough data. Excess data is skipped/ignored. 

When unparsing, extra data may have to be created (padding/filling) to satisfy the layer unparsing algorithm. The DFDL schema for the xs:sequence content must create this padded/filled extra data. It is an Unparse Error if the data created when unparsing that is provided to the layer transform encoding algorithm does not satisfy its length requirements.

Examples using Data Layering

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