Data exchange is the process of taking data structured under a source schema and actually transforming it into data structured under a target schema, so that the target data is an accurate representation of the source data. Data exchange is similar to the related concept of data integration except that data is actually restructured (with possible loss of content) in data exchange. There may be no way to transform an instance given all of our constraints. Conversely, there may be numerous ways to transform the instance (possibly infinitely many), in which case we must identify and justify a "best" choice of solutions.
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A data exchange language is a language that is domain-independent and can be used for any kind of data. Its semantic expression capabilities and qualities are largely determined by comparison with the capabilities of natural languages. The term is also applied to any file format that can be read by more than one program, including proprietary formats such as Microsoft Office documents. However, a file format is not a real language as it lacks a grammar and vocabulary.
Practice has shown that certain types of formal languages are better suited for this task than others, since their specification is driven by a formal process instead of a particular software implementation needs. For example XML is a markup language that was designed to enable the creation of dialects (the definition of domain-specific sublanguages) and a popular choice now in particular on the internet. However, it does not contain domain specific dictionaries or fact types. Beneficial to a reliable data exchange is the availability of standard dictionaries-taxonomies and tools libraries such as parsers, schema validators and transformation tools.
The following is an incomplete list of popular generic languages used for data exchange in multiple domains.
| Schemas | Flexible | Semantic verification | Dictionary -Taxonomy | Synonyms and homonyms | Dialecting | Web standard | Transformations | Lightweight | Human readable | Compatibility | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| XML | Yes[1] | Yes | No | No | No | Yes | Yes | Yes | No | No | subset of SGML, HTML |
| Atom | Yes | Unknown | Unknown | Unknown | Unknown | Yes | Yes | Yes | No | No | XML dialect |
| JSON | No | Unknown | Unknown | Unknown | Unknown | No | Yes | No | Yes | No | subset of JavaScript |
| YAML | No[2] | Unknown | Unknown | Unknown | Unknown | No | No | No[2] | Yes | Yes[3] | superset of JSON |
| REBOL | Yes[6] | Yes | No | Yes | Yes | Yes | No | Yes[6] | Yes | Yes[4] | |
| Gellish | Yes | Yes | Yes | Yes[7] | Yes | Yes | ISO | No | Yes | Partial[5] | SQL, RDF/XML, OWL |
Nomenclature
Notes:
The popularity of XML for data exchange on the World Wide Web has several reasons. First of all, it is closely related to the preexisting standards Standard Generalized Markup Language (SGML) and Hypertext Markup Language (HTML), and as such a parser written to support these two languages can be easily extended to support XML as well. For example, XHTML has been defined as a format that is formal XML, but understood correctly by most (if not all) HTML parsers. This lead to quick adoption of XML support in web browsers and the toolchains used for generating web pages.
Actually a part of the JavaScript programming language, the JSON (JavaScript Object Notation) was split out into a low-level format for structured data exchange. While it was originally not designed for data exchange at all, it was discovered to be useful. In contrast to XML above, there exist no schema definition and no support for dialecting. The key benefits of this language are the low overhead (the amount of data needed for structuring) compared to XML and the similarly wide support: every web browser that has JavaScript support can also process JSON.
YAML is a language that was designed to be human-readable (and as such to be easy to edit with any standard text editor). It's notion often is similar to reStructuredText or a Wiki syntax, who also try to be readable both by humans and computers. YAML 1.2 also includes a shorthand notion that is compatible with JSON, and as such any JSON document is also valid YAML; this however does not hold the other way.
REBOL is a language that was designed to be human-readable and easy to edit using any standard text editor. To achieve that it uses a simple free-form syntax with minimal punctuation, and a rich set of datatypes. REBOL datatypes like URLs, e-mails, date and time values, tuples, strings, tags, etc. respect the common standards. REBOL is designed to not need any additional meta-language, being designed in a metacircular fashion. The metacircularity of the language is the reason why e.g. the Parse dialect used (not exclusively) for definitions and transformations of REBOL dialects is also itself a dialect of REBOL. REBOL was used as a source of inspiration by the designer of JSON.
Gellish English is a formalized subset of natural English, which includes a simple grammar and a large extensible English Dictionary-Taxonomy that defines the general and domain specific terminology (terms for concepts), whereas the concepts are arranged in a subtype-supertype hierarchy (a Taxonomy), which supports inheritance of knowledge and requirements. The Dictionary-Taxonomy also includes standardized fact types (also called relation types). The terms and relation types together can be used to create and interpret expressions of facts, knowledge, requirements and other information. Gellish can be used in combination with SQL, RDF/XML, OWL and various other meta-languages. The Gellish standard is being adopted as ISO 15926-11.