Data exchange

Source: Wikipedia, the free encyclopedia.

Data exchange is the process of taking data structured under a source schema and transforming it into a target schema, so that the target data is an accurate representation of the source data.[1] Data exchange allows data to be shared between different computer programs.

It 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 the constraints. Conversely, there may be numerous ways to transform the instance (possibly infinitely many), in which case a "best" choice of solutions has to be identified and justified.

Single-domain data exchange

In some domains, a few dozen different source and target schema (proprietary data formats) may exist. An "exchange" or "interchange format" is often developed for a single domain, and then necessary routines (mappings) are written to (indirectly) transform/translate each and every source schema to each and every target schema by using the interchange format as an intermediate step.[2] That requires a lot less work than writing and debugging the hundreds of different routines that would be required to directly translate each and every source schema directly to each and every target schema.

Examples of these transformative interchange formats include:

Data exchange languages

A data interchange (or exchange) language/format is a language that is domain-independent and can be used for data from any kind of discipline.[9] They have "evolved from being markup and display-oriented to further support the encoding of metadata that describes the structural attributes of the information."[10]

Practice has shown that certain types of

parsers, schema validators, and transformation tools.[citation needed
]

Popular languages used for data exchange

The following is a partial list of popular generic languages used for data exchange in multiple domains.


Name/Abbreviation Schemas Flexible Semantic verification Dictionary Information Model Synonyms and homonyms Dialecting Web standard Transformations Lightweight Human readable Compatibility
RDF Yes[1] Yes Yes Yes Yes Yes Yes Yes Yes Yes Partial Subset of
Semantic web
XML Yes[2] Yes No No No No Yes Yes Yes No Yes subset of
SGML, HTML
Atom
Yes Un­known Un­known Un­known No Un­known Yes Yes Yes No No XML dialect
JSON No Un­known Un­known Un­known No Un­known No Yes No Yes Yes subset of YAML
YAML No[3] Un­known Un­known Un­known No Un­known No No No[3] Yes Yes[4] superset of JSON
REBOL
Yes[7] Yes No Yes No Yes Yes No Yes[7] Yes Yes[5]
Gellish Yes Yes Yes Yes[8] No Yes Yes ISO No Yes Partial[6] SQL, RDF/XML, OWL

Nomenclature

Notes:

  1. ^ RDF is a schema-flexible language.
  2. ^ The schema of XML contains a very limited grammar and vocabulary.
  3. ^ Available as an extension.
  4. ^ In the default format, not the compact syntax.
  5. ^ The syntax is fairly simple (the language was designed to be human-readable); the dialects may require domain knowledge.
  6. ^ The standardized fact types are denoted by standardized English phrases, which interpretation and use needs some training.
  7. Parse dialect
    is used to specify, validate, and transform dialects.
  8. ^ The English version includes a Gellish English Dictionary-Taxonomy that also includes standardized fact types (= kinds of relations).

XML for data exchange

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.[11]

YAML for data exchange

YAML is a language that was designed to be human-readable (and as such to be easy to edit with any standard text editor). Its 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.[13]

REBOL for data exchange

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, emails, 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.[14] REBOL was used as a source of inspiration for JSON.[15]

Gellish for data exchange

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 a combination of ISO 10303-221 (AP221) and ISO 15926.[16]

See also

References

  1. ^ A. Doan, A. Halevy, and Z. Ives. "Principles of data integration", Morgan Kaufmann,s 2012 pp. 276
  2. . Retrieved 25 May 2018.
  3. . Retrieved 25 May 2018.
  4. ^ Kalish, C.E.; Mayer, M.F. (November 1981). "DIF: A format for data exchange between application programs". BYTE Magazine: 174.
  5. ^ "About ODF". OpenDoc Society. Retrieved 25 May 2018.
  6. . Retrieved 25 May 2018.
  7. ^ "KML Reference". Google Inc. 21 January 2016. Retrieved 25 May 2018.
  8. . Retrieved 25 May 2018.
  9. ^ Billingsley, F.C. (1988). "General Data Interchange Language". ISPRS Archives. 27 (B3): 80–91. Retrieved 25 May 2018. The transformation routines will constitute a language and syntax which must be discipline and machine independent.
  10. ^ Nurseitov, N.; Paulson, M.; Reynolds, R.; Izurieta, C. (2009). "Comparison of JSON and XML Data Interchange Formats: A Case Study". Scenario: 157–162.
  11. ^ . Retrieved 25 May 2018.
  12. ^ "human-readable". Oxford Dictionaries. Oxford University Press. Archived from the original on May 30, 2018. Retrieved 29 May 2018.
  13. ^ Bendersky, E. (22 November 2008). "JSON is YAML, but YAML is not JSON". Eli Bendersky's website. Retrieved 29 May 2018.
  14. ^ Sassenrath, C. (2000). "The REBOL Scripting Language". Dr. Dobb's Journal. 25 (314): 64–8. Retrieved 29 May 2018.
  15. ^ Sassenrath, C. (13 December 2012). "On JSON and REBOL". REBOL.com. Retrieved 29 May 2018.
  16. ^ van Renssen, A.; Vermaas, P.E.; Zwart, S.D. (2007). "A Taxonomy of Functions in Gellish English". Proceedings from the International Conference on Engineering Design 2007: DS42_P_230. Retrieved 29 May 2018.