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ISBN represented as EAN-13 bar code showing both human-readable and machine-readable data. In computing, a human-readable medium or human-readable format is any encoding of data or information that can be naturally read by humans, resulting in human-readable data. It is often encoded as ASCII or Unicode text, rather than as binary data.
It defines a set of rules for encoding documents in a format that is both human-readable and machine-readable. The World Wide Web Consortium's XML 1.0 Specification [3] of 1998 [4] and several other related specifications [5] —all of them free open standards—define XML. [6]
The decision to use any one encoding may depend on the language used for the documents, or the locale that is the source of the document, or the purpose of the document. Text may be ambiguous as to what encoding it is in, for instance pure ASCII text is valid ASCII or ISO-8859-1 or CP1252 or UTF-8. "Tags" may indicate a document encoding, but ...
Punched tape with the word "Wikipedia" encoded in ASCII.Presence and absence of a hole represents 1 and 0, respectively; for example, W is encoded as 1010111.. Character encoding is the process of assigning numbers to graphical characters, especially the written characters of human language, allowing them to be stored, transmitted, and transformed using computers. [1]
The Text Encoding Initiative (TEI) is a text-centric community of practice in the academic field of digital humanities, operating continuously since the 1980s. The community currently runs a mailing list, meetings and conference series, and maintains the TEI technical standard , a journal , [ 1 ] a wiki , a GitHub repository and a toolchain .
A binary-to-text encoding is encoding of data in plain text. More precisely, it is an encoding of binary data in a sequence of printable characters . These encodings are necessary for transmission of data when the communication channel does not allow binary data (such as email or NNTP ) or is not 8-bit clean .
Machine-readable data must be structured data. [1]Attempts to create machine-readable data occurred as early as the 1960s. At the same time that seminal developments in machine-reading and natural-language processing were releasing (like Weizenbaum's ELIZA), people were anticipating the success of machine-readable functionality and attempting to create machine-readable documents.
Document-oriented databases have been developed for storing, retrieving, and managing document-oriented information, also known as semi-structured data. Extensible Markup Language is a World Wide Web Consortium Recommendation setting forth rules for encoding documents in a format that is both human-readable and machine