What Constitutes Successful Format Conversion? Towards a Formalization of 'Intellectual Content'
DOI:
https://doi.org/10.2218/ijdc.v6i1.179Abstract
Recent work in the semantics of markup languages may offer a way to achieve more reliable results for format conversion, or at least a way to state the goal more explicitly. In the work discussed, the meaning of markup in a document is taken as the set of things accepted as true because of the markup's presence, or equivalently, as the set of inferences licensed by the markup in the document. It is possible, in principle, to apply a general semantic description of a markup vocabulary to documents encoded using that vocabulary and to generate a set of inferences (typically rather large, but finite) as a result. An ideal format conversion translating a digital object from one vocabulary to another, then, can be characterized as one which neither adds nor drops any licensed inferences; it is possible to check this equivalence explicitly for a given conversion of a digital object, and possible in principle (although probably beyond current capabilities in practice) to prove that a given transformation will, if given valid and semantically correct input, always produce output that is semantically equivalent to its input. This approach is directly applicable to the XML formats frequently used for scientific and other data, but it is also easily generalized from SGML/XML-based markup languages to digital formats in general; at a high level, it is equally applicable to document markup, to database exchanges, and to ad hoc formats for high-volume scientific data.Some obvious complications and technical difficulties arising from this approach are discussed, as are some important implications. In most real-world format conversions, the source and target formats differ at least somewhat in their ontology, either in the level of detail they cover or in the way they carve reality into classes; it is thus desirable not only to define what a perfect format conversion looks like, but to quantify the loss or distortion of information resulting from the conversion.
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Published
2011-03-08
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Research Papers
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