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I would expect most data XML to be approx. power law too, as you are have more nested elements under each element (in the simplest case: db:1, table:t, row:t*(rows per table), field:rows*(f=fields per table)), and typically t and f are small (say 7), but the number of rows is large, so for ~n elements root:1, level1: ~7, level 2:n/7, level3:n. So perfect power law for n~=350. If the tag names for fields differ, then the frequency of each tag ends up more evenly spread out between tags on the same level, but the cumulative distribution should still be approximatly a power law between levels.
For more structured data then similar distributions can be seen- for each element that is a container, there will be a few properties, for each property that is multivalued, many child elements. Mixed text abbreviates away some of the multivalued property tags, but still the container-contained 1:many relationship should hold.
Doing a quick count on two data oriented XML files of the same data sets (mtbf of a fuel system)- one derived straight from a database, the other from an XMI instance of the same data (which uses attributes instead of nesting elements for some properties)- give the frequencies, which look similar:
XMI data (single value properties as attributes)
1,1,1,1,1,4,4,5,5,8,10,14,16,18,18,19,21,22,24,29,51,57,59,59,64,64,83,94,95,123,125,148,190,210,242,277,447,
XML data (properties as child elements, elements named after properties)
1,1,1,1,1,1,1,1,1,1,2,2,4,4,4,4,5,5,5,6,7,8,9,10,14,16,18,18,19,21,22,24,24,31,51,57,59,64,64,64,64,83,83,94,95,95,116,116,116,116,120,123,123,125,134,147,210,211,238,242,277,385,447,646,
And for a different data set (XMI model for an application):
1,1,1,1,1,1,1,1,11,14,14,14,30,30,30,43,74,74,101,117,132,148,148,169,169,447,447,595,595,595,652,680,
Pete
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