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<DIV dir=ltr align=left><FONT color=#0000ff size=2 face=Arial><SPAN
class=518225508-13062010>What you're asking for would certainly be nice!
But I was aiming more for what you described as "an improvement". Baby steps....
:-)</SPAN></FONT></DIV>
<DIV dir=ltr align=left><FONT color=#0000ff size=2 face=Arial><SPAN
class=518225508-13062010></SPAN></FONT> </DIV>
<DIV dir=ltr align=left><FONT color=#0000ff size=2 face=Arial><SPAN
class=518225508-13062010>Seriously, though -- I agree taxonomists have failed to
be sufficiently explicit in their writings over the centuries to provide the raw
material for machine-generated reasoning and inferencing through the content of
their documents. However, I'm not so sure they have failed to provide
sufficient information to allow for (mostly) reliable and accurate human- (or at
least taxonomist-) generated reasoning and inferencing. That's why I think
a key aspect of all of this -- especially for legacy content -- is third-party
assertions. I don't think it's true that "most" species descriptions
result in persons 1&2 assinging a given specimen to two separate
concepts. But certainly there are enough to represent a non-trivial
problem.</SPAN></FONT></DIV>
<DIV dir=ltr align=left><FONT color=#0000ff size=2 face=Arial><SPAN
class=518225508-13062010></SPAN></FONT> </DIV>
<DIV dir=ltr align=left><FONT color=#0000ff size=2 face=Arial><SPAN
class=518225508-13062010>Rich</SPAN></FONT></DIV><BR>
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<FONT size=2 face=Tahoma><B>From:</B> Peter DeVries
[mailto:pete.devries@gmail.com] <BR><B>Sent:</B> Saturday, June 12, 2010 7:24
PM<BR><B>To:</B> Richard Pyle<BR><B>Cc:</B> David Remsen (GBIF);
tdwg-content@lists.tdwg.org; Kevin Richards; Jerry Cooper; dmozzherin; David
Patterson<BR><B>Subject:</B> Re: [tdwg-content] Name is species concept
thinking<BR></FONT><BR></DIV>
<DIV></DIV>I think that the problem is that most species descriptions are
written a way that person1 interprets specimenA as conceptB and person2
interprets specimenA and ConceptC.
<DIV><FONT color=#0000ff size=2 face=Arial></FONT><BR></DIV>
<DIV>This needs to be made more scientific so that one can test what
proportions of specimens actually conform to the description (concept).</DIV>
<DIV><FONT color=#0000ff size=2 face=Arial></FONT><BR></DIV>
<DIV>These descriptions should be open, world readable and reference-able via
a URI.</DIV>
<DIV><FONT color=#0000ff size=2 face=Arial></FONT><BR></DIV>
<DIV>Respectfully,</DIV>
<DIV><FONT color=#0000ff size=2 face=Arial></FONT><BR></DIV>
<DIV>- Pete</DIV>
<DIV><FONT color=#0000ff size=2 face=Arial></FONT><BR></DIV>
<DIV>** There also seems to be mismatch between the concept the human
identifier choose (often via a key) and the species description (concept) to
which you are saying their data applies.</DIV>
<DIV><FONT color=#0000ff size=2 face=Arial></FONT><BR></DIV>
<DIV><FONT color=#0000ff size=2 face=Arial></FONT><BR>
<DIV class=gmail_quote>On Sat, Jun 12, 2010 at 7:50 PM, Richard Pyle <SPAN
dir=ltr><<A
href="mailto:deepreef@bishopmuseum.org">deepreef@bishopmuseum.org</A>></SPAN>
wrote:<BR>
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<DIV class=im><FONT color=#0000ff size=2 face=Arial></FONT><BR>> That
said modeling relationships between taxonomic publications where<BR>> the
authors actually read the original species description, reviewed<BR>> the
type specimens, and thought about the actual species conscription
is<BR>appropriate.<BR><BR></DIV>
<DIV class=im>This is the sort of things the Meta-Authorities would take
into account when<BR>selecting a "follow-this-treatment" Usage-Instance for
the preferred<BR>treatment of a name.<BR><BR><BR></DIV>
<DIV class=im>> Also consider that a large proportion of specimens are
misidentified,<BR>> and it occurs to me that modeling things like species
occurrences as<BR>> if they are Puma concolor (Linnaeus, 1771) sensu
stricto is probably<BR>> not appropriate. At best they are something like
(Felis concolor /<BR>> Puma concolor) with some significant level of
error.<BR><BR></DIV>
<DIV class=im>GNA can't helpw ith that directly -- but it can help
indirectly. Imagine a<BR>service that takes ever specimen in a given
collection's database, and runs<BR>it against a mapping service as I
described in the previous message. I can<BR>easily imagine a GIS-based
algorithm that finds "outliers" -- that is<BR>occurrence records that appear
to be outside the distribution based on the<BR>occurrence records from other
sources. A clver/robust such algorithm could<BR>probably even discern
whether the outlier likely represented a range<BR>extension (e.g.
poorly-known species, plausible extansion), vs. a<BR>misidentification
(e.g., well-known species and/or common<BR>misidentification).<BR><BR>This
would lead to a set of flagged records from the collection that might<BR>be
misidentified.<BR><BR>Rich<BR><BR><BR></DIV>_______________________________________________<BR>tdwg-content
mailing list<BR>
<DIV class=im><A
href="mailto:tdwg-content@lists.tdwg.org">tdwg-content@lists.tdwg.org</A><BR></DIV>
<DIV>
<DIV></DIV>
<DIV class=h5><A href="http://lists.tdwg.org/mailman/listinfo/tdwg-content"
target=_blank>http://lists.tdwg.org/mailman/listinfo/tdwg-content</A><BR></DIV></DIV></BLOCKQUOTE></DIV><BR><BR
clear=all><BR>--
<BR>----------------------------------------------------------------<BR>Pete
DeVries<BR>Department of Entomology<BR>University of Wisconsin -
Madison<BR>445 Russell Laboratories<BR>1630 Linden Drive<BR>Madison, WI
53706<BR>GeoSpecies Knowledge Base <BR>About the GeoSpecies Knowledge
Base<BR>------------------------------------------------------------<BR></DIV></BLOCKQUOTE></BODY></HTML>