What you're asking for would certainly be nice! But I was aiming more for what you described as "an improvement". Baby steps.... :-)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.Rich
From: Peter DeVries [mailto:pete.devries@gmail.com]Sent: Saturday, June 12, 2010 7:24 PM
To: Richard Pyle
Cc: David Remsen (GBIF); tdwg-content@lists.tdwg.org; Kevin Richards; Jerry Cooper; dmozzherin; David Patterson
Subject: Re: [tdwg-content] Name is species concept thinkingI 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.This needs to be made more scientific so that one can test what proportions of specimens actually conform to the description (concept).These descriptions should be open, world readable and reference-able via a URI.Respectfully,- Pete** 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.
On Sat, Jun 12, 2010 at 7:50 PM, Richard Pyle <deepreef@bishopmuseum.org> wrote:
> That said modeling relationships between taxonomic publications where
> the authors actually read the original species description, reviewed
> the type specimens, and thought about the actual species conscription is
appropriate.This is the sort of things the Meta-Authorities would take into account when
selecting a "follow-this-treatment" Usage-Instance for the preferred
treatment of a name.> Also consider that a large proportion of specimens are misidentified,
> and it occurs to me that modeling things like species occurrences as
> if they are Puma concolor (Linnaeus, 1771) sensu stricto is probably
> not appropriate. At best they are something like (Felis concolor /
> Puma concolor) with some significant level of error.GNA can't helpw ith that directly -- but it can help indirectly. Imagine a_______________________________________________
service that takes ever specimen in a given collection's database, and runs
it against a mapping service as I described in the previous message. I can
easily imagine a GIS-based algorithm that finds "outliers" -- that is
occurrence records that appear to be outside the distribution based on the
occurrence records from other sources. A clver/robust such algorithm could
probably even discern whether the outlier likely represented a range
extension (e.g. poorly-known species, plausible extansion), vs. a
misidentification (e.g., well-known species and/or common
misidentification).
This would lead to a set of flagged records from the collection that might
be misidentified.
Rich
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Pete DeVries
Department of Entomology
University of Wisconsin - Madison
445 Russell Laboratories
1630 Linden Drive
Madison, WI 53706
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