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Oh yeah, I forgot to say in the interest of defining acronyms used,
TDWG stands for "Biodiversity Information Standards". It supposedly
had grown beyond "Taxonomic Databases Working Group" and "focuses on
the development of standards for the exchange of
biological/biodiversity data." (<a class="moz-txt-link-freetext" href="http://www.tdwg.org/about-tdwg/">http://www.tdwg.org/about-tdwg/</a>). ;-)<br>
Steve.<br>
<br>
Steve Baskauf wrote:
<blockquote cite="mid:4DC132B8.3090908@vanderbilt.edu" type="cite">
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Thanks, Bob, for the examples. I will try to dig my way through them.
<br>
<br>
I don't want to give the impression that Darwin-SW was not intended to
facilitate any reasoning. That is, after all why it is called
"Darwin-SW" instead of "Darwin-data-markup". I know that Cam is quite
interested in the "semantic" end of it, and when he has Internet again
I hope he will chime in on this. I'm simply confessing what my primary
concern is (data markup). When we started working on the ontology, we
decided to make it as simple as possible while still trying to permit
every (or almost every) kind of class and relationship that was
discussed in the Oct/Nov discussion. The result was to have a single
class Occurrence whose instances are described by properties, not 1.7
million classes N#occurrence and so on for the other six classes in the
model. The intention was that DSW 1.0 would be constructed in such a
way that it could support the addition of more complex components (Cam
has actually marked the posted version at version 0.2 which means that
it is certainly subject to improvement) and possibly more complex
reasoning. But the more complex stuff was not put into the model at
the start because we wanted something that (hopefully) most people
could agree represents reality reasonably well (at least a TDWG form of
reality since it uses the structure of DwC as its basis) and hence it
would actually have the possibility of being used by more than two
people. <br>
<br>
I hope that people realize that I'm not making these comments to give
Pete a hard time or anything. I really am trying to understand the
relative benefits and problems of modeling on class of cat with many
properties vs. creating a class of cats for every property we care
about. Clearly Pete's interest is in Taxon Concepts in the sense that
he has defined them. OK, just to set up a straw man, let's say that I
am interested in geography more than taxonomy. So I define a class and
URI for every state and province in the world. I have no idea how many
of those there are, but I'll guess 400. Now I want to describe other
things in the biodiversity informatics world. So I mint classes
<a moz-do-not-send="true" class="moz-txt-link-freetext"
href="http://baskaufgeo.org/lod/ohio#occurrence">http://baskaufgeo.org/lod/ohio#occurrence</a>
for occurrences that happen
in Ohio, <a moz-do-not-send="true" class="moz-txt-link-freetext"
href="http://baskaufgeo.org/lod/swaziland#occurrence">http://baskaufgeo.org/lod/swaziland#occurrence</a>
for occurrences
that happen in Swaziland,
<a moz-do-not-send="true" class="moz-txt-link-freetext"
href="http://baskaufgeo.org/lod/tennessee#occurrence">http://baskaufgeo.org/lod/tennessee#occurrence</a>,
<a moz-do-not-send="true" class="moz-txt-link-freetext"
href="http://baskaufgeo.org/lod/ohio#taxon">http://baskaufgeo.org/lod/ohio#taxon</a>,
<a moz-do-not-send="true" class="moz-txt-link-freetext"
href="http://baskaufgeo.org/lod/swaziland#taxon">http://baskaufgeo.org/lod/swaziland#taxon</a>,
<a moz-do-not-send="true" class="moz-txt-link-freetext"
href="http://baskaufgeo.org/lod/tennessee#taxon">http://baskaufgeo.org/lod/tennessee#taxon</a>,
etc. etc. for all 400
state/provinces and all seven basic types of things in the biodiversity
domain. I can now do cool queries that involve geography. <br>
<br>
OK, maybe I'm somebody else and I love thinking about temporal
relationships. So I create
<a moz-do-not-send="true" class="moz-txt-link-freetext"
href="http://baskauf-time.org/lod/1959may#occurrence">http://baskauf-time.org/lod/1959may#occurrence</a>
for occurrences that
happen in May of 1959, <a moz-do-not-send="true"
class="moz-txt-link-freetext"
href="http://baskauf-time.org/lod/2005may#occurrence">http://baskauf-time.org/lod/2005may#occurrence</a>
for occurrences that happened in May of 2005, etc. Given a billion or
so years of life on earth, that would give me about 12 billion classes
for each of the six other basic kinds of things I want to model. I
could do all kinds of cool queries that involve time now. <br>
<br>
So which one of these three ontologies are we going to adopt? The
taxon based one? The time based one? The geography based one? Now we
are not just having to chose whether to model things as a single class
of cats whose instance have many color and reproductiveMethod
properties vs. many classes of cats each defined on the basis of its
color. We must decide whether it's better to have many classes of
colors each defined by the kind of animal that has that color, or many
kinds of reproductive systems, each with different kinds of animals,
etc. Where is it going to end and how could we agree on which system
to use? It seems to me that it would be better to have a class of
cats, a class of reproductive systems, etc. and connect their instances
with properties. <br>
<br>
Am I somehow thinking about this incorrectly?<br>
Steve<br>
<br>
Bob Morris wrote:
<blockquote
cite="mid:BANLkTimBPkOPFMRAGfpKWy6+tVY3qG6J=A@mail.gmail.com"
type="cite">
<pre wrap="">See, for example,
Mungall et al., “Integrating phenotype ontologies across multiple
species”, Genome
Biology 2010, 11:R2 doi:10.1186/gb-2010-11-1-r2)
Ward Blondé et al. "Reasoning with bio-ontologies: using relational
closure rules to enable practical querying", Bioinformatics (2011)
doi: 10.1093/bioinformatics/btr164
Calder, et al. "Machine Reasoning about Anomalous Sensor Data"
<a moz-do-not-send="true" class="moz-txt-link-freetext"
href="http://dx.doi.org/10.1016/j.ecoinf.2009.08.007">http://dx.doi.org/10.1016/j.ecoinf.2009.08.007</a> or in manuscript form
at <a moz-do-not-send="true" class="moz-txt-link-freetext"
href="http://efg.cs.umb.edu/pubs/SensorDataReasoning.pdf">http://efg.cs.umb.edu/pubs/SensorDataReasoning.pdf</a>
...
OK, so maybe these knowledge domains are all hypothesis-driven
sciences (i.e., sciences), and <whatever dsw is modelling> is not.
But that would be sad.
Bob
p.s. I had almost finished something else on this thread when Hilmar
beat me to the punch. But here's a slightly different expression of
his point:
It turns out that the differences between instances and classes is
mainly important in contexts in which you have declaimed interest,
namely reasoning. In the RDF/RDFS/OWL stack, enforcing a distinction
between classes and instances only occurs pretty high up in the stack,
when one desires an OWL variant that will offer guarantees that
reasoners will finish any inference they are asked to verify,
preferably in less than exponential time . I guess, but am not
certain, that even in an LOD context, if data are described with an
OWL ontology that is known to be intractable, e.g. not in OWL DL, that
it is possible to design SPARQL queries that will never complete. In
fact, I believe that even with tractable ontologies, there are SPARQL
queries that are fundamentally exponential in the number of variables.
p.p.s. Irrelevant, but equivalent, aside about mathematics. At the
turn of the 20th century, Whitehead and Russell tried (and failed) to
show that everything about numbers could be logically derived from an
axiomatic description of the natural numbers (i.e. non-negative
integers). It was later shown to be the case that you must include in
your logical foundations something deeper, namely the ability to have
sets that are elements of other sets (roughly, classes that are
individuals in other classes.). Without this, and starting only with
the natural numbers, you can logically derive all rational numbers
(fractions) and their arithmetic properties, and even all the
irrational numbers that are are the solutions of polynomial equations
with integer coefficients ("algebraic numbers") such as sqrt(2), and
even solutions of the polynomials that have coefficients that are
algebraic numbers. But without introducing the notion of the set of
subsets of a set, you cannot logically derive the all the interesting
transcendental numbers (i.e. those which are not the roots of
polynomials), such as e and pi. So if you love calculus, you better
not insist on distinguishing instances from classes. But if you are
content with polynomials, you can probably be ontologically sloppy.
Or, if you don't care about logical foundations of your science, you
can forget about the whole thing. :-)
On Tue, May 3, 2011 at 11:51 PM, Steve Baskauf
<a moz-do-not-send="true" class="moz-txt-link-rfc2396E"
href="mailto:steve.baskauf@vanderbilt.edu"><steve.baskauf@vanderbilt.edu></a> wrote:
</pre>
<blockquote type="cite">
<pre wrap="">[snip]
OK, so let's imagine that we mark up several million records of specimens,
tissue samples, and images as RDF. (We don't have to imagine very hard, I
think the BiSciCol group is planning to actually do this within the next
several months.) I would really like to hear from some of the people who
actually use "DL reasoners" (a group which certainly does not include me) to
know what it is that we could actually find out that would be useful about
that big data blob using reasoners. I have already confessed that my
primary concern is enabling data discovery, transfer, and aggregation using
GUIDs and RDF. I'm still somewhat of a "semantic web" skeptic as far as the
whole inferencing thing is concerned. Aside from inferring "duplicates",
I'm really wanting to know what else there is useful that could be reasoned
outside of the Taxon/TaxonConcept class. (I can imaging useful reasoning
being done about things in that class like the relationships among names,
concepts, parent taxa, etc. e.g. Rod Page's Biodiversity Informatics 3:1-15
article <a moz-do-not-send="true" class="moz-txt-link-freetext"
href="https://journals.ku.edu/index.php/jbi/article/view/25">https://journals.ku.edu/index.php/jbi/article/view/25</a>) I think this
(data markup priority vs. inferencing priority) is an important discussion
to have before the tdwg community can settle on some kind of consensus way
of turning database records into RDF, particularly if it is going to have a
big influence on the way the RDF model is set up. To me, there is a clear
and immediate need to be able to mark data up in a straightforward way. If
we can get the semantic part, too, that would be great but not at the
expense of data markup. I just was at a meeting of a bunch of herbarium
curators. They desperately need a way to implement GUIDs and aggregate data
and they need it now. I really don't think they care one whit about
inferencing. If we coalesce on a model that is great for doing cool things
with 10 records but which can't handle hundreds of thousands of records
easily and simply, then we are wasting our time. I don't think we need to
dither about this for another five years.
I would hate to have to draw an RDF graph of that model
I would as much hate to have to draw an RDF graph of 1.7 million instances.
The point being, in order to draw a graph of how someone models a domain you
don't draw a graph of the entire RDF triple store.
That was the point I was trying to make (I think).
Thanks for the clarification, Hilmar.
Steve
-hilmar
--
===========================================================
: Hilmar Lapp -:- Durham, NC -:- informatics.nescent.org :
===========================================================
--
Steven J. Baskauf, Ph.D., Senior Lecturer
Vanderbilt University Dept. of Biological Sciences
postal mail address:
VU Station B 351634
Nashville, TN 37235-1634, U.S.A.
delivery address:
2125 Stevenson Center
1161 21st Ave., S.
Nashville, TN 37235
office: 2128 Stevenson Center
phone: (615) 343-4582, fax: (615) 343-6707
<a moz-do-not-send="true" class="moz-txt-link-freetext"
href="http://bioimages.vanderbilt.edu">http://bioimages.vanderbilt.edu</a>
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</pre>
</blockquote>
<pre wrap=""><!---->
</pre>
</blockquote>
<br>
<pre class="moz-signature" cols="72">--
Steven J. Baskauf, Ph.D., Senior Lecturer
Vanderbilt University Dept. of Biological Sciences
postal mail address:
VU Station B 351634
Nashville, TN 37235-1634, U.S.A.
delivery address:
2125 Stevenson Center
1161 21st Ave., S.
Nashville, TN 37235
office: 2128 Stevenson Center
phone: (615) 343-4582, fax: (615) 343-6707
<a moz-do-not-send="true" class="moz-txt-link-freetext"
href="http://bioimages.vanderbilt.edu">http://bioimages.vanderbilt.edu</a>
</pre>
</blockquote>
<br>
<pre class="moz-signature" cols="72">--
Steven J. Baskauf, Ph.D., Senior Lecturer
Vanderbilt University Dept. of Biological Sciences
postal mail address:
VU Station B 351634
Nashville, TN 37235-1634, U.S.A.
delivery address:
2125 Stevenson Center
1161 21st Ave., S.
Nashville, TN 37235
office: 2128 Stevenson Center
phone: (615) 343-4582, fax: (615) 343-6707
<a class="moz-txt-link-freetext" href="http://bioimages.vanderbilt.edu">http://bioimages.vanderbilt.edu</a>
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