88 lines
8.4 KiB
Plaintext
88 lines
8.4 KiB
Plaintext
%META:TOPICINFO{author="BobMorris" date="1187669695" format="1.1" version="1.3"}%
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%META:TOPICPARENT{name="TerminologyWorkingGroup"}%
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---+++Some Sample Definitions
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(by Kevin Thiele)
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%TABLE{tablerules="all"}%
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|*Source*| | | |K.R. Thiele||||||||||| |CBD| |Thomson 1991 (from GISP)| |GISP|
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|*Term*| | | |Alien| |Invasive| |Introduced| |Native| |Adventive| |Cryptogenic| |Alien| |Invasive| |Invasive|
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|Origin| | | | | | | | | | | | | | | | | | | | |
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| | |Outside polygon of interest| |Yes| |Yes| |Yes| | | |Yes| | | |Yes| |Yes| |Yes|
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| | |Inside polygon of interest| | | | | | | |Yes| | | | | | | | | | |
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| | |Not relevant| | | | | | | | | | | | | | | | | | |
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| | |Not known| | | | | | | | | | | |Yes| | | | | | |
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|Human agent in range change?| | | | | | | | | | | | | | | | | | | | |
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| | |Yes| |Yes| |Yes| | | | | |Yes| | | | | | | |Yes|
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| | |No| | | | | | | | | | | | | | | | | | |
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| | |Not relevant| | | | | |Yes| | | | | | | |Yes| |Yes| | |
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| | |Not known| | | | | | | | | | | |Yes| | | | | | |
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| | |Not applicable| | | | | |Yes| | | | | | | | | | | | |
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|Impact| | | | | | | | | | | | | | | | | | | | |
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| | |Has negative impact (at least sometimes)| | | | | | | | | | | | | | | | | | |
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| | |Does not have negative impact| | | | | | | | | | | | | | | | | | |
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| | |Not relevant| |Yes| |Yes| |Yes| |Yes| |Yes| |Yes| |Yes| |Yes| |Yes|
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| | |Not known| | | | | | | | | | | | | | | | | | |
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|Establishment| | | | | | | | | | | | | | | | | | | | |
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| | |Established| | | |Yes| | | |Yes| | | |Yes| | | |Yes| |Yes|
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| | |Not established| | | | | | | | | | | | | | | | | | |
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| | |Not relevant| |Yes| | | |Yes| | | |Yes| | | |Yes| | | | |
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| | |Not known| | | | | | | | | | | | | | | | | | |
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|Geographic Range| | | | | | | | | | | | | | | | | | | | |
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| | |Widespread and/or spreading| | | |Yes| | | | | | | | | | | |Yes| |Yes|
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| | |Not widespread, not spreading| | | | | | | | | |Yes| | | | | | | | |
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| | |Not relevant| |Yes| | | |Yes| |Yes| | | |Yes| |Yes| | | | |
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| | |Not known| | | | | | | | | | | | | | | | | | |
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|Ecological Range| | | | | | | | | | | | | | | | | | | | |
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| | |Restricted to human-modified habitats| | | | | | | | | | | | | | | | | | |
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| | |Occurs in natural habitats| | | |Yes| | | | | | | | | | | | | |Yes|
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| | |Not relevant| |Yes| | | |Yes| |Yes| |Yes| |Yes| |Yes| |Yes| | |
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| | |Not known| | | | | | | | | | | | | | | | | | |
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---
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---++ Commentary
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Main.BobMorris wrote this commentary on Kevin's scheme in email to Main.AnnieSimpson and Main.KevinThiele.
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Kevin's spreadsheet is a representation of the first part of an _ontology_, namely the terminology. It's enough for humans, but machines
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usually need a little more to make good use of the ontology in deciding whether two databases use of a term are comparable for various purposes.
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Nevertheless, specialists could and should start with it because it is well thought out, easy to understand, and _at least_ as much as will
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ultimately be needed to resolve terminological differences between databases. Note that there are in fact four ontologies illustrated here: "K.R. Thiele", "CBD" , "Thomson 1991 (from GISP)" and "GISP". The point of Kevin's scheme is to make them comparable, as much as possible.
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His spreadsheet expresses "concepts" (e.g. 'invasive', 'alien', etc.), by telling the values they have for a small set of _properties_ ('Origin',
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'Impact', ...). For each property, there are a small set of possible _values_ to be used in these descriptions. Kevin's hope, which is probably
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very reasonable, is that with enough discussion, the discussants will agree that a small list of properties and values are expressive enough
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that most data providers can express the list of concepts coded in their own databases using just those properties and values the community
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agrees upon. Thus,rather than requiring the community of data providers (and consumers) to agree on a a single set of concepts, they instead
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agree on a set of terms that are used to _express_ concepts. In turn, application writers can decide for themselves how to rationalize comparisons of
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those concepts. I might write an application that enshrines a notion like "If two concepts agree on the majority of their property-value
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pairs, the program will treat them as the same". You might write an application that is more conservative and enshrines a requirement that
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two concepts must agree on 80% of their property-value pairs before considering them the same concept. Depending on the ultimate
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representation of these property-value lists, more sophisticated machine reasoning is possible than just conclusions of the form "For my purposes
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I can assume that CBD 'invasive' is equivalent to Thiele 'alien'+'invasive'".
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I understand that Kevin believes his property-value terms are a start, not an end, for discussion among the specialists and other interested
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parties, but regardless of this there are a few technical issues about how and where to represent such ontologies that the biologists shouldn't
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take a position about. In particular, there are arguments about whether the property-value terms belong in the schema or in some external document, and
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whether particular concept lists (the "definitions part of a database") belong in the data to be exchanged or in external documents. Those
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debates should not hinder specialists from discussing Kevin's notions and initially representing them in a spreadsheet as he has. The most
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important hidden technical issue is the extent to which proliferating terms also proliferates computation time unacceptably. What one desires is that if
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the terminology is increased N-fold, the time that applications need to compare data from different databases increases at most N-fold. Alas, it
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is easy in the ontology game for proliferation of terminology to become exponential in computation. For example, 10 times as many terms and
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concepts could lead not to 10 times as much computation, but 2 to the 10th power---1024 times as much computation. So there will always be a
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tension between adequacy of expression and small size---the two central disiderata of ontologies. There is a little bit of mathematical ontology
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theory that allows one to tell whether you are in this exponential situation, but I have the impression that for the few interesting
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ontologies coded in other ecology projects, the situation is, sadly, exponential and the advice is to try to limit terminology size if possible.
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The good news about all this is that it is a well explored and very current topic (it is presently high on the radar of the TDWG
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Architecture Group (TAG), and also of the GBIF Data Access and Data Integration (DADI) group, which are debating various standards to adopt
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for ontology. The bad news is that ontology tools are very sophisticated, but not very suitable for other than those who make a
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living crafting ontologies. The challenge to the GISIN technical group will be to make a representation that is nimble enough to get somethng
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going in a short timeframe, yet limber enough to slip out and replace if TDWG decides on standards for ontologies. I'm pretty sure this is
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possible if we find that some large fraction of the target databases can get along with ontologies that are, oh, say, significantly smaller than
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the databases themselves, and significantly fewer in number than the number of databases!
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In summary, my opinion is that initially, people should not be debating the concepts ("Invasive", "alien", ...) yet , but rather whether the primitive properties and values Kevin provides are powerful enough to express most of the concepts represented by the databases whose data would form part of GISIN.
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An interesting document for that discussion might also be the [[http://www.mnla.com/pdf/invasive/MIPAG_final_050325_rev.pdf][Massachusetts Criteria for Evaluating Non-Native Plant Species for Invasiveness]] pointed out by Main.JenniferForman, who will shortly post some other things that comprise what amount to ontologies.
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-- Main.BobMorris - 15 Mar 2006 |