response to "Some generic issues to consider"

Tue Apr 25 16:25:19 2000

A comment by Reed Lewis about

Some generic issues to consider

by Jonathan C. Matti

(a) can we really develop common science-language standards on a
continent-wide basis?

Maybe.  It is hard enough at the state level to get two geologists to agree. 
However, if we can agree on some common terms and some common categories
(types of tables) then progress will have been made.

(b) can we really do this at a level deeper than "granite versus basalt" or
"glacial versus deltaic" or "geologic contact versus fault", etc?

Maybe.  I prefer to keep it relatively simple. The Idaho Survey is most
interested in reaching out to new constituents, such as foresters interested
in tree nutrition.  We would like our data model to be flexible enough for
non-geologists to use, and we want to design it this way from the start.

(c) what role do regional geologic differences and geologic-mapping
traditions play in the development of science-language standards?

They play a significant role.  Also, differences occur WITHIN regions between
authors, and between terminology used on old maps versus new ones.

(d) should there be one single terminology standard, or multiple standards
linked by translators and equivalency tables?

We should strive for agreement on basic terms, particularly lithology terms,
but the difficulty comes with placing these terms in a hierarchy.  The IUGS
system works well for igneous rocks, but there are no universally accepted
hierarchies for sedimentary or metamorphic rocks.  Ideally, translators
would not be needed, but in reality, I think that is where this process will
end up.

(e) what kinds of scientific queries should be supported by standard
terminologies at the National, Regional, and Local levels, and should a
single science-language structure support each and all levels?

I am not sure what you are asking here.  A national standard can be
recommended.  It is up to the individual geologists to use it or ignore it.

(f) To what audience(s) will the data-model science language speak on behalf
of our various agencies?  Technical only?  Hybrid technical and
non-technical?  One language for technical, a second language for

Hybrid. The Idaho Survey version of the data model is aimed at both
geologists and non-geologists.  To prosper, and perhaps even to survive,
geologists need to get their map data out to non-traditional users.

(g) What does each map-producing agency expect to query (search for and
retrieve) from geologic-map data bases produced by the data model? (agency
point of view)

See 20 questions.

(h) What kind of geologic information will the typical geologist expect to
put INTO the data model and retrieve FROM it? (geologist point of view)

The main task for the geologist will be to compartmentalize the information
in the unit descriptions. See 20 questions for what he will get out of it.

(i) What kinds of interdisciplinary science should be incorporated into the
data model science language?  Or, put differently, how should the data model
be structured and populated to ensure its utility to the geophysics,
geo-engineering, earthquake, geochemical, and hydrogeologic communities?

Other disciplines should be able to use the data model to extract geologic
information.  Thus, we need to allow for simplification. Unfortunately, this
requires hierarchies, a significant stumbling block as mentioned above. We
don't need to incorporate any terminology from other disciplines; we have
trouble enough as it is.

(j) What kinds of feature-level locational-accuracy issues should be
addressed by our science language, as these bear on agency accountability?

The arcs or polygon boundaries need to have a qualitative estimate of
accuracy (e.g. approximate contact).  Scale is also key.

(k) What kinds of feature-level scientific-confidence issues should be
addressed by our science language, as these bear on agency accountability?

The best we can do here is have flags pop up with warnings for people not
familiar with how geologic maps are made.  Not really a language issue.

(l) What kinds of feature-level data-origination issues should be addressed
in our science language, as these bear on agency accountability?

Sources of arcs and points need to be tracked.

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