We wish to define a model for science linking traditional
research to education and which uses a model which
appears to be succesful from e-commerce. This can help
broaden the participation in and appreciation for science.

e-commerce is built around
a) End products like digital cameras that you might want
   to buy
b) Places such as Amazon and eopinions that compare
   products. Other places that list and otherwise
   compile information about products.
c) Places like Froogle and pricescan that collect all
   the different places you can buy and compare them.
   Prices and reliability indicators can be given.
d) Places where you buy products with associated
   catalogs, purchase and shipping units.
   
Now to e-CommunityScience:
Imagine a world full of sensors producing science data.
Assume all sensors are enabled as Web (Grid) Services
These sensors could be traditional pieces of hardware
(seismometers, GPS Satellites, Weather, Video cameras,
accelerators ...) or the papers, Blogs and Wikis that
can be thought of as the "Web Service Interface to
Brain waves)

Now the products in science are a mix of "not so
controversial real things" (the observed data)
and ideas/deductions.
We assume all products are generated by some sort of workflow
linking data to simulations to more data to deductions etc.
Just as in e-commerce, a given set of "facts" can have
many different organizations/people generating deductions.
We assume as in e-commerce, that we have other Web services
that collect related "scientific deductions" and presented
in a way you can sort in various ways. "Vendors" of "deductions"
could be rated in ways you choose
	By number and quality of PhD's in team
	Religuous correctness
	Type of organization etc.

End users are responsible for choosing scientific results
according to criteria they feel comfortable with. In particular
the current scientific methodology with roughly similar models
for evaluation of "vendors" can thrive.
The advantage of this approach is that it documents method of
selection of data and ideas and most importantly it allows
for a bigger net to catch ideas. Maybe most good results will
come from traditional sources but community science will
allow all to be potential participants.

For example, consider the current tragedy in Asia and suppose
(as probably isn't the case now) that relevant seismic
sensors are set up as Web Services. Then naively many different
groups would be to apply different approaches and their
results can in real time be collated and made available
to those worried about Tsunamis. There need not be just one
system but multiple approaches; thus even if Tsunami occurs
when key people in one organization are not available, those
in another time zone could come up with the needed analysis.

This suggests that Science Grids be built in a certain fashion
where at each stage of a possible science ideaflow or workflow
one sets up a framework that allows not only all people but all
resources to be harnessed i.e. we support both HPCC simulations
but also simulations on a P2P network in somebody's home.

This approach seems to be an attractive way to bring research
both into K-12 education and to communities that today do not
have a rich scientific infrastructure and expertise.
One could help both education and research disadvantaged
organizations by linking them to the now transparent 
traditional enterprise and by providing resources that
enabled their participation in it i.e. providing the needed
computing cycles for a local Tribal College to develop
custom agriculture models linked to the "traditional
enterprises environment, weather and climate data"