The Distributed Statistical Computing '99 conference
held in Vienna was the first occassion for those involved in
to meet face to face and discuss the project and its goals.
The following hopes to clarify the nature of the project
and explains each members (current) indvidual perspective.

For me the Omega project is an opportunity to experiment with
distributed algorithms for complex statistical calculations, such as
those involved in fitting linear and nonlinear mixed-effects models.
It also allows easy access to SQL databases and other common data
storage protocols. The use of Java as the implementation language and
the ability to incorporate compiled Java classes as top-level
Omega objects means that we can move from purely interactive use
to compiled classes very easily. I think this will be important in
many statistical computing uses. Finally, I am enthused about
developing freely-available (or ``open-source'') software. I have
benefitted tremendously from the GNU tools, from the Linux kernel,
from TeX and LaTeX, and from many other freely-available software
components. This is an opportunity to return something to the open
software community.

The Omega project is an opportunity to build a very flexible set of
software components from the ground up which can be used in all
aspects of ``computing with data''(see JMC). It will provide the
components needed for different styles of statistical environments
than can be created for different users and tasks such as a general
statistical environment, GUIs for specific statistical methods,
embedded scripting languages, etc. The form of the tools allows
extensibility in many different ways not possible in other systems.
This approach allows researchers to investigate new methodology, tools
and perspectives such as model fitting, web based reporting, parallel
and distributed algorithms, etc. based on the basic building blocks as
well as introducing entirely new components. Additionally, its use of
Java will allow us to explore and exploit facilities for distributing
new methodology (i.e. technology transfer) in interesting ways.