I'm looking for a specific axis-based data model, that I cannot find anymore.

The paper described a new way to model data. The model was based on
linking cells of data to each other by placing them on a certain axis
in a n-dimensional space. The link was always bi-directional so that
moving forward on an axis and moving backwards always brought you to
the same atom. Visualization of the model was a 2-D space where you
could map any of the axises to either the horizontal or the vertical
and rotate through the n-dimensional space.

There was atleast a Java implementation of the model, which had a
pastel shaded GUI, where data atoms zoomed closer and further when you
travelled the axis. The software was hard to use since all the
documentation and even the code for it was contained inside the model
itself.

There was also talk of a wrist-watch style implementation for the
idea, since you can express a great deal of things within a very
simple small display and a few input buttons.

I would love to locate the website describing this thing, the
speculations on the wrist-watch future, the Java software that
implemented and any research papers that I seem to recall that were
published. All of it was accessible over the web some 4 years ago.

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Clarification of Question by hadaka-ga on 04 Jan 2005 13:58 PST

Additional note about the model - all the different axis' were named
and more could be created on the fly. I think it had basic 'x' and 'y'
axis, then it had 'parent-child' axis, 'sibling' axis and then any
number of custom axis on the data.

Perhaps you are looking for a "cubed" data model. Although I am not
very well versed in cubed data models, this sounds to me like what you
are asking. I have done a number of Google searches on this but
unfortunately none have turned up any useful information. There are
most likely books and seminars on Data Mining and Data Analysis that
would explain this type of data model.

Well, I googled a bit on a cubed data model, didn't find much - but I
doubt that is it. Doesn't sound familiar at all and didn't look
familiar either.