  Simple time-reversible systems can generate {\it irreversible} flows
satisfying the Second Law of Thermodynamics. Maps, and equivalent random walks,
can also do this. We study a pair of time-reversible Baker Maps, $N2$ and $N3$,
which generate dissipative{\it fractal} phase-space structures. Steadily
decreasing phase-space volumes correspond to the dissipation associated with
entropy production. Like three smooth reversible dissipative one-body
phase-space flows developed in the 1980s and 1990s our maps generate fractal
distributions, but in two dimensions rather than three, simplifying
visualization and analyses. The continuity equation, which quantifies
phase-volume loss, motivates study of the fractals' reduced ``information
dimensions'', which were approximated by Kaplan and Yorke in terms of
two-dimensional maps' two Lyapunov exponents. The maps studied here generate
fractal (fractional dimensional) distributions in their phase spaces. By
mapping uniformly dense grids of points, fractal dimensions can be determined
by ``area-wise'' mappings. Beginning with a uniform grid area-wise mapping of
the $N2$ Baker Map provides an information dimension of 1.78969. Alternatively,
as many as a trillion iterations, starting from an arbitrary point, gives a
smaller ``point-wise'' dimensionality, $1.741_5$. Neither of these precisely
determined estimates matches the Kaplan-Yorke conjecture value, 1.7337. In the
course of studying these three different approaches to information dimension we
developed random walk equivalents to both mappings, which greatly simplifies
analyses. We found that for the older $ N2$ Baker map the three approaches all
disagree with one another! We later discovered that for the newer $N3$ Baker
mapping the three approaches to information dimension, area-wise, point-wise
and Kaplan-Yorke, agree.
