We created a set of volume limited samples taken from the 2dFGRS (Colless 2001) that contains about 250,000 galaxies with accurate redshifts, is relatively deep and is the richest in its kind so far. It is especially well suited for large-scale studies because the sky-to-sky variations, which have to be take into account, are well known. Volume limited samples are necessary when constructing a statistical meaningful sample. These samples are used to detect and quantify voids in between redshifts of z~0.05 to 0.2. Below we show a preliminary result of our detected void-size distribution in the 2dFGRS obtained from a single volume limited sample. One of the most striking features of the Large Scale Structure is its web-like appearance: most of the Matter appears to be situated in filamentary structures, that surround large under- dence regions called voids. Voids are a natural consequence of the standard ΛCDM paradigm: as the overdensity perturbations in the primordial density field collapse and form the filaments and clusters as the Universe evolves, the underdensiy perturbations will expand and cover up to 80% of the total volume. Although everybody seems to agree on what a void should look like, quantifying them is not straightforward. A number of different definitions of voids have been suggested so far: regions that have a density below some threshhold; regions that are empty of objects with masses/ luminocities larger than some value; regions enclosed by 'wall' galaxies, that have been linked together using an appropriate scale length. What remains unclear is whether these different definitions obtain the same class of objects, and what biases are introduced by their underlying assumptions. These should be known if one wants to study properties like size-distribution or the galaxy population inside these underdense regions. In our work we seek to clarify some of these issues using numerical and analytical theory of structure formation. To detect voids in a 3D-galaxy distribution, we use the voids finder, developed by Arbabi-Bidgoli and Müller (2002). This grid-based algorithm first finds the largest empty cubes, which are then extended, and has been successfully applied to the Las Campanas Survey. To understand the intrinsic biases due to the selection algorithm, we compare our void finder with that of Patiri et al. (2005). Their algorithm finds the maximal sphere in the galaxy distribution. A qualitative comparison of the largest voids detected shows that the positions are in very good agreement. Because our algorithm is more sensitive to asymmetries, we get larger effective radii by a factor 1.2 due to the extension of the void (shown below). The effective radii determined by the base cubes that we detected however are in very nice agreement with Patiri's result. This comparison already shows, that although different definitions used give qualitatively the same objects, one Sander von Benda-Beckmann (AIP) Above: The absolute magnitude vs. redshift plot shows two selected volume limited samples for the NGP and SGP regions taken from the 2dFGRS catalog. The black line indicates the cut-off for a homogeneous limiting apparent magnitude for the two samples. The two largest samples are shown. To get good statistics for the larger voids, we need an as large as possible volume, hence large redshift. Below: The void size distribution functions in redshift space for the volume limited sample SGP3 extracted from the 2dFGRS catalog. SGPcat3 was selected through: -2 h 12'0”≤ α ≤3 h 23'0”, -2 h 12'0”≤ δ ≤3 h 23'0”, M b ≥ , 0.14≤ z ≤0.2. We cannot directly compare this distribution with the figure on the right, because this sample has been selected based on the galaxy luminocity and the right figure based on DM halo mass. We plan to use semi-analytical models for galaxy evolution to compare and understand how these are related to each other.This way we will learn how galaxies evolve in underdense environments. Voids in Large Scale Surveys Cosmology Right: The void size distribution functions obtained from a DM-halo catalog of a 80 Mpc box with halos of masses M ≥ M. Shown are the voids obtained by our void finder and that of Patiri et al. (2005). Both void finders are grid-based and used a grid-size of 0.5 Mpc. For our results we show to characteristic sizes, the effective radius Rc defined by the base cube, and the effective radius Rs defined by the whole volume including the extension.