  Based on direct integrals, a framework allowing to integrate a parametrised
family of reproducing kernels with respect to some measure on the parameter
space is developed. By pointwise integration, one obtains again a reproducing
kernel whose corresponding Hilbert space is given as the image of the direct
integral of the individual Hilbert spaces under the summation operator. This
generalises the well-known results for finite sums of reproducing kernels;
however, many more special cases are subsumed under this approach: so-called
Mercer kernels obtained through series expansions; kernels generated by
integral transforms; mixtures of positive definite functions; and in particular
scale-mixtures of radial basis functions. This opens new vistas into known
results, e.g. generalising the Kramer sampling theorem; it also offers
interesting connections between measurements and integral transforms, e.g.
allowing to apply the representer theorem in certain inverse problems, or
bounding the pointwise error in the image domain when observing the pre-image
under an integral transform.
