  Recent high precision experimental data from a variety of hadronic processes
opens new opportunities for determination of the collinear parton distribution
functions (PDFs) of the proton. In fact, the wealth of information from
experiments such as the Large Hadron Collider (LHC) and others, makes it
difficult to quickly assess the impact on the PDFs, short of performing
computationally expensive global fits. As an alternative, we explore new
methods for quantifying the potential impact of experimental data on the
extraction of proton PDFs. Our approach relies crucially on the correlation
between theory-data residuals and the PDFs themselves, as well as on a newly
defined quantity --- the sensitivity --- which represents an extension of the
correlation and reflects both PDF-driven and experimental uncertainties. This
approach is realized in a new, publicly available analysis package PDFSense,
which operates with these statistical measures to identify particularly
sensitive experiments, weigh their relative or potential impact on PDFs, and
visualize their detailed distributions in a space of the parton momentum
fraction x and factorization scale \mu. This tool offers a new means of
understanding the influence of individual measurements in existing fits, as
well as a predictive device for directing future fits toward the highest impact
data and assumptions.
