  When combining data from multiple sources, inconsistent data complicates the
production of a coherent result. In this paper, we introduce a new type of
constraints called edit rules under a partial key (EPKs). These constraints can
model inconsistencies both within and between sources, but in a loosely-coupled
matter. We show that we can adapt the well-known set cover methodology to the
setting of EPKs and this yields an efficient algorithm to find minimal cost
repairs of sources. This algorithm is implemented in a repair engine called
Parker. Empirical results show that Parker is several orders of magnitude
faster than state-of-the-art repair tools. At the same time, the quality of the
repairs in terms of $F_1$-score ranges from comparable to better compared to
these tools.
