The Web has enabled the availability of a huge amount of useful information,
but has also eased the ability to spread false information and rumors across
multiple sources, making it hard to distinguish between what is true and what
is not. Recent examples include the premature Steve Jobs obituary, the second
bankruptcy of United airlines, the creation of Black Holes by the operation of
the Large Hadron Collider, etc. Since it is important to permit the expression
of dissenting and conflicting opinions, it would be a fallacy to try to ensure
that the Web provides only consistent information. However, to help in
separating the wheat from the chaff, it is essential to be able to determine
dependence between sources. Given the huge number of data sources and the vast
volume of conflicting data available on the Web, doing so in a scalable manner
is extremely challenging and has not been addressed by existing work yet.

In this paper, we present a set of research problems and propose some
preliminary solutions on the issues involved in discovering dependence between
sources. We also discuss how this knowledge can benefit a variety of
technologies, such as data integration and Web 2.0, that help users manage and
access the totality of the available information from various sources.