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Provenance-based Belief
March 2010
Adriane Chapman, The MITRE Corporation
Barbara Blaustein, The MITRE Corporation
Chris Elsaesser, The MITRE Corporation
ABSTRACT
Provenance has been touted as a basis to establish
trust in data. Intuitively, belief in a hypothesis should
depend on how much one trusts the relevant data.
However, current proposals to assess trust based solely
on provenance are insufficient for rigourous decision
making. We describe a model of provenance and belief
that is necessary and sufficient to incorporate “trust in
the data” in a way that supports normative inference. The
model is based on the observation that provenance can be
viewed as a causal structure which can be used to
compute belief from assessments of the accuracy of
sources and transformations that produced relevant data.
In our model, data sources are like sensors with
associated conditional probability tables. Provenance
identifies dependencies among sensors. Together, this
information allows construction of causal networks that
can be used to compute the belief in a state of the world
based on observation of data. This model formalizes the
role of source accuracy, and provides a method for
formally assessing belief that uses only information in the
provenance store, not the contents of the data.
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