Making sense of the future is a precarious endeavor because there
is no such thing as a definitive forecast. For that reason, data-driven
news has been welcomed as a source of more reliable outlooks
that strengthen journalism’s contribution to anticipating future
events and setting the public agenda. However, despite large-scale
investment into computational and data-rich previsions, little is
known about the way these prognoses are told. Based on a sample
of cases, we venture into this area of sensemaking and examine
the diagrammatic patterns along which data-based projections
have been crafted into a journalistic story. In our analysis of this
nascent genre of data journalism, we characterize three forms of
predictive storytelling: concentration on a single scenario, contrasting
different scenarios, and the conjunction of several future scenarios
into a prognostic tendency. In all these forms of predictive
data stories, more or less conclusive information is arranged into a
sequence of events and trends. In most of the resulting stories,
issues of probability and uncertainty are not submitted for interactive
exploration but become integrated into a directed explanation
offered by the news pieces. Read the full version here.