  Data documents play a central role in recording, presenting, and
disseminating data. Despite the proliferation of applications and systems
designed to support the analysis, visualization, and communication of data,
writing data documents remains a laborious process, requiring a constant
back-and-forth between data processing and writing tools. Interviews with eight
professionals revealed that their workflows contained numerous tedious,
repetitive, and error-prone operations. The key issue that we identified is the
lack of persistent connection between text and data. Thus, we developed
CrossData, a prototype that treats text-data connections as persistent,
interactive, first-class objects. By automatically identifying, establishing,
and leveraging text-data connections, CrossData enables rich interactions to
assist in the authoring of data documents. An expert evaluation with eight
users demonstrated the usefulness of CrossData, showing that it not only
reduced the manual effort in writing data documents but also opened new
possibilities to bridge the gap between data exploration and writing.
