Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Digital Collaborator: Augmenting Task Abstraction in Visualization
  Design with Artificial Intelligence   In the task abstraction phase of the visualization design process, including
in "design studies", a practitioner maps the observed domain goals to
generalizable abstract tasks using visualization theory in order to better
understand and address the users needs. We argue that this manual task
abstraction process is prone to errors due to designer biases and a lack of
domain background and knowledge. Under these circumstances, a collaborator can
help validate and provide sanity checks to visualization practitioners during
this important task abstraction stage. However, having a human collaborator is
not always feasible and may be subject to the same biases and pitfalls. In this
paper, we first describe the challenges associated with task abstraction. We
then propose a conceptual Digital Collaborator: an artificial intelligence
system that aims to help visualization practitioners by augmenting their
ability to validate and reason about the output of task abstraction. We also
discuss several practical design challenges of designing and implementing such
systems

10
The categories of this paper are: q-bio
20
The categories of this paper are: acc-phys
14
The categories of this paper are: math-ph
34
The categories of this paper are: chem-ph
7
The categories of this paper are: hep-th
32
The categories of this paper are: atom-ph
12
The categories of this paper are: nucl-th
37
The categories of this paper are: supr-con
29
The categories of this paper are: funct-an
36
The categories of this paper are: cmp-lg
21
The categories of this paper are: adap-org
22
The categories of this paper are: chao-dyn
17
The categories of this paper are: q-fin
16
The categories of this paper are: stat
4
The categories of this paper are: cond-mat
5
The categories of this paper are: gr-qc