  The importance of tasks in information retrieval (IR) has been long argued
for, addressed in different ways, often ignored, and frequently revisited. For
decades, scholars made a case for the role that a user's task plays in how and
why that user engages in search and what a search system should do to assist.
But for the most part, the IR community has been too focused on query
processing and assuming a search task to be a collection of user queries, often
ignoring if or how such an assumption addresses the users accomplishing their
tasks. With emerging areas of conversational agents and proactive IR,
understanding and addressing users' tasks has become more important than ever
before. In this paper, we provide various perspectives on where the
state-of-the-art is with regard to tasks in IR, what are some of the
bottlenecks in deriving and using task information, and how do we go forward
from here. In addition to covering relevant literature, the paper provides a
synthesis of historical and current perspectives on understanding, extracting,
and addressing task-focused search. To ground ongoing and future research in
this area, we present a new framing device for tasks using a tree-like
structure and various moves on that structure that allow different
interpretations and applications. Presented as a combination of synthesis of
ideas and past works, proposals for future research, and our perspectives on
technical, social, and ethical considerations, this paper is meant to help
revitalize the interest and future work in task-based IR.
