This website is meant as a quick overview of information related to the review process of AutomotiveUI, especially the papers track. This page is a work-in-progress, that we occasionally update in an attempt to be as transparent as possible about criteria and context.
We discuss these topics:
Deadline for Reviews (all reviewers): May 25, 2022
Deadline for Meta-Reviews (ACs): June 3, 2022
All deadlines are AoE (anywhere on earth) on the date shown.
You can volunteer to become a reviewer for AutomotiveUI 2022 via the precision conference system (note: links for various tracks will open gradually). To see which tracks are currently available to volunteer for, select for “Show only” the following: Society - SIGCHI; Conference/journal: AutomotiveUI 2022.
When you volunteer, we ask you to update your profile with the following information via various submenus here:
ACs use this information to select the best reviewers that match the work. Keywords and example papers are also used by PCS to semi-automatically suggest suitable reviewers. Update this to have the best matches to your expertise.
You will be invited by ACs via e-mail (automated message from PCS) to review a paper.
The general reviewing process of the Papers track is explained in the call of the papers track. Check the section “review process” here: https://www.auto-ui.org/22/authors/papers/
AutomotiveUI strives to accept the best scientific work that is relevant for the AutomotiveUI community. As a reviewer you give an assessment of the paper to inform the Associate Chair (AC), knowing that authors will also read your review. The AC uses your review and that of other reviewers to recommend acceptance of rejection of the paper to the Technical Program Chairs, who take the final decision.
Reviewers are asked to consider for each paper:
You express your judgment in three ways:
When reviewing, you can consider ACM SIGCHI’s criteria that reviews should be (a) high quality and (b) fair.
High quality implies that you systematically and clearly motivate your assessment. Even if you think a paper is great, you should motivate why, so the AC and TPC also understand this (not all might be familiar with this specific method or topic).
If you think a paper is weak, you should explain why. Keep in mind that authors are reading this, so your feedback can help them improve this line of work in the future. Especially when the first author is a (PhD) student, your constructive feedback can help them improve this line of work. Don’t just say that something is not good enough, but explain why and use sound argumentation.
Fair can be understood in multiple ways:
AutomotiveUI is a conference organized by ACM SIGCHI. Some broader policies and tips can therefore be found on other sites. Note that not everything applies to AutomotiveUI: