Yes-Yes-Yes: Proactive Data Collection for ACL Rolling Review and Beyond

Understand

The shift towards publicly available text sources has enabled language processing at unprecedented scale, yet leaves under-serviced the domains where public and openly licensed data is scarce.

• Proactively collecting text data for research is a viable strategy to address this scarcity, but lacks systematic methodology taking into account the many ethical, legal and confidentiality-related aspects of data collection.
• Our work presents a case study on proactive data collection in peer review -- a challenging and under-resourced NLP domain.
• We outline ethical and legal desiderata for proactive data collection and introduce "Yes-Yes-Yes", the first donation-based peer reviewing data collection workflow that meets these requirements.