The DEEP is a collaborative platform for qualitative data analysis supporting humanitarian analytical teams to produce actionable insights. Since its inception in the aftermath of the 2015 Nepal Earthquake, DEEP has significantly contributed to improving the humanitarian data ecosystem, and today, without a doubt, is the largest repository of annotated humanitarian response documents: 50k+ sources/leads and 400k+ entries, used for 300+ projects by 3.5k+ registered users in 60+ countries.

During crises, rapidly identifying important information from available data (news, reports, research, etc.) is crucial to understand the needs of affected populations and to improve evidence-based decision making. To make the information classification process even faster, DEEP is largely benefitting from Natural Language Processing (NLP) and Deep Learning (DL) to aid and support the manual tagging process and give the humanitarian community more time to produce analyses and take rapid action to save more lives.

This track will be a thriving platform for fostering the dialogue and forming synergies between United Nations, humanitarian response communities, and NLP/DL experts. We aim to build this bridge by bringing forward the challenges and opportunities of the NLP/DL developments for DEEP from the technical, ethical, and humanitarian perspectives. This is an extended invitation to the attendees for open discussions, experimentation, and participation leading to further enrichment of this domain.