  We describe the Gun Violence Database (GVDB), a large and growing database of
gun violence incidents in the United States. The GVDB is built from the
detailed information found in local news reports about gun violence, and is
constructed via a large-scale crowdsourced annotation effort through our web
site, http://gun-violence.org/. We argue that centralized and publicly
available data about gun violence can facilitate scientific, fact-based
discussion about a topic that is often dominated by politics and emotion. We
describe our efforts to automate the construction of the database using
state-of-the-art natural language processing (NLP) technologies, eventually
enabling a fully-automated, highly-scalable resource for research on this
important public health problem.
