Harnessing the crowd to collect massive amounts of data (crowdsourcing) has become increasingly popular. Examples in our culture include Wikipedia, social tagging systems for images, traffic information aggregators like Waze, and hotel and movie ratings like TripAdvisor and IMDb. In this talk, I give an overview of the challenges inherent in providing declarative, database-style platforms for supporting crowdsourcing. I then discuss how to go one step further and enable users to posed general questions to mine the crowd for potentially relevant data, and to receive concise, relevant answers that represent frequent significant data patterns. I close by discussing the challenges that crowd mining poses for provenance.