1. A method comprising: receiving a continuous electronic data stream of unlabeled data instances; automatically feeding said unlabeled data instances into a stream-based selection strategy and a pool-based selection strategy; automatically continuously applying said stream-based selection strategy to each of said unlabeled data instances to continually select stream-based data instances by performing an incremental computerized selection processes that selects ones of said unlabeled data instances based on human annotation criteria, incrementally as each unlabeled data instance is received; automatically storing said stream-based data instances in an electronic storage element; automatically periodically applying said pool-based selection strategy to a pool of data obtained from said unlabeled data instances to periodically select pool-based data instances by performing a batch computerized selection processes that selects ones of said unlabeled data instances based on human annotation criteria, from all unlabeled data instances in said electronic storage element; each time said pool-based selection strategy is applied, automatically replacing ones of said stream-based data instances in said electronic storage element with said pool-based data instances; providing, on demand, access to said electronic storage element to annotate ones of said stream-based data instances and said pool-based data instances currently maintained by said electronic storage element at a time when a user accesses said electronic storage element; receiving annotations relating to said stream-based data instances and said pool-based data instances from said user to produce annotated data instances; and automatically training a previous model with said annotated data instances to produce an updated model by updating said previous model using labels said annotations provide.