  We present CQELS 2.0, the second version of Continuous Query Evaluation over
Linked Streams. CQELS 2.0 is a platform-agnostic federated execution framework
towards semantic stream fusion. In this version, we introduce a novel
neural-symbolic stream reasoning component that enables specifying deep neural
network (DNN) based data fusion pipelines via logic rules with learnable
probabilistic degrees as weights. As a platform-agnostic framework, CQELS 2.0
can be implemented for devices with different hardware architectures (from
embedded devices to cloud infrastructures). Moreover, this version also
includes an adaptive federator that allows CQELS instances on different nodes
in a network to coordinate their resources to distribute processing pipelines
by delegating partial workloads to their peers via subscribing continuous
queries
