For this query that you have chosen, J is not independent of K given W, simply because K is part of J's Markov blanket. Also, J cannot be independent of K because K is J's Parent.
In general, we can determine if 2 nodes are conditionally independent of each other (given some other nodes) based on the following scenarios:
1) Indirect "Causal" Effect
- K is independent of W given J
2) Indirect Evidential Effect
- W is independent of K given J
3) Common "Cause"
- G is independent of W given C
4) Common Effect / Collider
- B is NOT independent of T given X (i.e. X acts as a collider, and if we know information about X, B and T can be
dependent) If X is NOT OBSERVED, then B and T are
marginally independent.
It is not entirely necessary to use Markov Blankets to determine if 2 nodes are independent of each other.
But to give you a better understanding of how Markov blanket can be applied to determine independence, lets consider the node C
Given C's Markov Blanket, L, G, W, J, which are C's Parents, Children, and Children's Parents, C is then independent of every other node in the Bayesian Network.
Therefore, we can say that:
C is independent of B, X, T, K, given L, G, W, J