  Co-adaptive guidance aims to enable efficient human-machine collaboration in
visual analytics, as proposed by multiple theoretical frameworks. This paper
bridges the gap between such conceptual frameworks and practical implementation
by introducing an accessible model of guidance and an accompanying guidance
library, mapping theory into practice. We contribute a model of system-provided
guidance based on design templates and derived strategies. We instantiate the
model in a library called Lotse that allows specifying guidance strategies in
definition files and generates running code from them. Lotse is the first
guidance library using such an approach. It supports the creation of reusable
guidance strategies to retrofit existing applications with guidance and fosters
the creation of general guidance strategy patterns. We demonstrate its
effectiveness through first-use case studies with VA researchers of varying
guidance design expertise and find that they are able to effectively and
quickly implement guidance with Lotse. Further, we analyze our framework's
cognitive dimensions to evaluate its expressiveness and outline a summary of
open research questions for aligning guidance practice with its intricate
theory.
