  To process a large amount of data sequentially and systematically, proper
management of workflow components (i.e., modules, data, configurations,
associations among ports and links) in a Scientific Workflow Management System
(SWfMS) is inevitable. Managing data with provenance in a SWfMS to support
reusability of workflows, modules, and data is not a simple task. Handling such
components is even more burdensome for frequently assembled and executed
complex workflows for investigating large datasets with different technologies
(i.e., various learning algorithms or models). However, a great many studies
propose various techniques and technologies for managing and recommending
services in a SWfMS, but only a very few studies consider the management of
data in a SWfMS for efficient storing and facilitating workflow executions.
Furthermore, there is no study to inquire about the effectiveness and
efficiency of such data management in a SWfMS from a user perspective. In this
paper, we present and evaluate a GUI version of such a novel approach of
intermediate data management with two use cases (Plant Phenotyping and
Bioinformatics). The technique we call GUI-RISPTS (Recommending Intermediate
States from Pipelines Considering Tool-States) can facilitate executions of
workflows with processed data (i.e., intermediate outcomes of modules in a
workflow) and can thus reduce the computational time of some modules in a
SWfMS. We integrated GUI-RISPTS with an existing workflow management system
called SciWorCS. In SciWorCS, we present an interface that users use for
selecting the recommendation of intermediate states (i.e., modules' outcomes).
We investigated GUI-RISP's effectiveness from users' perspectives along with
measuring its overhead in terms of storage and efficiency in workflow
execution.
