# Towards A Methodology and Framework for Workflow-Driven Team Science

## TL;DR

This paper proposes a new methodology and framework to enhance collaboration and adaptability in scientific workflows, addressing the evolving needs of data-driven, heterogeneous, and collaborative scientific research environments.

## Contribution

It introduces a collaboration-centered reference architecture and conceptual design for methodologies and tools to improve workflow-driven team science.

## Key findings

- Design of a reference architecture for collaborative workflows
- Development of the PPoDS methodology for team collaboration
- Introduction of the SmartFlows Toolkit for workflow management

## Abstract

Scientific workflows are powerful tools for management of scalable experiments, often composed of complex tasks running on distributed resources. Existing cyberinfrastructure provides components that can be utilized within repeatable workflows. However, data and computing advances continuously change the way scientific workflows get developed and executed, pushing the scientific activity to be more data-driven, heterogeneous and collaborative. Workflow development today depends on the effective collaboration and communication of a cross-disciplinary team, not only with humans but also with analytical systems and infrastructure. This paper presents a collaboration-centered reference architecture to extend workflow systems with dynamic, predictable and programmable interfaces to systems and infrastructure while bridging the exploratory and scalable activities in the scientific process. We also present a conceptual design towards the development of methodologies and tools for effective workflow-driven collaborations, namely the PPoDS methodology and the SmartFlows Toolkit for smart utilization of workflows in a rapidly evolving cyberinfrastructure ecosystem.