@misc{007dccb9061946279cea924cbc646885,
title = "PIPES: Pipeline for Integrated Projects in Energy Systems",
abstract = "Pipeline for Integrated Projects in Energy Systems (PIPES) is an open-source platform for project, data, and workflow management that helps integrated modeling teams manage large-scale, multi-model analyses. PIPES serves as a centralized repository to manage project data, metadata, tasks, and model workflows, with project schedule tracking and automated validation of model handoffs. The platform includes a user interface, a CLI, and an API so technical users (scientific modelers, data scientists, analysts) and nontechnical stakeholders (project managers, decision-makers, clients) can configure, track, and visualize end-to-end project pipelines. Through this, PIPES supports project tracking and resulting scalability, reinforcing best practices in large-scale energy system modeling. The PIPES platform was inspired by a need to advance integrated modeling projects' process tracking and handoff management to fully leverage the capability of energy systems modeling across the national labs and beyond. It simplifies and accelerates scientific energy projects through a user-friendly platform and a standardized corpus of foundational model and dataset metadata. Projects managers and team members can assemble complete project pipelines detailing the modeling workflow and capture technical requirements and assumptions for each step of the process.",
keywords = "data, data management, DOE, energy, energy systems, integrated modeling, metadata, modeling, pipeline, PIPES, project management, scalability, scientific energy projects, tracking, workflow",
author = "Adrienne Lowney and James Morris and Jianli Gu and Jane Lockshin and Meghan Mooney",
year = "2026",
language = "American English",
series = "Presented at the DOE Data Days (D3) Workshop, 3-5 March 2026, Chantilly, Virginia",
publisher = "National Laboratory of the Rockies (NLR)",
address = "United States",
type = "Other",
}