Advances in Open Source Forecasting Software

Call for paper

Advances in Open Source Forecasting Software

Journal: International Journal of Forecasting
Publisher: Elsevier
Submission Deadline: 31 August 2026

Detailed Overview

International Journal of Forecasting (Impact Factor: 7.1, CiteScore: 17.1), a premier Elsevier journal, calls for papers for this special section on open-source forecasting software advancements. It highlights how mature libraries and pre-trained models in R, Python, and Julia enhance collaboration, accessibility, transparency, reproducibility, and adoption in forecasting workflows. Emphasis is on addressing forecasting's unique challenges—complex data, temporal patterns, evaluation—through specialized abstractions, scalable designs, and trade-offs at the software-forecasting intersection.

Guest Editors:
Mitchell O’Hara-Wild (Monash University, Australia, Mitch.OHara-Wild@monash.edu)
Anastasios Panagiotelis (Monash University, Australia, anastasios.panagiotelis@monash.edu)
Tim Januschowski (Databricks, Berlin, Germany, tim.januschowski@gmail.com)

Core Themes and Topics

• Forecasting software frameworks and large pre-trained models.

• Forecasting at scale (efficient code, parallelisation).

• Benchmarking, forecast evaluation.

• Real-world operational applications of open-source tools.

Key Dates

Submission Guidelines

• Submit via https://submit.elsevier.com/IJF, selecting "SI: Open-Source Forecasting" and include cover letter.

• Follow guide: https://www.sciencedirect.com/journal/international-journal-of-forecasting/publish/guide-for-authors.

• Concise papers (~20 pages); focus on forecasting-informed design, not just software showcases; peer-reviewed.

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