Skill UI

This guide outlines the stringent reproducibility and data requirements for submitting manuscripts to Agricultural Systems (AgSy). Because AgSy treats code, models, and algorithms as research data, authors must learn how to deposit all materials in a recognized repository (e.g., Zenodo, OSF), cite them permanently, and document the model structure, parameters, and versions. It provides a checklist for building a reproducible research workflow.

A comprehensive guide for preparing data-availability statements, shareable data, and reproducible code for conservation biology manuscripts. It outlines best practices for using persistent identifiers (like Dryad or Zenodo), masking sensitive species locations, and documenting full research provenance to meet journal standards.

This comprehensive guide outlines best practices for packaging and releasing scientific artifacts—including code, training configurations, demonstration data, and policy checkpoints—for robotics research papers. It details how to prepare materials for anonymous reviewer assessment and for durable public release, ensuring the work is fully reproducible by the academic community.

This guide outlines the creation of a complete, verifiable research package for economic policy manuscripts. It ensures that all empirical, experimental, or simulation results are fully reproducible by providing raw data guides, cleaning scripts, analysis code, and a single 'master' script that runs end-to-end. This process is critical for academic acceptance, allowing reviewers and discussants to independently verify every figure, table, and key number reported in the paper.

This guide details the requirements for creating a comprehensive replication package for manuscripts submitted to Econometric Society journals. It ensures full reproducibility of all results, including code, data provenance, and parameter settings, adhering to the journal's Data and Code Availability Policy. Key components include a master script, reproducible data, and detailed documentation.

This guide outlines best practices for submitting theoretical econometrics manuscripts to ET. It addresses how to handle extensive proofs, auxiliary lemmas, and simulation results that exceed page limits. The core focus is utilizing the voluntary Supplementary Material policy to ensure full reproducibility and transparency without requiring mandatory data or code archives.

This guide outlines the mandatory open data and code requirements for publishing in Global Change Biology (GCB). It details that primary and secondary data, along with supporting code/software, must be archived in public, DOI-minting repositories (e.g., Dryad, Zenodo) prior to acceptance. It emphasizes that 'available on request' is not accepted and provides a structured checklist for ensuring reproducibility and proper metadata submission.

This guide assists authors planning to submit to Games and Economic Behavior (GEB) by detailing best practices for data and code sharing. It clarifies that while data deposition is strongly encouraged for reproducibility, it is not a mandatory requirement. It outlines what to prepare, including raw data, analysis scripts, experimental instructions, and proper availability statements.

This guide outlines the mandatory data and code deposit policy for articles published in the Journal of Applied Econometrics (JAE). Authors must submit a complete, non-confidential set of input data (plain ASCII/CSV), programs that replicate every result, and a detailed README file. It emphasizes strict adherence to archival format rules, ensuring the research is fully reproducible for the academic community.

This guide assists researchers in assembling a comprehensive, reproducible data and code supplement for submissions to statistical journals, adhering to the American Statistical Association (ASA) data-sharing policies. It outlines the required structure (README, code, data), provenance tracking, environment pinning, and necessary steps (like setting random seeds and drafting data availability statements) to ensure that published results can be fully regenerated and verified by reviewers.

This comprehensive guide outlines the best practices for preparing a complete and reproducible research package for submission to the Journal of Banking & Finance (JBF) following Elsevier Option C guidelines. It details requirements for data availability statements, proper structuring of code and data access materials, and best methods for managing proprietary or restricted datasets (such as CRSP or Compustat), ensuring research transparency and verifiability.

This guide assists authors in preparing research materials for submission to the Journal of Financial Intermediation (JFI), adhering to Elsevier Option C. It provides detailed instructions on managing, depositing, citing, and linking research data, code, and algorithms—whether the data is public, proprietary, or restricted (e.g., central bank registers). The goal is to ensure methodological rigor and reproducibility through the Data Statement.