Skill UI

This comprehensive guide helps researchers audit their papers before submission to the EDBT conference. It covers critical steps including selecting the correct submission cycle and paper shape (Regular, Vision, Experiments & Analysis), adhering to strict formatting standards, managing the 12-month resubmission ban, ensuring double-blind compliance, and providing verifiable, reproducible artifacts. It is essential for academic publishing compliance.

This guide helps researchers determine the optimal venue for their database project, analyzing whether the work belongs at EDBT, SIGMOD, VLDB, ICDE, or a dedicated theory venue like ICDT. It provides frameworks for choosing the right conference based on contribution type (systems, theory, experiments), open access preferences, and submission cycle proximity.

A comprehensive project management guide for submitting database systems papers to EDBT. It details the complexities of the multiple-cycle rolling publication model, covering everything from initial evidence lock and cycle selection to the five-step review arc (Submission, Author Feedback, Revision, etc.). Use this to backward-plan your research timeline and manage the entire academic publishing process.

This guide provides stringent best practices for authors submitting papers to top database systems conferences (like EDBT). It emphasizes leading with a concrete data-management contribution, ensuring mechanisms are reproducible in prose, and pairing every claim with rigorous, real-world evidence. It also dictates how to manage scope and adhere to publishing constraints.

This skill guides users through strengthening the causal identification strategy of empirical economic manuscripts (DiD, IV, RDD, Experiments). It helps audit research designs against general academic credibility standards, ensuring that assumptions, potential biases, and the link between data variation and causal objects are explicitly stated and robustly defended for diverse expert audiences.

This guide provides a structured framework for authors to sharpen the narrative of their academic contribution, particularly for high-impact journals. It teaches the 'two-layer positioning': creating a broad-interest hook for general readers, and defining a precise marginal delta against 3-5 specific, current frontier papers. It transforms vague related-work sections into compelling, verifiable arguments.

This guide helps academic authors anticipate and proactively address likely critiques from expert reviewers (e.g., limited scope, weak identification, missing robustness checks) before submitting to top-tier journals. By mapping potential objections to specific defenses within the manuscript, authors can significantly reduce the risk of desk rejection and streamline the review process.

This guide outlines the mandatory structure for creating a reproducible research package, required by academic journals like the European Economic Review (EER). It details how to properly assemble raw data, master analysis scripts, environmental specifications, and comprehensive documentation (README) to ensure that reported results can be independently verified by others. It is essential for any paper involving empirical analysis or simulations.

A comprehensive guide for building a 'robustness battery' to validate empirical findings. It instructs researchers on thoroughly testing results against potential weaknesses in specification, sample selection, measurement, estimator choice, and inference assumptions. Essential for publishing rigorous, credible quantitative research.

This comprehensive preflight checklist guides researchers through the final essential steps before submitting a manuscript to the European Economic Review (EER). It ensures adherence to Elsevier formatting standards, addresses mandatory replication policies (data/code availability), verifies funding declarations, and confirms all necessary fees and ethical statements are in place. Use this guide as the ultimate final check before pressing submit.

A comprehensive guide for authors preparing manuscripts for top economics journals (e.g., EER). It details best practices for designing self-contained tables and figures, emphasizing the correct reporting of standard errors (SEs), confidence intervals (CIs), and interpreting results cleanly. This guide ensures exhibits adhere to rigorous academic publishing standards, moving beyond simple star counts to let the magnitude of the result speak for itself.

A comprehensive guide for economists on refining theoretical models and structures for publication in high-impact journals. It provides rigorous best practices for developing pure economic theory, executing structural quantitative modeling, and ensuring models effectively interpret empirical estimates, focusing on generalizability and interpretability.