Skill UI

This guide details the complex requirements for writing the 'Related Work' section for CIKM submissions. It emphasizes the need for 'three-front coverage' (Retrieval, Mining, and Knowledge Management/Databases) and provides specific instructions on writing the 'boundary-work paragraph.' It also covers critical academic hygiene, such as avoiding venue misattribution, maintaining recency baselines, and accurately stating novel contributions.

Provides stringent guidelines for formatting tables and figures in high-level economics and finance manuscripts. Covers mandatory three-line table styles, column count limits, rigorous variable definition requirements (including naming specific databases), data source transparency, and professional figure generation techniques (e.g., 300 dpi, proper event study plots).

This guide provides comprehensive instructions for creating a robust, reproducible artifact package for database systems research. It details best practices including containerization, pinning workloads, generating a permanent DOI-archived record, and designing the package to be successfully built and demonstrated on a reviewer's clean machine within a tight time budget. The goal is to strengthen scientific rigor and ensure permanent, open-access citation.

This guide provides comprehensive standards for designing, auditing, and reporting empirical evaluations in database systems research. It emphasizes the principle that evidence must proportionally match the claim, requiring the use of real-world workloads, fair and tuned baselines, thorough measurement of variance and state (warm/cold), and fully reproducible evaluation harnesses. It also outlines the higher bar for 'Experiments & Analysis' papers.

A comprehensive guide for authors submitting to top-tier database conferences (like EDBT). It teaches how to audit the novelty and eligibility of a research paper by writing a 'delta-first' contrast against related work, rather than simply listing citations. Covers positioning contributions relative to flagship venues, theory literature, and managing resubmission rules.

This guide outlines best practices for achieving high levels of research reproducibility for academic papers, particularly in database and systems research. It details methods for pinning dataset versions, logging system environments, mapping empirical claims to verifiable evidence, and structuring availability statements. Adherence ensures the work is robust, transparent, and fully verifiable by the scientific community.

A comprehensive guide detailing the multi-cycle, rolling model for EDBT research submissions. It covers the entire review pipeline, from initial program committee evaluation and author-feedback exchange, through the accept/revise/reject decision, and critically, the in-cycle revise-and-resubmit stage. The guide also contrasts EDBT's open-access, three-cycle cadence with other top-tier database conferences (e.g., SIGMOD, VLDB).

This guide outlines the strict rules for dividing a research paper into the main body and supplementary materials (artifact/appendices), particularly for database systems conferences like EDBT. It emphasizes that all decision-critical evidence must be presented within the reviewed pages, ensuring reviewers can judge the work without needing to open external files. It covers page budget discipline, reproducibility standards, and practical partitioning techniques.

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.

A comprehensive guide for academic researchers on structuring the 'Data and Sample' section of manuscripts for high-impact journals. It details requirements for database naming, variable definition using calculation formulas, descriptive statistics reporting (including winzorization and quantiles), and establishing full, reproducible sample selection trails. Essential for ensuring methodological rigor and passing peer review.