Skill UI

A comprehensive checklist for auditing submissions to top-tier data mining conferences like KDD. This guide covers critical areas including track declaration, OpenReview profile completeness for all authors, adherence to strict page limits, double-blind anonymity rules, and quantifying post-launch performance evidence. Essential for maximizing acceptance chances.

A comprehensive style guide for revising research papers to meet the specific, high standards of KDD conferences. It details the expected structure of the first page, emphasizing data regimes, named mechanisms, and quantifiable evidence (scale, metrics). It also provides rules for differentiating research vs. applied data science (ADS) voices and optimizing content for two-column, page-limited formats.

A comprehensive guide for authors designing figures and tables for Nature Geoscience manuscripts. It outlines strict rules for adhering to a limited figure budget (4-6 display items), ensuring the lead figure immediately conveys the core Earth-system advance and its uncertainty, and maintaining high standards of cartography and data visualization for non-specialist readership.

This guide directs authors on how to structure the related work section for academic papers in database theory (e.g., for venues like PODS, ICDT). It emphasizes a 'delta-first' approach, requiring authors to compare their specific *results* (theorems, bounds, dichotomies) directly against the nearest prior *results*, rather than simply cataloging related citations. It also covers complex rules regarding self-citation, anonymity, and overlap declaration with concurrent or prior-version work.

This skill details the rigorous methodology for defining study eligibility criteria and coding data for comprehensive meta-analyses. It emphasizes pre-specifying inclusion/exclusion rules in a protocol, developing a detailed codebook, performing double-coding, and calculating inter-rater reliability (e.g., Kappa, ICC) to ensure the reproducibility and trustworthiness of synthesis findings.

This guide helps authors polish the prose, abstract, and introduction of quantitative economics manuscripts for a general-interest Econometric Society readership. It emphasizes structuring the paper to clearly present both a substantive economic question and a quantitative method. It adheres to QE house rules, requiring findings to be communicated through point estimates with standard errors and confidence sets, rather than relying on statistical asterisks.

A comprehensive pre-submission audit checklist for authors preparing papers for the SIGMOD conference. It covers critical rules such as double-anonymous formatting, ACM template compliance, abstract-plus-COI pre-deadlines, and avoiding common desk-reject hazards. Use this guide to ensure your submission meets the rigorous technical and ethical standards required for top-tier data management publications.

A comprehensive guide for authors submitting visualization papers to major conferences like IEEE VIS. It outlines the strict rules for partitioning content, ensuring the core argument remains judgeable from the main body while leveraging supplemental materials (video, code, full data) to demonstrate interaction and reproducibility. Essential reading for academic researchers in the field.

A comprehensive checklist and guide for authors submitting research papers to PVLDB (Proceedings of the VLDB Endowment). This resource details critical steps, including adherence to multiple deadlines (abstract, full paper), category budget selection, single-blind formatting rules, and author co-contribution caps, ensuring submissions avoid desk rejection.

A comprehensive guide for submitting manuscripts to The World Bank Economic Review (WBER). It covers critical pre-submission checks, including adherence to the 40-page limit, single-anonymization rules, required data availability statements with DOIs, and correct formatting (PDF, double-spaced, Times New Roman). Use this checklist before submitting via ManuscriptCentral to ensure your paper meets the journal's strict formatting and policy requirements, minimizing the risk of immediate return.

This skill enables implementing data quality validation using Great Expectations, dbt tests, and data contracts. It is used for building reliable data pipelines, setting up validation rules, and establishing data contracts between teams. It includes automating validation in CI/CD and monitoring data quality metrics to ensure data reliability in production environments.