PODS Topic Selection
Evaluates database management research to accurately route papers between ACM PODS, SIGMOD, VLDB, ICDT, and pure theory venues.
PODS Topic Selection guides academic researchers in determining whether a data-management project aligns with the theoretical rigor of ACM PODS or should be targeted toward systems flagships like SIGMOD/VLDB/ICDE, sister theory venues like ICDT, or pure theory conferences like LICS and STOC. By evaluating contribution shapes (such as complexity classifications, query semantics, and provably optimal algorithms) through concrete heuristic tests like the result-swap and re-label checks, this skill prevents costly venue mismatches and ensures your research is structured for the right audience before writing starts.
Características Principales
01Provides a routing matrix mapping research outputs to ACM PODS, SIGMOD/VLDB/ICDE, ICDT, LICS/ICALP, or journals
02Guides reconnaissance strategies across bibliography citations, DBLP tracks, and dual-cycle conference deadlines
03Identifies optimal PODS contribution shapes including complexity dichotomies, query expressiveness, and semantics
04Assesses proof maturity and scope to determine when projects require full journal treatment (TODS/JACM) versus symposium abstracts
05Differentiates theoretical database contributions from empirical systems research using the result-swap and re-label tests
061,086 GitHub stars
Casos de Uso
01Selecting between ACM PODS and ICDT based on publication calendars, community focus, and paper maturity
02Evaluating whether an emerging data model or logic formalization meets PODS's bar for provable, foundational statements
03Deciding whether a database algorithm paper belongs at PODS as a theoretical bound or SIGMOD/VLDB as an empirical system