Passenger arrivals research splits into two distinct workflows. The voyage-specific lookup is well-served by per-ship pages, but the broader year-and-port research, where someone searches for "all arrivals at Galveston in 1907" or "all New Orleans arrivals 1880 to 1885," is a different surface entirely. Aggregators handle it through filtered search results, with no dedicated URL for the year-port pairing.

SleekRank reads the arrivals aggregation file and emits one WordPress page per year-and-port pair. Each page carries arrival year, port name, total voyages, total passengers, top three lines by passenger volume, microfilm publication range, and an Event schema block representing the arrival corpus, all driven by tag and selector mappings on a shared base. The URL pattern is /arrivals/{slug}/, and new aggregations appear after the next cache refresh.

The win is that voyage-specific pages, year-port aggregations, and individual passenger pages can all be generated from the same source files by running three separate page groups. The CSV stays canonical, the rendering stays cache-driven, and the corpus becomes a network of landing pages where researchers pivot naturally between year, port, voyage, and passenger views.

Migration history research splits naturally into corpus-level and voyage-level queries. Aggregators handle voyage-level workflows through name and ship search, but corpus-level queries ("all arrivals at New Orleans in 1883" or "top lines arriving at Boston in 1912") have no dedicated URLs in any major public surface. Researchers find aggregate context only inside aggregator filter results, which means the structural research workflow that migration historians actually use is invisible to search engines.

SleekRank closes the gap by turning the same year-port aggregation file into a corpus of landing pages on a heritage organisation's own domain. Each year-port pair becomes its own URL that ranks for port-and-year searches. Internal links to voyage and passenger page groups build a cross-linked structure that mirrors how migration research actually flows.

Event and Dataset schema make every page eligible for entity panels and enhanced results. The corpus stays current with NARA and FamilySearch through cache cycles. Aggregators win on integrated search; the per-year-port page wins on the structural depth that migration history research actually requires, and on capturing the long-tail searches that previously had no public landing surface at all.