▁construct s . ▁This ▁results ▁both ▁in ▁simpler ▁workflow ▁graphs ▁compared ▁to ▁other ▁scientific ▁workflow ▁systems , ▁e . g . ▁Ta ver na ▁work ben ch ▁and ▁the ▁Ke pler ▁scientific ▁workflow ▁system ▁and ▁also ▁provides ▁the ▁opportunity ▁to ▁apply ▁formal ▁methods ▁for ▁the ▁analysis ▁of ▁their ▁properties . ▁ ▁Data ▁management ▁and ▁multiple ▁data ▁models ▁▁ ▁A ▁key ▁feature ▁of ▁the ▁design ▁of ▁the ▁system ▁has ▁been ▁its ▁support ▁for ▁data ▁management ▁within ▁the ▁workflow ▁engine ▁itself . ▁This ▁is ▁an ▁important ▁feature ▁since ▁scientific ▁experiments ▁typically ▁generate ▁and ▁use ▁large ▁amounts ▁of ▁heter ogeneous ▁and ▁distributed ▁data ▁sets . ▁The ▁system ▁was ▁thus ▁designed ▁to ▁support ▁pers istence ▁and ▁caching ▁of ▁intermediate ▁data ▁products ▁and ▁also ▁to ▁support ▁scal able ▁workflow ▁execution ▁over ▁potentially ▁large ▁data ▁sets ▁using ▁remote ▁compute ▁resources . ▁ ▁A ▁second ▁important ▁aspect ▁of ▁the ▁Disc overy ▁Net ▁system ▁is ▁based ▁on ▁a ▁typed ▁workflow ▁language ▁and ▁its ▁extens ibility ▁to ▁ ▁support ▁arbitrary ▁data ▁types ▁defined ▁by ▁the ▁user . ▁Data ▁typing ▁simpl ifies ▁workflow ▁scientific ▁workflow ▁development , ▁enh ances ▁optimization ▁of ▁workflow s ▁and ▁enh ances ▁error ▁checking ▁for ▁workflow ▁validation ▁. ▁The ▁system ▁included ▁a ▁number ▁of ▁default ▁data ▁types ▁for ▁the ▁purpose ▁of ▁supporting ▁data ▁min ing ▁in ▁a ▁variety ▁if ▁scientific ▁applications . ▁These ▁included ▁a ▁rel ational ▁model ▁for ▁tab ular ▁data , ▁a ▁bio in format ics ▁data ▁model ▁( FA ST A ) ▁for ▁representing ▁gene ▁sequences ▁and ▁a ▁stand - off ▁markup ▁model ▁for ▁text ▁min