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Utilizadon ofCctmpksxstatistical data has come et graet cost to imfivfduel researchers, the inhmetbn community, and to thenetbnalinfmndm infmetmctura. Diaaatiafection with thetmdtbnel appmechtoinformedon system design snd in-fOnnethaeIvbe pwieicm, and, by implii, the thaorat-icel bases on which these systems smt aervieee have been develo@ has lad Iibretfens and infwmtim Scientists to WJWe$J—rn~ is a user eonatmct and therefore system designs should place greeter emphasis on ueer-centered appmecbe. ~ia atiiole extenda Dewin's and Monis's tknticsl fremetmxk for designing effective information asmioes by synthesizing and integmting theory and research derfvad frommdlipl esppfoecheeinthe aocialsndbehav-iorel adencaa. These hecmdcel fremewotits are aodied to tionsyetams endeemicee thst relyon Complex etstietical dete. The focuaofthia atticleison fectorethet contributato srrorinthe pmducbnofhigh quelityec&ntifie outputandon faihrea OfCOIWtW~ duringthe lWOCSSSOf CbtS production and date utitizetion.Such insights provide uaaful freme-works todeaignad&tdMed syetemofaocisl co@tionthat WI detec$ diagnose, cammunicete, and barn from as?ctr. Strategies to design syatama that auppoft communicetiva cm@ence and cognhive competence emphasize the utili-zetionofidmnatbn syetemainaueer—centmd learning en-vhment. TWeinchdea v&w@cognMon ssagemmtive pmceae and recognizing the continuing i~ and active involvement of experts, novieas, and technological gatekeepers.

Extending Theory for User-Centered Information Services: Diagnosing and Learning from Error in Complex Statistical Data