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

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.