{"title":"比较时间序列图可视化的基准任务和洞察力评估方法","authors":"Purvi Saraiya, Chris North, K. Duca","doi":"10.1145/2110192.2110201","DOIUrl":null,"url":null,"abstract":"A study to compare two different empirical research methods for evaluating visualization tools is described: the traditional benchmark-task method and the insight method. The methods were compared using different criteria such as: the conclusions about the visualization tools provided by each method, the time participants spent during the study, the time and effort required to analyze the resulting empirical data, and the effect of individual differences between participants on the results. The studies used three graph visualization alternatives to associate bioinformatics microarray timeseries data to pathway graph vertices, based on popular approaches used in existing bioinformatics software.","PeriodicalId":235801,"journal":{"name":"Workshop on Beyond Time and Errors: Novel Evaluation Methods for Visualization","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":"{\"title\":\"Comparing benchmark task and insight evaluation methods on timeseries graph visualizations\",\"authors\":\"Purvi Saraiya, Chris North, K. Duca\",\"doi\":\"10.1145/2110192.2110201\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A study to compare two different empirical research methods for evaluating visualization tools is described: the traditional benchmark-task method and the insight method. The methods were compared using different criteria such as: the conclusions about the visualization tools provided by each method, the time participants spent during the study, the time and effort required to analyze the resulting empirical data, and the effect of individual differences between participants on the results. The studies used three graph visualization alternatives to associate bioinformatics microarray timeseries data to pathway graph vertices, based on popular approaches used in existing bioinformatics software.\",\"PeriodicalId\":235801,\"journal\":{\"name\":\"Workshop on Beyond Time and Errors: Novel Evaluation Methods for Visualization\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-04-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"16\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Workshop on Beyond Time and Errors: Novel Evaluation Methods for Visualization\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2110192.2110201\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Workshop on Beyond Time and Errors: Novel Evaluation Methods for Visualization","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2110192.2110201","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Comparing benchmark task and insight evaluation methods on timeseries graph visualizations
A study to compare two different empirical research methods for evaluating visualization tools is described: the traditional benchmark-task method and the insight method. The methods were compared using different criteria such as: the conclusions about the visualization tools provided by each method, the time participants spent during the study, the time and effort required to analyze the resulting empirical data, and the effect of individual differences between participants on the results. The studies used three graph visualization alternatives to associate bioinformatics microarray timeseries data to pathway graph vertices, based on popular approaches used in existing bioinformatics software.