{"title":"The DataSpace for HIV vaccine studies","authors":"David McColgin, Paul Hoover, M. Igra","doi":"10.1109/VAST.2016.7883509","DOIUrl":null,"url":null,"abstract":"The DataSpace for HIV vaccine studies is a discovery tool available on the web to hundreds of investigators. We designed it to help them better understand activity in the field and explore new ideas latent in completed research. The DataSpace harmonizes immunoassay results and study metadata so that a broader research community can pursue more flexible discovery than the typical centrally planned analyses. Insights from human-centered design and beta evaluation suggest strong potential for visual analytics that may also apply to other efforts in open science. The contribution of this paper is to elucidate key domain challenges and demonstrate an application that addresses them. We made several changes to familiar visualizations to support key tasks such as identifying and filtering to a cohort of interest, making meaningful comparisons of time series data from multiple studies that have different plans, and preserving analytic context when making data transformations and comparisons that would normally exclude some data.","PeriodicalId":357817,"journal":{"name":"2016 IEEE Conference on Visual Analytics Science and Technology (VAST)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE Conference on Visual Analytics Science and Technology (VAST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VAST.2016.7883509","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
The DataSpace for HIV vaccine studies is a discovery tool available on the web to hundreds of investigators. We designed it to help them better understand activity in the field and explore new ideas latent in completed research. The DataSpace harmonizes immunoassay results and study metadata so that a broader research community can pursue more flexible discovery than the typical centrally planned analyses. Insights from human-centered design and beta evaluation suggest strong potential for visual analytics that may also apply to other efforts in open science. The contribution of this paper is to elucidate key domain challenges and demonstrate an application that addresses them. We made several changes to familiar visualizations to support key tasks such as identifying and filtering to a cohort of interest, making meaningful comparisons of time series data from multiple studies that have different plans, and preserving analytic context when making data transformations and comparisons that would normally exclude some data.