{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,2]],"date-time":"2025-11-02T09:40:55Z","timestamp":1762076455098,"version":"build-2065373602"},"reference-count":66,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2022,11,19]],"date-time":"2022-11-19T00:00:00Z","timestamp":1668816000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Chinese Key-Area Research and Development Program of Guangdong Province","award":["2020B0101350001","1916425","1734853","1636840","1416953","0716055","1023115","P20 NR015331","P30 DK089503","UL1 TR002240","R01 CA233487","R01 MH121079","R01 MH126137","T32 GM141746"],"award-info":[{"award-number":["2020B0101350001","1916425","1734853","1636840","1416953","0716055","1023115","P20 NR015331","P30 DK089503","UL1 TR002240","R01 CA233487","R01 MH121079","R01 MH126137","T32 GM141746"]}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["2020B0101350001","1916425","1734853","1636840","1416953","0716055","1023115","P20 NR015331","P30 DK089503","UL1 TR002240","R01 CA233487","R01 MH121079","R01 MH126137","T32 GM141746"],"award-info":[{"award-number":["2020B0101350001","1916425","1734853","1636840","1416953","0716055","1023115","P20 NR015331","P30 DK089503","UL1 TR002240","R01 CA233487","R01 MH121079","R01 MH126137","T32 GM141746"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["2020B0101350001","1916425","1734853","1636840","1416953","0716055","1023115","P20 NR015331","P30 DK089503","UL1 TR002240","R01 CA233487","R01 MH121079","R01 MH126137","T32 GM141746"],"award-info":[{"award-number":["2020B0101350001","1916425","1734853","1636840","1416953","0716055","1023115","P20 NR015331","P30 DK089503","UL1 TR002240","R01 CA233487","R01 MH121079","R01 MH126137","T32 GM141746"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>Many systems for exploratory and visual data analytics require platform-dependent software installation, coding skills, and analytical expertise. The rapid advances in data-acquisition, web-based information, and communication and computation technologies promoted the explosive growth of online services and tools implementing novel solutions for interactive data exploration and visualization. However, web-based solutions for visual analytics remain scattered and relatively problem-specific. This leads to per-case re-implementations of common components, system architectures, and user interfaces, rather than focusing on innovation and building sophisticated applications for visual analytics. In this paper, we present the Statistics Online Computational Resource Analytical Toolbox (SOCRAT), a dynamic, flexible, and extensible web-based visual analytics framework. The SOCRAT platform is designed and implemented using multi-level modularity and declarative specifications. This enables easy integration of a number of components for data management, analysis, and visualization. SOCRAT benefits from the diverse landscape of existing in-browser solutions by combining them with flexible template modules into a unique, powerful, and feature-rich visual analytics toolbox. The platform integrates a number of independently developed tools for data import, display, storage, interactive visualization, statistical analysis, and machine learning. Various use cases demonstrate the unique features of SOCRAT for visual and statistical analysis of heterogeneous types of data.<\/jats:p>","DOI":"10.3390\/info13110547","type":"journal-article","created":{"date-parts":[[2022,11,21]],"date-time":"2022-11-21T04:13:36Z","timestamp":1669004016000},"page":"547","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["SOCRAT: A Dynamic Web Toolbox for Interactive Data Processing, Analysis and Visualization"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4563-3226","authenticated-orcid":false,"given":"Alexandr A.","family":"Kalinin","sequence":"first","affiliation":[{"name":"Statistics Online Computational Resource (SOCR), Department of Health Behavior and Biological Sciences, University of Michigan, Ann Arbor, MI 48104, USA"},{"name":"Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48104, USA"},{"name":"Shenzhen Research Institute of Big Data, Shenzhen 518172, China"},{"name":"Statistics Online Computational Resource (SOCR), Department of Statistics, University of California Los Angeles, Los Angeles, CA 90095, USA"}]},{"given":"Selvam","family":"Palanimalai","sequence":"additional","affiliation":[{"name":"Statistics Online Computational Resource (SOCR), Department of Health Behavior and Biological Sciences, University of Michigan, Ann Arbor, MI 48104, USA"}]},{"given":"Junqi","family":"Zhu","sequence":"additional","affiliation":[{"name":"Statistics Online Computational Resource (SOCR), Department of Health Behavior and Biological Sciences, University of Michigan, Ann Arbor, MI 48104, USA"}]},{"given":"Wenyi","family":"Wu","sequence":"additional","affiliation":[{"name":"Statistics Online Computational Resource (SOCR), Department of Health Behavior and Biological Sciences, University of Michigan, Ann Arbor, MI 48104, USA"}]},{"given":"Nikhil","family":"Devraj","sequence":"additional","affiliation":[{"name":"Statistics Online Computational Resource (SOCR), Department of Health Behavior and Biological Sciences, University of Michigan, Ann Arbor, MI 48104, USA"}]},{"given":"Chunchun","family":"Ye","sequence":"additional","affiliation":[{"name":"Statistics Online Computational Resource (SOCR), Department of Statistics, University of California Los Angeles, Los Angeles, CA 90095, USA"}]},{"given":"Nellie","family":"Ponarul","sequence":"additional","affiliation":[{"name":"Statistics Online Computational Resource (SOCR), Department of Statistics, University of California Los Angeles, Los Angeles, CA 90095, USA"}]},{"given":"Syed S.","family":"Husain","sequence":"additional","affiliation":[{"name":"Statistics Online Computational Resource (SOCR), Department of Health Behavior and Biological Sciences, University of Michigan, Ann Arbor, MI 48104, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3825-4375","authenticated-orcid":false,"given":"Ivo D.","family":"Dinov","sequence":"additional","affiliation":[{"name":"Statistics Online Computational Resource (SOCR), Department of Health Behavior and Biological Sciences, University of Michigan, Ann Arbor, MI 48104, USA"},{"name":"Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48104, USA"},{"name":"Shenzhen Research Institute of Big Data, Shenzhen 518172, China"},{"name":"Statistics Online Computational Resource (SOCR), Department of Statistics, University of California Los Angeles, Los Angeles, CA 90095, USA"},{"name":"Michigan Institute for Data Science (MIDAS), University of Michigan, Ann Arbor, MI 48104, USA"}]}],"member":"1968","published-online":{"date-parts":[[2022,11,19]]},"reference":[{"key":"ref_1","unstructured":"McAfee, A., and Brynjolfsson, E. 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