{"id":133008,"date":"2025-09-04T19:52:18","date_gmt":"2025-09-04T19:52:18","guid":{"rendered":"https:\/\/www.newsbeep.com\/us\/133008\/"},"modified":"2025-09-04T19:52:18","modified_gmt":"2025-09-04T19:52:18","slug":"new-open-source-tool-makes-complex-data-easily-understandable","status":"publish","type":"post","link":"https:\/\/www.newsbeep.com\/us\/133008\/","title":{"rendered":"New Open-Source Tool Makes Complex Data Easily Understandable"},"content":{"rendered":"

\t\t\"Complex<\/a>Scientists at the University of Duisburg-Essen have developed Datavzrd, an open-source tool that transforms complex tables into interactive, easy-to-use reports. This breakthrough promises to make massive datasets clearer and more accessible across scientific disciplines. Credit: Shutterstock<\/p>\n

Datavzrd makes complex datasets interactive and easy to use. It works across scientific fields without programming knowledge.<\/p>\n

Tabular data is central to scientific research, whether in medicine, the social sciences, or archaeology. Yet transforming raw tables into something clear and usable is often labor-intensive, especially when the datasets are large or complicated.<\/p>\n

To address this, the Institute for Artificial Intelligence in Medicine (IKIM) at the University of Duisburg-Essen has created Datavzrd<\/a>, an open-source tool that converts ordinary tables into interactive and visually engaging HTML reports. Importantly, it requires no programming skills or additional software. The development was recently described in the open-access journal PLOS One.<\/p>\n

Raw tables are often hard to interpret and can quickly become overwhelming. Typically, data points cannot be sorted, filtered, or connected, and when tables are shared, much of their context is lost. Existing solutions, such as R Shiny, provide useful visualization and interactivity but usually demand advanced technical expertise or specialized software.<\/p>\n

User-friendly solution at IKIM<\/p>\n

Datavzrd, designed at IKIM, avoids these drawbacks. Reports generated with the tool can be viewed directly in a web browser, attached to manuscripts, or sent by email. They stay fully interactive even when handling massive datasets with millions of rows. \u201cThe big advantage of Datavzrd is that it is particularly user-friendly and low-maintenance,\u201d explains Felix Wiegand, a computer scientist involved in its development.<\/p>\n

Wiegand, a member of Prof. Dr. Johannes K\u00f6ster\u2019s research group at IKIM, emphasizes the tool\u2019s simplicity. \u201cThe reports are not programmed, but simply described in an easy-to-understand text file \u2013 similar to a profile that specifies which data should be displayed and in what way. This allows even users without programming experience to prepare their data quickly and clearly.\u201d He adds that the tool can also represent complex relationships across multiple tables, enabling users to explore hierarchies or link related entries. A tutorial further streamlines its use, making it accessible to a wide range of researchers.<\/p>\n

Wide applications in research<\/p>\n

The IKIM team demonstrates the versatility of Datavzrd in the publication using various examples, including these two: In a molecular tumor board, genetic findings and therapy options are presented interactively on a patient-specific basis \u2013 just as required in medical practice. And in an archaeological study, decorated clothing elements from various archaeological sites are prepared in a comparable manner and presented in a linked format.<\/p>\n

\u201cDatavzrd makes data-based results intuitive, flexible, and sustainable,\u201d says Felix Wiegand, summarizing the advantages. \u201cIt is suitable for almost all disciplines and scientific fields \u2013 from research and teaching to evaluation.\u201d<\/p>\n

Reference: \u201cDatavzrd: Rapid programming- and maintenance-free interactive visualization and communication of tabular data\u201d by Felix Wiegand, David L\u00e4hnemann, Felix M\u00f6lder, Hamdiye Uzuner, Adrian Prinz, Alexander Schramm and Johannes K\u00f6ster, 22 July 2025, PLOS ONE.
DOI: 10.1371\/journal.pone.0323079<\/a><\/p>\n

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