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SciDAVis (Scientific Data Analysis and Visualization) is an open-source cross-platform computer program for interactive scientific graphing and data analysis. Development started in 2007 as fork of QtiPlot, which in turn is a clone of the proprietary program Origin.
The analysis highlights History, Art and Science as prominent areas in the source structure around SciDAVis.
Source areas are shown by the number of related topics found in each part of the analysis. Use smaller areas too: they can reveal specialized angles and content gaps.
Smaller areas are not necessarily less important. They contain fewer connections in this analysis and can be useful for finding specialized angles or coverage gaps.
High-confidence facts extracted from structured source data. Use them as anchors for further research.
Browse the complete topic structure, not only the most central items. Less prominent entities and concepts can reveal missing angles, specialized context and useful research gaps. Each item opens a new analysis centered on that subject.
Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.
The extracted context around SciDAVis shows recurring relationship patterns in the source. For example, SciDAVis → ASCII, Curve, EPS, FFT, FFT-based, GNU Scientific Library, Note, PDF, Python, Qt, SVG, The, The GUI Another extracted example is SciDAVis → After, Franke, In, Ion Vasilief, KDE, KDE4, Knut Franke, LabPlot, Qt, QtiPlot, This, Tilman Benkert. Use these groups to spot repeated connection types before inspecting the individual relationships.
Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.
data analysis release project program windows fork qtiplot franke code open-source cross-platform python plots scientific graphing development 2007 tilman benkert
TTTA extracted 39 structured relationships around SciDAVis. Examples in this analysis include SciDAVis → As of → 9 January 2021 and SciDAVis → Available in → 11 languages. The table shows each extracted connection, where it came from and its confidence.
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| SciDAVis | As of | 9 January 2021 | 1.00 | infobox |
| SciDAVis | Available in | 11 languages | 1.00 | infobox |
| SciDAVis | Developers | Miquel Garriga, Arun Narayanankutty, Dmitriy Pozitron, Russell Standish | 1.00 | infobox |
| SciDAVis | License | GNU GPLv2 | 1.00 | infobox |
| SciDAVis | Operating system | Microsoft Windows, OS X, Linux | 1.00 | infobox |
| SciDAVis | Original authors | Tilman Benkert, Knut Franke | 1.00 | infobox |
| SciDAVis | Platform | x86, AMD64 | 1.00 | infobox |
| SciDAVis | Release | 5 August 2007; 19 years ago (2007-08-05) | 1.00 | infobox |
| SciDAVis | Repository | https://github.com/SciDAVis/scidavis | 1.00 | infobox |
| SciDAVis | Size | 42.9 MB (Windows), 86.3 MB (Mac), 9.8 MB (Source code) | 1.00 | infobox |
| SciDAVis | Stable release | 2.9.2 / 16 April 2022; 4 years ago (2022-04-16) | 1.00 | infobox |
| SciDAVis | Type | Data analysis and plotting | 1.00 | infobox |
| SciDAVis | Website | scidavis.sourceforge.net | 1.00 | infobox |
| SciDAVis | Written in | C++, Python | 1.00 | infobox |
The concept neighborhoods around SciDAVis bring nearby vocabulary together. In this analysis, examples include Benkert, Cross-platform and Developers. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
For SciDAVis, one of the stronger structural bridges in this analysis connects SciDAVis with Overview. Bridges highlight paths between different parts of the map and can reveal research angles that are easy to miss in a flat list.
TTTA analyzes the structure around SciDAVis to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as History, Art & Science, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
Source: Wikipedia — SciDAVis · EN edition · Analysis: TopicsToTalkAbout