Research this topic
Explore the main themes, entities and connections around Skencil. Start with the topic map, then use the sections below for research and deeper semantic analysis.
Explore this topic
Start with a few of the strongest sections from the source topic. These are research directions, not a list of keywords you must use.
History
Overview
Key facts & relationships
High-confidence facts extracted from structured source data. Use them as anchors for further research.
- Available in
- 10+ languages
- Developer
- sK1 Project
- Engine
- Xlib, Tk, Tkinter, PyGTK
- Final release
- 0.6.17 / June 19, 2005; 21 years ago (2005-06-19)
- License
- GNU Library General Public License
- Operating system
- Linux, FreeBSD, Mac OS, Solaris, IRIX, AIX
Topics to explore
A structured outline of related entities, concepts and subtopics. Open any item to build a new map centered on it.Browse the full topic structure. Each item opens a new analysis centered on that subject.
Overview
History
- X11
- Xfig
- Tgif Tgif (program)
- Python Python (programming language)
- Linux
- I386 Intel 80386
- DEC Alpha
- M68k
- PowerPC
- SPARC
- FreeBSD
- Solaris Solaris (operating system)
- IRIX
- AIX AIX operating system
- SK1 Project SK1 (program)
- 64-bit 64-bit computing
- Code.google.com
- GitHub
- WxWidgets
- Fork Fork (software development)
- Color management
- CMYK
- Color space
- Multiple document interface
- Pango
- Cairo Cairo (graphics)
- CorelDRAW
- Tk Tk (software)
- Tkinter
- GTK+
Advanced semantic analysis
Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.
Map overview Semantic statistics
Number of nodes, edges, triples, density and central hubs. Use it to gauge the size and connectivity of the map.Skencil
How this topic connects Entity context
Quick relationship hints grouped by predicate. Useful for spotting recurring semantic connections around the current entity.See the strongest relationship patterns around the current topic before diving into the raw triples.
Skencil
Top relations
Important terminology Word statistics
Frequent words and multi-word phrases across the lead, headings, infobox and body. Useful for terminology coverage.Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.
Important terminology
sketch sk1 project released linux herzog vector graphics editor gnu public github development alpha bernhard release written website org https
Entity relationships Subject–Predicate–Object triples
Extracted RDF-like relationships with confidence and source. The table includes structured facts and lower-confidence contextual relations.| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Skencil | Available in | 10+ languages | 1.00 | infobox |
| Skencil | Developer | sK1 Project | 1.00 | infobox |
| Skencil | Engine | Xlib, Tk, Tkinter, PyGTK | 1.00 | infobox |
| Skencil | Final release | 0.6.17 / June 19, 2005; 21 years ago (2005-06-19) | 1.00 | infobox |
| Skencil | License | GNU Library General Public License | 1.00 | infobox |
| Skencil | Operating system | Linux, FreeBSD, Mac OS, Solaris, IRIX, AIX | 1.00 | infobox |
| Skencil | Original author | Bernhard Herzog | 1.00 | infobox |
| Skencil | Other names | Sketch | 1.00 | infobox |
| Skencil | Platform | IA-32 (i386), DEC Alpha, m68k, PowerPC, SPARC, x86-64 | 1.00 | infobox |
| Skencil | Predecessor | Sketch | 1.00 | infobox |
| Skencil | Preview release | 1.0 rc1 / November 4, 2016; 9 years ago (2016-11-04) | 1.00 | infobox |
| Skencil | Release | October 31, 1998; 27 years ago (1998-10-31) | 1.00 | infobox |
| Skencil | Repository | https://github.com/sk1project/skencil | 1.00 | infobox |
| Skencil | Successor | sK1 | 1.00 | infobox |
| Skencil | Type | Vector graphics editor | 1.00 | infobox |
| Skencil | Website | www.skencil.org | 1.00 | infobox |
| Skencil | Written in | C, Python | 1.00 | infobox |
Related concept clusters Concept neighborhoods
Clusters of nearby vocabulary surrounding the topic. Scan them for adjacent concepts and language you may have missed.These clusters group vocabulary that occurs around closely connected concepts in the source material.
Connections between topic areas Semantic bridges
Bridge nodes connect otherwise separate parts of the map. Expand a row to inspect the topic groups on each side.Bridges can reveal useful research angles that are easy to miss in a flat list of related terms.