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Amrum (German pronunciation: ⓘ; Öömrang North Frisian: Oomram) is one of the North Frisian Islands on the German North Sea coast, south of Sylt and west of Föhr. It is part of the Nordfriesland district in the federal state of Schleswig-Holstein and has approximately 2,300 inhabitants.
The analysis highlights History, Geography, Culture and Economy as prominent areas in the source structure around Amrum.
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 Amrum shows recurring relationship patterns in the source. For example, Amrum → Amrum's, Both, During, Europe's, Föhr, Germany, In, Including, Kniepsand, Nebel, Norddorf, Nordfriesland, North, North Sea, Northward, Odde, On, Polish, Saalian, Siatler Another extracted example is Amrum → Additionally, Amrum's, Arctic, Birdlife, December, Eurasian, Friedrichskoog, Germany, Heligoland, In, In January, It, January, Like, Moreover, National Park, North Sea, Occasionally, Schleswig-Holstein, She. 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.
sea island amrum's north area föhr frisian population dunes species part also found many wittdün still coast german öömrang sylt
TTTA extracted 180 structured relationships around Amrum. Examples in this analysis include Amrum → Archipelago → North Frisian Islands and Amrum → Area → 20.46 km2 (7.90 sq mi). The table shows each extracted connection, where it came from and its confidence.
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Amrum | Archipelago | North Frisian Islands | 1.00 | infobox |
| Amrum | Area | 20.46 km2 (7.90 sq mi) | 1.00 | infobox |
| Amrum | Coordinates | .mw-parser-output .geo-default,.mw-parser-output .geo-dms,.mw-parser-output .geo-dec{display:inline}.mw-parser-output .geo-nondefault,.mw-parser-output .geo-multi-punct,.mw-pars… | 1.00 | infobox |
| Amrum | District | Nordfriesland | 1.00 | infobox |
| Amrum | Ethnic groups | Germans, Frisians | 1.00 | infobox |
| Amrum | Highest elevation | 32 m (105 ft) | 1.00 | infobox |
| Amrum | Highest point | Siatler | 1.00 | infobox |
| Amrum | Location | Wadden Sea | 1.00 | infobox |
| Amrum | Major islands | Sylt, Föhr, Amrum | 1.00 | infobox |
| Amrum | Pop. density | 111/km2 (287/sq mi) | 1.00 | infobox |
| Amrum | Population | 2,354 (2013) | 1.00 | infobox |
| Amrum | State | Schleswig-Holstein | 1.00 | infobox |
| Amrum | is a | refuge for many species of birds and a number of marine mammals including the grey seal and harbour porpoise.Settlements on Amrum have been traced back to the Neolithic period w… | 0.90 | text |
The concept neighborhoods around Amrum bring nearby vocabulary together. In this analysis, examples include Sea, Germany and Föhr. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
For Amrum, one of the stronger structural bridges in this analysis connects Amrum with Flora and fauna. 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 Amrum to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as History, Geography, Culture & Economy, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
Source: Wikipedia — Amrum · EN edition · Analysis: TopicsToTalkAbout