S-100 feature catalogue framework
E406458
The S-100 feature catalogue framework is a standardized model and methodology developed by the IHO for defining, organizing, and encoding geospatial features and attributes in modern hydrographic and marine information products.
All labels observed (5)
| Label | Occurrences |
|---|---|
| S-100 data encoding formats | 1 |
| S-100 feature catalogue | 1 |
| S-100 feature catalogue framework canonical | 1 |
| S-100 portrayal and encoding rules | 1 |
| S-100 portrayal framework | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T4000249 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: S-100 feature catalogue framework Context triple: [S-101, uses, S-100 feature catalogue framework]
-
A.
The Structure of Appearance
The Structure of Appearance is a 1951 philosophical work by Nelson Goodman that develops a rigorous nominalist system for analyzing the structure of experience and phenomenal qualities.
-
B.
Object Modeling Technique
Object Modeling Technique (OMT) is an early object-oriented analysis and design methodology that introduced structured notations for modeling systems, helping lay the groundwork for what became the Unified Modeling Language (UML).
-
C.
Kanade–Lucas–Tomasi feature tracker
The Kanade–Lucas–Tomasi feature tracker is a widely used computer vision algorithm for robustly tracking distinctive image features across video frames, building on the Lucas–Kanade optical flow method with Tomasi’s feature selection criteria.
-
D.
Objectory
Objectory is an object-oriented software development methodology created by Ivar Jacobson that introduced use cases and significantly shaped modern modeling approaches later incorporated into UML.
-
E.
Simple Knowledge Organization System
The Simple Knowledge Organization System (SKOS) is a W3C standard model for representing and sharing knowledge organization systems such as thesauri, classification schemes, and taxonomies on the Semantic Web.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: S-100 feature catalogue framework Target entity description: The S-100 feature catalogue framework is a standardized model and methodology developed by the IHO for defining, organizing, and encoding geospatial features and attributes in modern hydrographic and marine information products.
-
A.
The Structure of Appearance
The Structure of Appearance is a 1951 philosophical work by Nelson Goodman that develops a rigorous nominalist system for analyzing the structure of experience and phenomenal qualities.
-
B.
Object Modeling Technique
Object Modeling Technique (OMT) is an early object-oriented analysis and design methodology that introduced structured notations for modeling systems, helping lay the groundwork for what became the Unified Modeling Language (UML).
-
C.
Kanade–Lucas–Tomasi feature tracker
The Kanade–Lucas–Tomasi feature tracker is a widely used computer vision algorithm for robustly tracking distinctive image features across video frames, building on the Lucas–Kanade optical flow method with Tomasi’s feature selection criteria.
-
D.
Objectory
Objectory is an object-oriented software development methodology created by Ivar Jacobson that introduced use cases and significantly shaped modern modeling approaches later incorporated into UML.
-
E.
Simple Knowledge Organization System
The Simple Knowledge Organization System (SKOS) is a W3C standard model for representing and sharing knowledge organization systems such as thesauri, classification schemes, and taxonomies on the Semantic Web.
- F. None of above. chosen
Statements (46)
| Predicate | Object |
|---|---|
| instanceOf |
geospatial data standard framework
ⓘ
hydrographic information model ⓘ |
| aimsTo |
facilitate multi-domain marine data integration
ⓘ
support future expansion of hydrographic data domains ⓘ |
| appliesTo |
ECDIS and other navigation systems
ⓘ
hydrographic offices ⓘ marine GIS systems ⓘ |
| basedOn |
ISO 19100 series of geographic information standards
ⓘ
linked to:
ISO 19100 series
ISO 19110 Methodology for Feature Cataloguing ⓘ
linked to:
ISO 19100 series
|
| defines |
rules for attribute types
ⓘ
rules for code lists and enumerations ⓘ rules for feature associations ⓘ rules for feature relationships ⓘ rules for feature types ⓘ rules for information types ⓘ rules for portrayal-related attributes ⓘ structure of feature catalogues ⓘ |
| developedBy | International Hydrographic Organization ⓘ |
| domain |
hydrography
ⓘ
marine navigation ⓘ marine spatial data infrastructures ⓘ |
| enables |
consistent encoding of hydrographic features
ⓘ
data interoperability across S-100 products ⓘ harmonization of feature definitions ⓘ machine-readable feature catalogues ⓘ |
| governedBy | IHO S-100 standard maintenance process ⓘ |
| hasComponent |
attribute type definitions
ⓘ
constraints and rules for feature use ⓘ feature association definitions ⓘ feature type definitions ⓘ information type definitions ⓘ |
| hasPurpose |
define geospatial features and attributes for hydrographic products
ⓘ
support modern electronic navigational and marine information products ⓘ |
| partOf | IHO S-100 Universal Hydrographic Data Model ⓘ |
| relatedTo |
S-100 data encoding formats
ⓘ
linked to:
S-100 feature catalogue framework
S-100 metadata framework ⓘ S-100 portrayal framework ⓘ
linked to:
S-100 feature catalogue framework
|
| supports |
S-100 based product specifications
ⓘ
interoperable marine geospatial data ⓘ |
| supportsEncoding |
GML
ⓘ
XML ⓘ |
| usedIn |
electronic navigational chart products
ⓘ
hydrographic survey data products ⓘ marine information overlays ⓘ maritime safety information products ⓘ other S-100 based marine geospatial datasets ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: S-100 feature catalogue framework Description of subject: The S-100 feature catalogue framework is a standardized model and methodology developed by the IHO for defining, organizing, and encoding geospatial features and attributes in modern hydrographic and marine information products.
Referenced by (5)
Full triples — surface form annotated when it differs from this entity's canonical label.
linked to: S-100 feature catalogue framework
linked to: S-100 feature catalogue framework
linked to: S-100 feature catalogue framework
S-124 Navigational Warnings product specification
→
basedOnConcept
→
S-100 portrayal and encoding rules
ⓘ
linked to: S-100 feature catalogue framework