A code list in Unified Modeling Language (UML), a simple list of values without any structure, can be employed as a simple data type to further capture the semantics of a domain. The code list values as used in international standards (e.g. ISO and OGC) are generally presented without definition, reference to the source of a definition, multi-lingual alternative term support and semantic relationships (e.g. hierarchical, associative). Moreover, managing, implementing, and maintaining UML code lists can be considered as a difficult task since they generally do not provide structured and semantically enriched values. This is also true in the case of ISO 19152:2012 Land Administration Domain Model (LADM), which is currently under systematic review and adding more content, meaning and structure to code list values could be considered an improvement. In last decade, there is a growing interest in representing terms as well as code list values using Semantic Web technologies (e.g. RDF, OWL, SKOS, SPARQL) and making them available on a registry (e.g. ISO/TC211 Geolexica, OGC Definitions Server, INSPIRE code list register, BARTOC), including land administration domain (e.g. CaLAThe, LandVoc). However, there is no joint understanding in structuring, extending and maintaining code list values, which may be achieved through an agreed metamodel. Such a metamodel should also provide insight into content, localisation (multi-lingual support), versioning and implementation. The aim of this study is to propose a framework (basically a metamodel) for structuring, extending, maintaining and implementing semantically enriched code lists, and to discuss the application of the proposed framework to be included in the revision of LADM. To achieve this aim, the requirements for refined code list values are firstly collected considering existing thesauri, vocabularies and standards. Subsequently, a metamodel is proposed for the refined code list. The proposed metamodel is applied to a code list of LADM as well as a part of a selected country profile.@en

3D environments allow advanced spatial navigation and visualization, but have traditionally provided limited support for performing non-spatial data analysis operations like filtering, joining, and integrating data on-the-fly. Linked Open Data provides advanced support for performing filters and joins over datasets that can be dynamically combined through SPARQL federation. Unfortunately, Linked Data results often lack intuitive visualization capabilities, making it relatively difficult to interpret the data for a data analyst. In this paper we present our integration of 3D visualization into the read-evaluate-print-loop of SPARQL query execution. We show how the inclusion of 3D visualization has concrete benefits for the SPARQL query writing process, and how our integrated solution is used to answer specific use cases that could not be answered before.@en