# Ontology-Based Spatial Data Quality Assessment Framework
## 1 Introduction
In the Prolog section, inconsistency rules are implemented to identify sources of data inconsistencies. [PERSON] et al. [8] used SWRL for spatial data quality assessment and drew attention to the need for further development of ontology models and rule description languages to support spatial rules. This research investigated data validation in situ, while collecting and entering data from the field using mobile devices. The studies [7; 8] are domain dependent. Our study investigates data quality assessment of spatial data according to their specifications. In the central ontology part, SWRL rules follow OWA. Reusability and robustness against ontological inconsistency identifying the root of the problem are prime aspects in our study. For semantic sensor networks and the related quality aspects, [PERSON] [20] created a design pattern and used SWRL to infer quality results. A system for context-based spatial information retrieval using spatial functions and SWRL was proposed by [13]. It introduced a mechanism for querying real-time sensor data during rule execution, making Geographic Information Retrieval systems more adaptable to the dynamic nature of user contexts and environmental changes. It demonstrates how SWRL can be applied to model user preferences and retrieve context-aware geographical information. Although this study is not directly related to quality assessment, it is an example of the use of SWRL rules in context-based applications. Furthermore, there are studies using SWRL for quality assessment in health and music domains [6; 21]. [PERSON] et al. [22] proposed a system validating the acceptability of recommended street names against existing rules in the regulation using SWRL rules. The main goal of the study was to leverage SWRL to automate tasks related to spatial transactions, such as updating, managing, or validating geospatial data. The use of SWRL helps create flexible, rule-based systems that ensure the correct handling of spatial data in accordance with predefined rules. The system has rules only for the applied domain and for attribute tests. The system lacks support for topo-semantic rules and does not include a component that enables users to create rules without requiring specialized expertise, a capability that our system provides. [PERSON] and [PERSON] [19] propose a system based on ontologies and SPARQL queries to check the spatial compliance of underground utilities with required regulations. To achieve this, they designed four ontologies specific to underground utilities. These are utility product ontology, transportation object ontology, geometry ontology, and utility spatial rule ontology. These ontologies standardize the way data are represented, ensuring that heterogeneous data sources (geospatial utility data and textual regulations) are uniformly interpreted. The proposed system is domain specific but can be extendible to apply to different domains with remodeling. The specification rules for the domain are extracted with the help of a text and data converter. In our system, this is done by the SfO creation phase with a domain expert. [PERSON] [16] proposed an ontology-based framework to evaluate the \"fitness for use\" of thematic map data by modeling user requirements. The study proposes a framework containing ontologies for a thematic map, requirement profile, and data quality. SWRL and SPARQL are used as well to make inference with the constraints that were modeled in the study. While this study focuses on the \"fitness for use\" quality element for spatial data, our study focuses on logical consistency and topo-semantic quality element assessment. [PERSON] [14] presented a method to assess OSM data quality in terms of completeness quality element, using SQWRL rules to contribute information extraction from the existing database. Its aim is to calculate and create the non-existing spatial information from the existing spatial data. For this purpose, the study creates three levels of ontologies and mappings between them.