Situation-Dependent Data Quality Analysis for Geospatial Data Using Semantic Technologies

Homburg, Timo; Boochs, Frank

doi:10.1007/978-3-030-04849-5_49

Cited by 6 publications

(8 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To define the quality of a given data set for a given application case, an often prioritized set of data quality metrics needs to be evaluated, a common data quality score needs to be defined, and finally interpreted to be able to result in an informative data quality statement. Reference [27] suggests that these data quality definitions and the requirements associated with a data quality statement may be modeled in an ontology model. Clearly, a goal of capturing metadata is to infer information about the quality of the respective 3D scan, therefore our ontology model should allow for the definition of data quality statements.…”

Section: Quality Is the Degree To Which A Set Of Inherent Characteristics Fulfills Requirementsmentioning

confidence: 99%

Metadata schema and ontology for capturing and processing of 3D cultural heritage objects

et al. 2021

Self Cite

View full text Add to dashboard Cite

Motivated by the increased use of 3D acquisition of objects by cultural heritage institutions, we were investigating ontologies and metadata schemes for the acquisition process to provide details about the 3D capturing, which can be combined with preexisting ontologies describing an object. Therefore we divided the 3D capturing workflow into common steps starting with the object being placed in front of a 3D scanner to preparation and publication of the 3D datasets and/or derived images. While the proposed ontology is well defined on a coarse level of detail for very different techniques, e.g. Stucture from Motion and LiDAR we elaborated the metadata scheme in very fine detail for 3D scanners available at our institutions. This includes practical experiments with measurement data from past and current projects including datasets published at Zenodo as guiding examples and the source code for their computation. Additionally, the free and Open Source GigaMesh Software Framework’s analysis and processing methods have been extended to provide metadata about the 3D processing steps like mesh cleaning as well as 2D image generation. Finally, we discuss the current limitations and give an outlook about future extensions.

show abstract

Section: Quality Is the Degree To Which A Set Of Inherent Characteristics Fulfills Requirementsmentioning

confidence: 99%

Metadata schema and ontology for capturing and processing of 3D cultural heritage objects

et al. 2021

Self Cite

View full text Add to dashboard Cite

show abstract

“…represent the fitness for use. For this purpose we follow (Homburg and Boochs, 2019) to define a requirement profile to define a good/acceptable Stolperstein representation as defined in Table 1.…”

Section: Requirement Profilementioning

confidence: 99%

“…if the quality of the data sources is sufficient enough to support a certain use case. Data quality is commonly measured using data quality metrics customized for a specific use case (Homburg and Boochs, 2019) to quantify the fitness for use of the respective data set. We would like to test the fitness for use of (linked) open data sources representing Stolpersteine (Franke and Demnig, 2009), stones commemorating Jewish victims of the second world war in three similar-sized cities of Germany.…”

Section: Introductionmentioning

confidence: 99%

Evaluating linked data location based services using the example of Stolpersteine

Homburg

Böhm

Bruhn

et al. 2019

Adv. Cartogr. GIScience Int. Cartogr. Assoc.

Self Cite

View full text Add to dashboard Cite

Abstract. In this publication we introduce a linked data powered application which assists users to find so-called Stolpersteine, stones commemorating Jewish victims of the second world war. We show the feasibility of a dedicated location based service as an app using linked data resources and evaluate this approach against local data sources gathered by communities to find out if the current linked data environment can equally and/or sufficiently support an application in this knowledge domain.

show abstract

“…In addition to quality management with OWL, SWRL rules are used in several studies for quality assessment process. (Wang et al, 2005); (Cheng et al, 2008); (Keßler et al, 2009); (Zhu, 2013); (Cherfi et al, 2017); (Varadharajulu et al, 2017); (Mobasheri, 2017); (Homburg and Boochs, 2019) can be given as example. Wang et al (2005) developed a system to detect inconsistent spatial data with the help of SWRL rules in a specific domain.…”

Section: Introductionmentioning

confidence: 99%

“…Wang et al (2005) developed a system to detect inconsistent spatial data with the help of SWRL rules in a specific domain. Homburg and Boochs (2019), Varadharajulu et al (2017), and Mobasheri (2017) propose rule-based approaches including SWRL rules for domain dependent solutions. Varadharajulu et al (2017) design a framework to check the consistency of the transportation data against the rules that are created with SWRL.…”

Section: Introductionmentioning

confidence: 99%

Sdqo and Sfo, Ontologies for Spatial Data Quality Assessment

Yılmaz¹,

Cömert²,

Yıldırım³

2019

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

View full text Add to dashboard Cite

Spatial quality assessment is based on the conformance of data to its specifications or fitness for users' purpose. These specifications and the users' purposes include the rules and constraints that a dataset should comply with. Assessing the compliance of data to the rules is still an active research subject and rule-based approach is the common method. For the efficient rule-based system implementation, it is desired to automate assessment process with a domain-independent and web-based approach. Reasoning capability and re-usability of semantic web components are expected to promote efficient implementation. In literature, many domains such as agriculture, music, Linked Data and geospatial domain etc. apply ontology-based methods for quality management. There is a need to model geospatial quality concepts and rules in a domain-independent way to automate the quality management process. In our model of rule formalism, we use Web Ontology Language (OWL) and Semantic Web Rule Language (SWRL). We devise two types of ontologies. These are; the specification ontologies (SfO) and the Spatial Data Quality Ontology (SDQO). SfO is to be created by domain experts/users to define rules according to specifications. SDQO is responsible with quality assessment; it is domain independent and makes assessment based on the rules defined by any SfO for the related domain. The quality elements are domain and toposemantic consistency that assessed by SWRL. In this paper, the design considerations of the ontologies for quality assessment are explained with an example.

show abstract

Situation-Dependent Data Quality Analysis for Geospatial Data Using Semantic Technologies

Cited by 6 publications

References 21 publications

Metadata schema and ontology for capturing and processing of 3D cultural heritage objects

Metadata schema and ontology for capturing and processing of 3D cultural heritage objects

Evaluating linked data location based services using the example of Stolpersteine

Sdqo and Sfo, Ontologies for Spatial Data Quality Assessment

Contact Info

Product

Resources

About