Norwegian State of Estate Report as Linked Open Data

PurposeThis study aimed to develop a taxonomy of research areas in open government data (OGD) through a bibliometric mapping tool and a qualitative analysis software.Design/methodology/approachIn this study, the authors extracted metadata of 442 documents from a bibliographic database. The authors used a bibliometric mapping tool for familiarization with the literature. After that, the authors used qualitative analysis software to develop taxonomy.FindingsThis paper developed taxonomy of OGD with three research areas: implementation and management, architecture, users and utilization. These research areas are further analyzed into seven topics and twenty-eight subtopics. The present study extends Charalabidis et al. (2016) taxonomy by adding two research topics, namely the adoption factors and barriers of OGD implementations and OGD ecosystems. Also, the authors include artificial intelligence in the taxonomy as an emerging research interest in the literature. The authors suggest four directions for future research: indigenous knowledge in open data, open data at local governments, development of OGD-specific theories and user studies in certain research themes.Practical implicationsEarly career researchers and doctoral students can use the taxonomy to familiarize themselves with the literature. Also, established researchers can use the proposed taxonomy to inform future research. Taxonomy-building procedures in this study are applicable to other fields.Originality/valueThis study developed a novel taxonomy of research areas in OGD. Taxonomy building is significant because there is insufficient taxonomy of research areas in this discipline. Also, conceptual knowledge through taxonomy creation is a basis for theorizing and theory-building for future studies.

show abstract

“…For example, Hitz-Gamper et al . (2019) and Shi et al . (2017) proposed strategies to support LOD for data discoverability.…”

Section: Resultsmentioning

confidence: 96%

Towards a taxonomy of research areas in open government data

Mohamad¹,

Sylvester

Campbell‐Meier

2023

OIR

View full text Add to dashboard Cite

show abstract

“…Strategies to support linked open data are investigated [44]. Experiences on LOD practices in some countries are shared [45]. Research on the semantic web involves integrating machine learning and cloud computing for data recommendations on OGD platforms [46].…”

Section: Linked Open Data (Lod) and Semantic Web -mentioning

confidence: 99%

Towards A Taxonomy of Emerging Topics in Open Government Data: A Bibliometric Mapping Approach

Mohamad¹,

Sylvester²,

Campbell‐Meier³

2022

Proceedings of the Annual Hawaii International Conference on System Sciences

View full text Add to dashboard Cite

The purpose of this paper is to capture the emerging research topics in Open Government Data (OGD) through a bibliometric mapping approach. Previous OGD research has covered the evolution of the discipline with the application of bibliometric mapping tools. However, none of these studies have extended the bibliometric mapping approach for taxonomy building. Realizing this potential, we used a bibliometric tool to perform keyword analysis as a foundation for taxonomy construction. A set of keyword clusters was constructed, and qualitative analysis software was used for taxonomy creation. Emerging topics were identified in a taxonomy form. This study contributes towards the development of an OGD taxonomy. This study contributes to the procedural realignment of a past study by incorporating taxonomy building elements for taxonomy creation. These contributions are significant because there is insufficient taxonomy research in the OGD discipline. The taxonomy building procedures extended in this study are applicable to other fields.

show abstract

“…In Finland, the National Land Survey piloted the delivery of geographic name data, authoritative data, and building data as linked data [23]. In Norway, Kartverket also released some geospatial datasets as linked data [24]. A recent report summarized and reflected on the development of geospatial linked data in the Netherlands, Finland, Norway, and Spain.…”

Section: Geospatial Semantic Web and Linked Datamentioning

confidence: 99%

Assessment and Benchmarking of Spatially Enabled RDF Stores for the Next Generation of Spatial Data Infrastructure

Huang

Raza

Mirzov

et al. 2019

IJGI

View full text Add to dashboard Cite

Geospatial information is indispensable for various real-world applications and is thus a prominent part of today’s data science landscape. Geospatial data is primarily maintained and disseminated through spatial data infrastructures (SDIs). However, current SDIs are facing challenges in terms of data integration and semantic heterogeneity because of their partially siloed data organization. In this context, linked data provides a promising means to unravel these challenges, and it is seen as one of the key factors moving SDIs toward the next generation. In this study, we investigate the technical environment of the support for geospatial linked data by assessing and benchmarking some popular and well-known spatially enabled RDF stores (RDF4J, GeoSPARQL-Jena, Virtuoso, Stardog, and GraphDB), with a focus on GeoSPARQL compliance and query performance. The tests were performed in two different scenarios. In the first scenario, geospatial data forms a part of a large-scale data infrastructure and is integrated with other types of data. In this scenario, we used ICOS Carbon Portal’s metadata—a real-world Earth Science linked data infrastructure. In the second scenario, we benchmarked the RDF stores in a dedicated SDI environment that contains purely geospatial data, and we used geospatial datasets with both crowd-sourced and authoritative data (the same test data used in a previous benchmark study, the Geographica benchmark). The assessment and benchmarking results demonstrate that the GeoSPARQL compliance of the RDF stores has encouragingly advanced in the last several years. The query performances are generally acceptable, and spatial indexing is imperative when handling a large number of geospatial objects. Nevertheless, query correctness remains a challenge for cross-database interoperability. In conclusion, the results indicate that the spatial capacity of the RDF stores has become increasingly mature, which could benefit the development of future SDIs.

show abstract

Norwegian State of Estate Report as Linked Open Data

Cited by 9 publications

References 7 publications

Towards a taxonomy of research areas in open government data

Towards a taxonomy of research areas in open government data

Towards A Taxonomy of Emerging Topics in Open Government Data: A Bibliometric Mapping Approach

Assessment and Benchmarking of Spatially Enabled RDF Stores for the Next Generation of Spatial Data Infrastructure

Contact Info

Product

Resources

About