A novel model to support OGC Web Services semantic search using OWL-S

Miao, Lizhi; Guo, Jing; Cheng, Wenchao; Zhou, Ya

doi:10.1109/geoinformatics.2016.7578973

Cited by 2 publications

(3 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As it is important for the user to have more relevant results first, instead of using unranked metrics as in other works [9,43], we adopted a ranked metric. For each query, a ground truth order of the results is manually established; then, for the evaluation of the ranking method, the Kendal tau distance [22] is applied (Equations ( 1)-( 3)).…”

Section: Results Rankingmentioning

confidence: 99%

“…Dissimilar to other works [7,8] that focus on the development of a web crawler to discover data on the web, our paper focuses mainly on the semantic augmentation through Natural Language Processing and ranking methods to improve the search results presented to the user. This thematic has been marginally explored in other works, which focus on the generation of web ontologies [9][10][11] or the exploitation of such ontologies to describe and categorize web services [12]. However, all of these approaches rely on models to parse information from well-structured fields retrieved with GetCapabilites.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Search Engine for Open Geospatial Consortium Web Services Improving Discoverability through Natural Language Processing-Based Processing and Ranking

Ferrari,

Striewski,

Tiefenbacher

et al. 2024

IJGI

View full text Add to dashboard Cite

The improvement of search engines for geospatial data on the World Wide Web has been a subject of research, particularly concerning the challenges in discovering and utilizing geospatial web services. Despite the establishment of standards by the Open Geospatial Consortium (OGC), the implementation of these services varies significantly among providers, leading to issues in dataset discoverability and usability. This paper presents a proof of concept for a search engine tailored to geospatial services in Switzerland. It addresses challenges such as scraping data from various OGC web service providers, enhancing metadata quality through Natural Language Processing, and optimizing search functionality and ranking methods. Semantic augmentation techniques are applied to enhance metadata completeness and quality, which are stored in a high-performance NoSQL database for efficient data retrieval. The results show improvements in dataset discoverability and search relevance, with NLP-extracted information contributing significantly to ranking accuracy. Overall, the GeoHarvester proof of concept demonstrates the feasibility of improving the discoverability and usability of geospatial web services through advanced search engine techniques.

show abstract

Section: Results Rankingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Search Engine for Open Geospatial Consortium Web Services Improving Discoverability through Natural Language Processing-Based Processing and Ranking

Ferrari,

Striewski,

Tiefenbacher

et al. 2024

IJGI

View full text Add to dashboard Cite

show abstract

“…Also, we have worked on the semantic search of distributed resources with the implementation of a mapping model for the conversion of the geoservice description information to the value of corresponding tags of the service profile through the web ontology language (OWL) (Miao et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of the response time of a geoservice using a hybrid and distributed database

Treviño-Villalobos

Víquez-Acuña

Quirós-Oviedo

et al. 2022

Rev. colomb. comput.

View full text Add to dashboard Cite

Web mapping services provide information directly to users and other software programs that can consume and produce information. One of the main challenges this type of service presents is improving its performance. Therefore, in this research, a new geoservice integrated into GeoServer was developed, called GeoToroTur, with an OWS implementation of vector layers that consumes the information from a hybrid and distributed database that was implemented with PostgreSQL and MongoDB, making use of ToroDB for document replication. This geoservice was evaluated by executing geographic and descriptive attribute filter queries. Based on the results, we can conclude that the response time for GeoToroTur is shorter than that for Geoserver.

show abstract

A novel model to support OGC Web Services semantic search using OWL-S

Cited by 2 publications

References 6 publications

Search Engine for Open Geospatial Consortium Web Services Improving Discoverability through Natural Language Processing-Based Processing and Ranking

Search Engine for Open Geospatial Consortium Web Services Improving Discoverability through Natural Language Processing-Based Processing and Ranking

Evaluation of the response time of a geoservice using a hybrid and distributed database

Contact Info

Product

Resources

About