David Oesch
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
David Oesch has a total of 5 co-authors. Here are the top co-authors by number of shared publications:
- Elia Ferrari
Institute of Geomatics, FHNW University of Applied Sciences and Arts Northwestern Switzerland, 4132 Muttenz, Switzerland
1 shared publication - Fiona Tiefenbacher
Institute of Geomatics, FHNW University of Applied Sciences and Arts Northwestern Switzerland, 4132 Muttenz, Switzerland
1 shared publication - Friedrich Striewski
FHNW University of Applied Sciences and Arts Northwestern Switzerland, Institute Geomatics, Switzerland
1 shared publication - Pasquale Di Donato
Federal Office of Topography Swisstopo, 3084 Wabern, Switzerland
1 shared publication - Pia Bereuter
FHNW University of Applied Sciences and Arts Northwestern Switzerland, Institute of Geomatics, Muttenz, Switzerland
1 shared publication
Latest Publications
- Open Access
- 12 April 2024
- Published by MDPI AG in ISPRS International Journal of Geo-Information
- Vol. 13 (4) , 128
Search Engine for Open Geospatial Consortium Web Services Improving Discoverability through Natural Language Processing-Based Processing and Ranking
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.
- 12 April 2024
- Published by MDPI AG in ISPRS International Journal of Geo-Information
- Vol. 13 (4) , 128
Open AccessSearch Engine for Open Geospatial Consortium Web Services Improving Discoverability through Natural Language Processing-Based Processing and Ranking
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.