Publicaties

2022

Interoperability and Integration: An Updated Approach to Linked Data Publication at the Dutch Land Registry: Rowland, A., Folmer, E., Beek, W., & Wenneker, R. (2022). ISPRS international journal of geo-information, 11(1), [51], online toegang.
Formalisation of code lists and their values - The case of ISO 19152 Land Administration Domain Model: Kara, A., Rowland, A., van Oosterom, P., Stubkjær, E., Çağdaş, V., Folmer, E., Lemmen, C., Quak, W., Meggiolaro, L. (2022). In Proceedings of the 10th Land Administration Domain Model Workshop (LADM2022), online toegang.

Demo: GeoDataWizard for linked spatial data creation: Rowland, A., Overeem, J., & Folmer, E. (2021). In: Proceedings of the 4th International Workshop on Geospatial Linked Data (GeoLD 2021) (pp. 13-17). (CEUR workshop proceedings; Vol. 2977), online toegang.
Spatial linked data in Europe: Report from spatial linked data sessions at knowledge graph in action: Bucher, B., Folmer, E., Brennan, R., Beek, W., Hbeich, E., Würriehausen, F., Rowland, L., Maturana, R. A., Alvarado, E., Buyle, R., & Di Donato, P. (2021). (73 ed.) (Official Publication - EuroSDR; No. 73), online toegang.

Towards Self-Service GIS - Combining the Best of the Semantic Web and Web GIS: Alexandra Rowland, Erwin Folmer, Wouter Beek. In: ISPRS International Journal of Geo-Information, Vol 9, No. 12, 2020, online toegang.

Kadaster Knowledge Graph: Beyond the Fifth Star of Open Data: Stanislav Ronzhin, Erwin Folmer, Pano Maria, Marco Brattinga, Wouter Beek, Rob Lemmens, Rein van’t Veer. In: Information, Vol. 10, No. 10, online toegang.
Enhancing the Usefulness of Open Governmental Data with Linked Data Viewing Techniques: Erwin Folmer, Wouter Beek, Laurens Rietveld, Stanislav Ronzhin, Rutger Geerling, Davey den Haan. In: Proceedings of the 52^nd Hawaii International Conference on System Sciences, 2019, online toegang.
Machine Learning for Geospatial Vector Data: Rein van ‘t Veer, Peter Bloem, Erwin Folmer. In: Deep Learning for Classification Tasks on Geospatial Vector Polygons, arXiv preprint arXiv:1806.03857, online toegang.

Linked Data Viewing as part of the Spatial Data Platform of the Future: Erwin Folmer, Wouter Beek, Laurens Rietveld. In: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. 42, No. 4, 2018, pp. 49-52, online toegang.
Adding 3D GIS Visualization and Navigation to the SPARQL Query Loop: Wouter Beek, Erwin Folmer, Laurens Rietveld, Tony Baving, Vincent Van Altena. In: International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences, Vol. 42, 2018, online toegang.

Kadaster Data Platform ― Overview Architecture: Erwin Folmer, Wouter Beek. In: Free and Open Source Software for Geospatial (FOSS4G) Conference Proceedings, Vol. 17, No. 1, 2017, online toegang.
An Integrated Approach for Linked Data Browsing: Wouter Beek, Erwin Folmer. In: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2017, pp. 35-38, online toegang.
GeoYASGUI: The GeoSPARQL Query Editor and Result Set Visualizer: Wouter Beek, Erwin Folmer, Laurens Rietveld, John Walker. In: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2017, pp. 39-42, online toegang.

Business Rationale for Linked Data at Governments: a case study at the Netherlands’ Kadaster Data Platform: Erwin Folmer, Stanislav Ronzhin, Jos Van Hillegersberg, Wouter Beek, Rob Lemmens. 2015. In: Access, online toegang.

Brainstorm Document Machine Learning & Kadaster: In het kader van zijn onderzoek heeft Rein van ‘t Veer een document opgesteld met onderwerpen waar machine learning op geodata een bijdrage kan leveren.