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Thijs Brentjens's Projects

api icon api

API voor eenvoudig gebruik PDOK en OGC services in websites

geowebcache icon geowebcache

GeoWebCache is a tile caching server implemented in Java that provides various tile caching services like WMS-C, TMS, WMTS, Google Maps, MS Bing and more

geox icon geox

Repository voor het ontwikkelen van een handreiking over het uitwisselen van geometrie.

inspirenl icon inspirenl

A QGIS plugin to search and add Datasets of the Dutch Dataportal 'Nationaal Georegister' to QGIS.

nen3610-linkeddata icon nen3610-linkeddata

Repository voor het werken aan een linked data profiel op NEN3610. De concepttekst is hier te lezen: https://geonovum.github.io/NEN3610-Linkeddata

owslib icon owslib

OWSLib is a Python package for client programming with Open Geospatial Consortium (OGC) web service (hence OWS) interface standards, and their related content models.

pdokkaart icon pdokkaart

Home en instellingen pagina voor PDOK Kaart, zie ook Lucs API.

pygeoapi icon pygeoapi

pygeoapi provides an API to geospatial data

rdflib icon rdflib

RDFLib is a Python library for working with RDF, a simple yet powerful language for representing information.

respec icon respec

A tool for creating technical documents and web standards

sheetjs icon sheetjs

:green_book: SheetJS Community Edition -- Spreadsheet Data Toolkit

soapui icon soapui

SoapUI is a free and open source cross-platform functional testing solution for APIs and web services.

stetl icon stetl

Stetl, Streaming ETL, is a lightweight, geospatial ETL framework. Stetl uses existing transformation tools like GDAL/OGR and XSLT and is glued through Python. A config file specifies an ETL chain of modules. Stetl is speed-optimized by using native calls like ogr2ogr, libxml and libxslt (via lxml). Stetl is in particularly meant in ETL cases where either ogr2ogr or XSLT alone is not sufficient. This mostly involves schema transformations as required for INSPIRE and local GML-based complex datasets. Stetl has proven to be able to handle 10's of millions of features/records through a technique dubbed "gml-splitting" (and outputting into a deegree blobstore, which could be dubbed "gml-spitting").

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