PROCESSING CONSERVATION INDICATORS WITH OPEN SOURCE TOOLS: LESSONS LEARNED FROM THE DIGITAL OBSERVATORY FOR PROTECTED AREAS

The European Commission has a commitment to open data and the support of open source software and standards. We present lessons learnt while populating and supporting the web and map services that underly the Joint Research Centre's Digital Observatory for Protected Areas. Challenges include: large datasets with highly complex geometries; topological inconsistencies, compounded by reprojection for equal-area calculations; multiple different representations of the same geographical entities, for example coastlines; licensing requirement to continuously update indicators to respond to monthly changes in the authoritative data. In order to compute and publish an array of indicators, we used a range of open source tools including GRASS, R, python, GDAL, PostGIS, geometry libraries for Hadoop, Geoserver, Geonode, and Mapserver. In addition we assessed the value of the commercial ArcGIS Pro software and the Google Earth Engine platform.
We describe the lessons that we learnt in building and documenting a usable and repeatable workflow,highlighting weak spots and workarounds., Code for our processing workflows will be shared via github and key process flows will be shared via a VRE to allow reproducible research while complying with data redistribution restrictions from the data providers. Our final goal is to move the entire processing chain to open source tools and share it as a versioned resource.