BURUNDI: OSM intrinsic completeness by discrete classification


FAIR Overall Score

77%

Abstract

OpenStreetMap intrinsic complete analysis by discrete classification of its collines using terrain ruggedness and gridded population estimates as auxiliary predictors.

Keywords

Africa, bdi_osm_discr_class, completeness, features, intrinsic, osm

Supplemental information

"High" and "low" in the data mean either greater than 3rd quartile or lower than 1st quartile of the sample data.

Public Domain (PD): Works in the public domain may be used freely without the permission of the former copyright owner. (http://www.copyright.gov/help/faq/faq-definitions.html)

Contact for resource

Eurac Research - Center for Climate Change and Transformation
piero.campalani@eurac.edu
Bolzano, ITA

Contact for metadata

Eurac Research - Center for Climate Change and Transformation
piero.campalani@eurac.edu
Bolzano, ITA

Download online resources


FAIR Overall Score: 77%

Principle Score Earned Level
Findable 57% 4 of 7 moderate
Accessible 100% 7 of 7 advanced
Interoperable 67% 4 of 6 moderate
Reusable 83% 5 of 6 moderate

Assessed 2026-07-22 (metrics 0.8)

Evaluated by F-UJI web service: Anusuriya Devaraju, & Robert Huber. (2020). F-UJI - An Automated FAIR Data Assessment Tool. Zenodo. https://doi.org/10.5281/zenodo.6361400


# Name Description Link Date published Category
1 Maps web services URLs Here you can find all the available web service URLs provided by Maps, to consume datasets through an interoperable client (QGIS, Python, etc.) or to develop codes for analysis. The most relevant services to access datasets are: WMS (Web Map Service) to visualize layers in a map and to query them); WFS (Web Feature Service) or WCS (Web Coverage Service) to download raw datsets and use them for deep analysis or transformation. Link Dec. 13, 2021 Maps
2 maps.eurac.edu documentation maps.eurac.edu is based on Geonode, here the link to the official documentation Link April 28, 2021 Maps