This indicator presents the score of the "Land Owership" component of the Global Open Data Index (GODI) 2016/2017.
The "Land Ownership" component of the GODI was jointly assessed by Open Knowledge International - OKI and Cadasta Foundation.
The main idea in this specific case is that data should include maps of lands with parcel layer that displays boundaries in addition to a land registry with information on registered parcels of land. The Index focuses on assessing open land tenure data (describing the rules and processes of land property). In particular, "Land Ownership" was assessed against 6 criteria:
- Openly licenced - Is the data openly licensed/in public domain? (20 points)
- Open and machine readable format - Is the data in open and machine-readable file formats? (20 points)
- Downloadable at once - Is the data downloadable at once? (15 points)
- Up-to-date - Is the data up-to-date? (15 points)
- Publicly available - Is the data available online without the need to register or request access to the data? (15 points)
- Free of charge - Is the data available free of charge? (15 points)
The GODI Index looks at specific data using specific survey questions. The result is a final score that has to be read carefully. Behind fairly high scores we often do not find open data, but access-controlled data, or public data in poorly structured, or not machine-readable formats. The score, therefore, does not show a linear increase of openness. Instead, it highlights areas where the government may improve open data publication. Only 100% means that the data is open.
For more information please visit http://cadasta.org/open-data/overview-of-property-rights-data/ or https://index.okfn.org/dataset/land/ .
The methodology used in the Global Open Data Index has changed over time; significantly so between 2015 and 2016. For this reason, the results are not directly comparable over time and this is why we only included results for the most recent wave of GODI (2016/2017). Previous rounds are available at https://index.okfn.org/dataset/land/.
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