Integrating Land Data Sets : Towards Inclusive Land Information Systems

Paul Saers, Mathilde Molendijk & Co Meijer

How can third party data contribute to inclusive land administration (LA)? Entities tasked with formal land registration often lack the capacity to provide the required service levels to their clients and additionally face huge backlogs and gaps in territorial coverage. On the other hand service expectations rise among the client community at levels of the individual citizen, local community, government and at even global level. As countries develop at an increasingly faster rate, the need for multipurpose LA services grows fast. How can existing LA institutes respond adequately to this wide range of new purposes for their land data, while still struggling with inadequate capacity and outdated regulatory frameworks, with budget shortages, backlogs, limited territorial coverage and multipurpose application of their land data? The answer is obviously in accepting and adopting data from third parties. Who are these parties? They may be citizens using participative, self-service or volunteered data, para-specialists trained for the para-surveyor and paralegal role, Non-Governmental Organisations (NGO’s), Global entities such as MCA or GLTN, private enterprises, traditional trusted third parties such as notaries and licenced surveyors and government entities such as Ministries or Agencies. What does it take to ensure third party data is compatible, interoperable, and has the right quality for the respective purposes? How can government efficiency be increased with the collect-once-use-many concept? This paper explores the potential and requirements from third party data to accelerate the introduction of inclusive land data and bring the benefits of good land administration to as many people as possible in the shortest time necessary.

Event: Responsible Land Governance : Towards an Evidence Bases Approach : Annual World Bank Conference on Land and Poverty

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Document type:Integrating Land Data Sets : Towards Inclusive Land Information Systems (1911 kB - pdf)