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Article type: Research Article
Authors: Feiring, Birgitte* | Thornberry, Francesca | Hassler, Adrian
Affiliations: Danish Institute for Human Rights, Copenhagen, Denmark
Correspondence: [*] Corresponding author: Birgitte Feiring, The Danish Institute for Human Rights, Wilders Plads 8K, 1403 Copenhagen K, Denmark. E-mail: bife@humanrights.dk.
Note: [1] The Danish Institute for Human Rights is a member of the Global Alliance of National Human Rights Institutions (GANHRI). The present paper was originally prepared for the UN World Data Forum in Cape Town, South Africa, in January 2017.
Abstract: The 2030 Agenda for Sustainable Development is grounded in the principles of international human rights treaties, and the Sustainable Development Goals seek to realize the human rights of all. To ensure accountability to citizens in this process, the availability of quality, timely and reliable disaggregated data will be a critical component of effective Follow-up and Review (FuR) mechanisms that “leave no one behind”. This paper presents an analysis of the global SDG monitoring framework from a human rights perspective. The analysis identifies principal limitations, such as an excess of outcome-oriented indicators, as well as practical constraints, including the limited capacity of National Statistical Offices (NSOs) to provide disaggregated data. The findings suggest that there will be significant data gaps in the monitoring framework for years to come. However, some of the critical gaps can be filled with available data from other sources, including human rights monitoring bodies. This requires building a “pluralistic ecosystem of data” that incorporates data from credible third parties, including citizens and private sector entities. Such an approach has significant potential to enhance the efficiency and sustainability of data collection, and National Human Rights Institutions (NHRIs) can play a facilitating and vetting role.
Keywords: Sustainable Development Goals, human rights monitoring, human rights-based approach to data, data disaggregation, administrative data, official statistics
DOI: 10.3233/SJI-170378
Journal: Statistical Journal of the IAOS, vol. 33, no. 4, pp. 919-942, 2017
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