As national statistics offices identify the gaps in the data they collect and what is necessary to effectively monitor progress towards national plans and the SDGs, there is demand for mechanisms to effectively integrate non-official or non-national level datasets into indicators useable at the national scale. The process of data reconciliation, which stitches together multiple related datasets, can increase the efficiency and achieve a level of specificity hitherto unavailable to most statistics offices. SDSN TReNDS is exploring the ways in which data reconciliation can be applied as a method to address data gaps across disparate sectors (urban economic growth, water quality and access) and stakeholder scenarios (multi-lateral and bi-lateral data sharing agreements). With funding from the Hewlett Foundation and support from SDSN and in-country partners are working together to co-design an open-source platform for such exchange.
In the Colombia pilot project, a joint effort involves CEPEI, the Bogota Chamber of Commerce, and the Colombian national statistics office (DANE) to reconcile sub-national economic development data with national indicators for SDG 11 and SDG 5. DANE is particularly interested in the project as a pilot platform by which to collect urban datasets and integrate them into their national statistics, with intended use for other sectors and with other partners.
In the Bangladesh research project, Oxford University Scholar Alexander Fischer investigated the utility of data reconciliation for SDG 6 data in Bangladesh. By reviewing the many sources of data relating to access to quality and affordable water supply, Fischer created a set of recommendations for how to assess data gaps and a framework for when data reconciliation is the most effective and efficient tool. Read his full report here.