Please note this website is being phased out.
The Global Data Facility is the new World Bank-hosted innovative global funding instrument for the world's most critical data impact opportunities. For the latest updates, visit our new website at www.worldbank.org/global-data-facility.
ECASTAT is a programmatic regional trust fund established for assisting countries to improve their statistical systems, increase their capacity to produce reliable, timely and accurate data in line with internationally accepted methodologies and best practices that meet user needs, and inform decision-making process within the government and community. ECASTAT works closely with UNECE and CIS Statistical Committee for well coordinated international efforts to improve statistics in the region.
ECASTAT’s overall objective is to address the capacity and financial constraints of the statistical systems of the countries in the region. ECASTAT will support the long-term process of improving development outcomes by strengthening the production of reliable and relevant data on a timely basis for evidence-based decision making at all levels of government in Eastern Europe and the CIS region.
In particular, the ECASTAT aims to:
In line with the 2004 Marrakech Action Plan for Statistics (MAPS), previous assistance to the ECA region has focused on mainstreaming strategic planning in statistics and in helping countries to prepare National Strategies for the Development of Statistics (NSDS) or their equivalent. Through a number of interventions including support from the World Bank’s Trust Fund for Statistical Capacity Building (TFSCB), and the European Union and the UN Economic Commission for Europe (UNECE), almost all Eastern and CIS countries now have a NSDS in place or have started the process of preparing one. Some of the countries have started the NSDS implementation. ECASTAT will build on lessons learned and past successes in statistical capacity development. It places countries at the center of the process and aims to align its support for the development of statistical capacity with country priorities and national objectives. In particular, the approach to be used by ECASTAT will emphasize:
Ownership: Countries take the leadership in their statistical capacity improvement activities and determine their needs, development strategies for statistics and actively coordinate development actions;
Alignment: Support is aligned with the countries’ national statistical development strategies, institutions and procedures;
Harmonizing: Support is harmonized through well-coordinated efforts with other donors and organizations;
Managing for results: Resources are used for improving evidence based decision-making and should generate measurable results.
Window 1, regional projects
Window 2, country specific projects
SDG Metadata Translation Pilot
SDG indicators rely on transparency to ensure accountability of statistics for SDGs. However, metadata for SDG indicators are not available in official translations in UN official languages. Absent official translations, national translations of SDG indicator metadata can contribute to differences in understanding and calculation of indicators—between countries, agencies, policymakers, and the public. Currently, there is no mechanism currently to generate official translations of SDG indicators. Version control is a related concern, as updates to metadata should be signaled in their translation.
A pilot protocol is being developed to describe how official translation of SDG indicator metadata could be achieved efficiently and inclusively using computer-assisted translation software. This will evaluate the approach for a subset of indicators in a language. Best practices identified in the evaluation could be replicated to address other SDG language translation needs. The resulting key term database could be applied to other SDG technical documents. Resulting quality-controlled translations and machine-readable versions of the English and Russian language metadata would be made available online.
The project will proceed in three phases:
1. Assessing the accuracy of three machine-learning translation services against 10 SDG indicators
2. Translate Tier 1 SDG indicators metadata into Russian with the best translation software
3. Published translated metadata and evaluate with partners for feedback