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This article discusses the International Monetary Fund's (IMF) experience with its Data Quality Program (DQP) and the framework it has developed using the Data Quality Assessment Framework (DQAF). It explores how the DQP integrates data initiatives with member countries and the IMF's own statistical activities, as well as its impact on data management and dissemination. The article also highlights the gradual approach taken by the IMF in implementing the DQP and its plans for data and metadata exchange.
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The IMF experience with quality assurance framework April, 27, 2006 Conference on Data Quality for International Organizations (Committee for the Coordination of Statistical Activities) Lucie Laliberté
The IMF Data Quality Program The IMF introduced its DQAF-based Data Quality Program for integrating: • its data initiatives with member countries and • its own statistical activities
DQAF with IMF member countries The DQAF structure underpins the IMF main data quality initiatives with member countries: • The SDDS/GDDS • ROSC Data module • Technical assistance reports
What is the experience of the IMF? While initially focused on its member countries, the DQAF-centred DQP now increasingly covers the IMF statistical operations that were previously conducted by statistical domain specific divisions.
Reorganization to enhance data management In 2005, STA created the Statistical Information Management Section (SIMS) to: (i) provide central leadership to ensure the use of cost effective and best work practices in data management; (ii) provide data collection and client services for STA; (iii) provide central leadership for STA in the use of information technology (IT) and managing IT development and production projects; and (iv) manage STA’s publications and electronic dissemination through, for example, a statistics portal. .
Gradual approach The strategy consists in taking a staggered approach reflecting resource constraints and the need to develop new work processes related to data collection and processing, IT, and data dissemination. As efficiencies from data production are effected, resources are freed for developmental work such as designing, testing, and implementing a more unified approach to data collection.
Data and metadata for own operations • As DQAF metadata become available in sufficient quantity, the resulting Metadata Repository will be used as a source for series and table notes in publications such as International Financial Statistics, the various Yearbooks, and the online databases. • The Repository is expected to play an important documentation role in the IMF-wide Data Warehouse now in the pilot stages, enhancing the effectiveness of the Warehouse in exposing any substantive data inconsistencies across the institution, thus allowing resources to be focused on eliminating them, and possibly improving the efficiency of internal data processes.
Data and Metadata Exchange The plans are to make the Metadata Repository of the nascent Data Warehouse capable of Statistical Data and Metadata Exchange (SDMX)-conformant data interchange within the IMF and between IMF and other institutions, as SDMX metadata transmission standards become settled. The relatively fine and structured detail in the DQAF makes it highly interoperable with other structures in use by other organizations.
What is the experience of the IMF? The weaknesses of our data operations are well known: First, designing the DQAF structure helped identify weaknesses in our own data operations. Second, the experience that the IMF gains through its technical assistance, data dissemination initiatives and data quality assessment has been very beneficial in identifying problems and devising solutions. Third, valuable inputs are received from internal Fund users. Fourth, periodic external reviews are conducted on statistical publications, which reflect the views of external users.
What is the experience of the IMF? • The introduction of the DQP centered on the DQAF is in line with the meeting of the Coordinating Committee for Statistical Activities (CCSA) May 27-28, 2004 (Wiesbaden, Germany) where it was noted that the DQAF provides a starting point for development of a statistical data quality program for international organizations