Big Data Quality Assurance Through Data Traceability: A Case Study of the National Standard Reference Data Program of Korea

Abstract

In the era of big data, the scientific and social demand for quality data is aggressive and urgent. This paper sheds light on the expanded role of metrology of verifying validated procedures of data production and developing adequate uncertainty evaluation methods to ensure the trustworthiness of data and information. In this regard, I explore the mechanism of the national standard reference data (SRD) program of Korea, which connects various scientific and social sectors to metrology by applying useful metrological concepts and methods to produce reliable data and convert such data into national standards. In particular, the changing interpretation of metrological key concepts, such as “measurement,” “traceability,” and “uncertainty,” will be explored and reconsidered from the perspective of data quality assurance. As a result, I suggest the concept of “data traceability” with “the matrix of data quality evaluation” according to the elements of a data production system and related evaluation criteria. To conclude, I suggest social and policy implications for the new role of metrology and standards for producing and disseminating reliable knowledge sources from big data.

Keywords

• Big data
• data quality
• data traceability
• metrology
• standard reference data
• uncertainty