Abstract
Data quality management in document oriented data stores has not been deeply explored yet, presenting many challenges that arise because of the lack of a rigid schema associated to data. Data quality is a critical aspect in this kind of data stores, since its control is not possible and it is not a priority in the data storage stage. Additionally, data quality evaluation and improvement are also very difficult tasks due to the schema-less characteristic of data. This paper presents a first step towards data quality management in document oriented data stores. In order to address the problem, the paper proposes a strategy for defining data granularities for data quality evaluation and analyses some data quality dimensions relevant to document stores.
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Cristalli, E., Serra, F., Marotta, A. (2018). Data Quality Evaluation in Document Oriented Data Stores. In: Woo, C., Lu, J., Li, Z., Ling, T., Li, G., Lee, M. (eds) Advances in Conceptual Modeling. ER 2018. Lecture Notes in Computer Science(), vol 11158. Springer, Cham. https://doi.org/10.1007/978-3-030-01391-2_35
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DOI: https://doi.org/10.1007/978-3-030-01391-2_35
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