Quality standards for data and metadata addressed to data science applications
DOI:
https://doi.org/10.47909/anis.978-9916-9760-3-6.116Keywords:
Networked Databases, Metadata, Metadata Quality, Data Science, Information ScienceAbstract
The present research investigates how the models of organization and representation of information and knowledge can be applied in Data Science. We highlight and discuss how data quality standards can provide conditions for the production of curated databases for applications. As for the methodology, this is qualitative, exploratory, and descriptive research. Our theoretical discussions are supported by bibliographic research performed in the fields of data science and information science. The results contributed to understanding that the potential of data reuse for applications in Data Science depends on strategies of organization and representation of information and knowledge based on the theoretical-methodological scope of Information Science. From the metadata creation stages to the description, cataloguing, classification, and indexing processes, Information Science can make significant contributions that impact the data quality for use and reuse in diverse applications.
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