Abstract
Data quality involves a set of characteristics, values, and expressions that are built iteratively. Open government data (OGD) shares the qualities of Big Data regarding volume, speed, accuracy, and value, and the purpose of achieving stakeholders’ reuse stands out. This study uses a bibliographic review to identify the relationships among big data, open data, data quality, and value. We conclude that OGD, a recent trend, encourages collaboration and citizen participation and enables reusing data to pursue public and private innovation. Ensuring data quality makes it possible to obtain value from its reuse and generate Economic Value, Commercial Value, Social Value, and Public Value. Consumers require a solid basis of trust before using public information, which requires a data quality assurance process that strengthens and intensifies the inherent value of the data and activates its potential in different contexts.
Highlights
At the heart of data are their contextual value and the potential for projection and extension to other domains
16% of the records correspond to publications made by multilateral organizations, such as the InterAmerican Development Bank (IDB), the UNECE, and the American Society for Quality (ASQ)
The authors of topics of study have dedicated considerable time in their research to the area of Emerging Information Technologies, 55% of the selected literature is focused on open government data, 19% shows the relationship of Big Data with open government data, 7% discusses the relationship of Big Data with open data, and 19% concentrates only on Big Data
Summary
At the heart of data are their contextual value and the potential for projection and extension to other domains. Whether the data have quality problems or not, a fundamental step is ensuring their suitability and adequacy for their purpose It emerges that data quality is oriented in its foundation of a continuous and not static process, which is an enabler and motivator to take a large set of data, perhaps without form, and adapt it so that users can discover patterns, new ideas, and trends (BSA The Software Alliance, 2017). In this way, a contribution is made to the data value chain. Data-based products are generated with the potential value of fostering digital development in transportation, health, manufacturing, and retail (Attard et al, 2016)
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