Abstract

This paper focuses on the characteristics of research data quality, and aims to cover the most important issues related to it, giving particular attention to its attributes and to data governance. The corporate word’s considerable interest in the quality of data is obvious in several thoughts and issues reported in business-related publications, even if there are apparent differences between values and approaches to data in corporate and in academic (research) environments. The paper also takes into consideration that addressing data quality would be unimaginable without considering big data.

Highlights

  • Open science encourages cooperative work in research and making knowledge publicly accessible in digital formats with minimal or no restrictions [1]

  • Royal Society [2] stated, effective data ecology requires all stakeholders of scientific work to elaborate and implement transparent policies, paying attention to custodianship and data quality (DQ)

  • Based on a non-exhaustive review of the literature, this paper aims to identify the most important issues of research data quality and data governance

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Summary

Introduction

Open science encourages cooperative work in research and making knowledge publicly accessible in digital formats with minimal or no restrictions [1]. Achieving real benefits of sharing research data is possible only if data are reused by others [3] This requirement involves being concerned with its quality. We will focus on the characteristics of research data quality, being aware of the corporate word’s considerable interest in the quality of data, some business-related publications on these issues could not be neglected, even if there are apparent differences between values and approaches to data in corporate and in academic (research) environments. The distinction between these two types of data is clear. Before examining data quality issues themselves, we need to consider the changes which the views on the nature of data have undergone

Changing Views on the Nature of Data
The Stakeholders of Research Data Quality
The Nature of Data Quality
Data Quality Attributes
Technical and Scientific Quality
Data Quality and Data Reuse
Other Quality Factors
Big Data Quality and Smart Data
Data Governance
Quality Beyond Characteristics and Attributes
Conclusions
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