The quality of research data

Abstract

This paper begins with a brief description of the changes that our views on the nature of data and information have gone through. It is stated that the main stakeholders of data quality are researchers, but it is also important for funding organizations and scholarly publishers, as well as libraries. The management of research data aims to provide high-quality, accessible, and reusable data. Ensuring data quality is also part of data literacy which is closely linked to information literacy. The study describes the nature of trust which is one of the most important quality characteristics. There are several other attributes of data quality that can be grouped differently. There may be external characteristics, such as its fitness for purpose. Nonetheless, digitized objects also have intrinsic values, including accuracy, objectivity, and credibility. Among the contextual quality characteristics we find relevance, added value, and completeness. Timeliness and volatility (rapid obsolescence) also can be related to temporality. Mention may also be made of completeness, comparability and originality, as well as a number of other features that can be grouped in varied ways. Approaching big data can be done similarly to the ways how we treat data in general. However, their incomplete and often uncertain nature negatively affect quality.