Abstract

Data are the most important resource of the 21st century. The open data (OD) movement provides publicly available data for the development of a knowledge-based society. As such, the concept of OD is a valuable information technology (IT) tool for economic, social, and human development, which adds value. To further develop these processes on a global scale, users need to manage the quality of OD in their practices. Otherwise, what is the point of using data just for the sake of using it (in science or practice) without thinking about data compliance with norms, standards, and so forth? This article aims to provide an overview of (meta)data quality dimensions, sub-dimensions, and metrics used within OD assessment-related research papers. To achieve this, the authors performed a systematic literature review (SLR) and extracted data from 86 relevant studies dealing with the evaluation of OD. The article endows the progress made so far in OD assessment research. Findings of reviewing the assessment of the OD in the light of existing (meta)data quality dimensions unveil the potential of metadata. Furthermore, the analysis disclosed the need for greater use of quantitative methods in research, and metadata can greatly assist in this.

Highlights

  • The open data (OD) initiative has gained a lot of attention in recent years, as usage of OD can be beneficial to various stockholders

  • The main findings of the article are shown as answers to the defined research questions: Research Question 1 (RQ1): Whatdata qualitydimensions are used for OD assessment? The authors have identified 10 mostly useddata dimensions within OD studies and these are completeness, accuracy, consistency, accessibility, timeliness, usage, retrievability, openness, transparency, and understandability

  • The initial literature review revealed that there is room for improvement of OD as well as the improvement of the current assessment of OD within existing research. This improvement can be directed to different aspects of the OD paradigm, for instance, generally recognized dataset attributes, requirements for publishing open datasets, compliance with various policies, required functionalities of OD infrastructure, quality assessment of datasets, openness, transparency, participation or collaboration, and assessment of social, economic, political, and human value in OD initiatives

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Summary

Introduction

The open data (OD) initiative has gained a lot of attention in recent years, as usage of OD can be beneficial to various stockholders. The questionable quality, poses a risk for the success of the OD initiative. To contribute to the issue, examination of what has been done so far is lacking. Insufficient examination of OD in research far was the primary motivation for carrying out this review research. The main objective of the research is to provide a review of the state of the art for OD assessment. The main objective is further divided into two sub-objectives. One side is to identify papers that investigate the OD assessment (omit big data). The other sub-objective is to analyze papers identified as relevant, considering defined research questions

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