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In today's fast, agile, complex and interconnected business world, one of the main goals and concerns is to find an efficient and effective way of managing information security risks. So, one of the means is usage of multicriteria decision-making techniques for such purposes. The vast majority of research begins with some form of literature review. Thus, the review of the literature must be done thoroughly and impartially in order to obtain certain scientific value. This paper provides a systematic literature review (SLR) of relevant and recent literature from both research domains, namely information security risk management and multicriteria decision-making, identifying the standards, methods, techniques and tools that are considered to be the most relevant in the research areas observed. The main purpose of the paper is to discover complementary ISRA and MCDM methods that could be used as a basis to create a new hybrid model for more efficient evaluation of critical IT solutions. The related context, main goals, review methods, relevant results of each research phase along with the findings, papers' analysis, recommendations and conclusions are all given in this review article in order to fully comply with the SLR requirements.

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.