Illuminating dark data: a systematic literature review of its characteristics and management strategies

Dark data refers to information collected by organisations that remains underutilised, often due to its unstructured nature. This article presents a systematic literature review (SLR) to define dark data comprehensively and examine its characteristics and management strategies. Despite the growing recognition of its potential value, a universally accepted definition remains absent, with scholars offering varied interpretations. The review analysed 182 articles before narrowing the scope to 81 relevant publications that highlight the difficulties in categorising and accessing dark data. Key characteristics identified include unused, ignored, and unmeasured, which are often generally in the organisation's repositories. This study further explored the implications of dark data on compliance, cybersecurity risks, and organisational efficiency. By addressing the existing literature gaps, this research aims to provide a clearer understanding of dark data and propose frameworks for its effective management. The findings are are particularly relevant for any organizations in Malaysia, providing a foundation for future research and practical strategies to optimise data utilisation while mitigating associated risks. Ultimately, this work underscores the need to recognise and manage dark data as a critical component of modern data governance strategies. Keywords: Dark data, data management, data utilisation, Systematic Literature Review, unstructured data