In the health industry, the use of data (including Big Data) is of growing importance. The term ‘Big Data’ characterizes data by its volume, and also by its velocity, variety, and veracity. Big Data needs to have effective data governance, which includes measures to manage and control the use of data and to enhance data quality, availability, and integrity. The type and description of data quality can be expressed in terms of the dimensions of data quality. Well-known dimensions are accuracy, completeness, and consistency, amongst others. Since data quality depends on how the data is expected to be used, the most important data quality dimensions depend on the context of use and industry needs. There is a lack of current research focusing on data quality dimensions for Big Data within the health industry; this paper, therefore, investigates the most important data quality dimensions for Big Data within this context. An inner hermeneutic cycle research approach was used to review relevant literature related to data quality for big health datasets in a systematic way and to produce a list of the most important data quality dimensions. Based on a hierarchical framework for organizing data quality dimensions, the highest ranked category of dimensions was determined.

Interoperability has become crucial in the world of electronic health records, allowing for seamless data exchange and integration across diverse settings. It facilitates the integration of disparate systems, ensures that patient records are accessible, and enhances the care-delivery process. The current interoperability landscape of electronic health records is saddled with challenges hindering efficient interoperability. Existing interoperability frameworks have not adequately addressed many of the challenges relating to data exchange, security and privacy. To address these challenges, the TASIPPS (Technical and Semantic Interoperability, Preserving Privacy and Security) framework is proposed as a comprehensive approach to achieving efficient interoperability. The TASIPPS framework integrates robust security and privacy measures, providing real-time access to electronic health records that enable precise diagnoses, timely treatment plans and improved patient outcomes. The TASIPPS framework offers a holistic and effective solution to healthcare interoperability challenges. A comparison of the framework with existing frameworks showed that the TASIPPS framework addresses key limitations in privacy, security, and scalability, while providing enhanced interoperability across distinct healthcare systems, positioning it as a more comprehensive solution for modern healthcare needs.

In the digital music market (and accompanying digital players), use of different digital rights management (DRM) systems, have effectively locked-in consumers to proprietary technologies of respective companies. Currently, no single DRM standard exists for digital music, therefore, music purchased from one competitor may not be compatible with another competitor's jukebox software or digital player. There is little incentive for leading competitors to license their technology or provide support for other technologies to enable interoperability of different technologies. Consequently, consumers purchasing from such competitors in-effect become locked into their proprietary technology and its accompanying DRM systems. This paper examines the consequences of such market behaviour focusing on the most popular music store iTunes (owned by Apple), its dominance in the industry and the implications of Apple's decision not to open its FairPlay DRM scheme that controls all music purchased from iTunes. It discusses the attempt by RealNetworks to secure interoperability with Apple's FairPlay scheme and the resultant response of Apple. Finally, it examines the potential benefits, problems and legal issues raised by the actions of RealNetworks and argues for interoperability.