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Nowhere to hide : an ethical evaluation of how big data aggregation violates privacy (and what we should do about it)
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Hybrid agency in the age of big data: towards a Foucaultian problematisation
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Incentives, virtues and big data organisations
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The privacy paradox: organisational data utilisation versus individual privacy
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Quality metrics for Privacy-Preserving Data Mining: a systematic review, phase-based classification, and critical synthesis
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An investigation into the requirements of a big data stewardship training / instruction programme / curriculum
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Big data analytics strategy formulation: a case study of big data analytics organizations in South Africa
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Common sense testing and sanity checks in machine learning
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Federated and privacy-preserving learning in neurological imaging: a systematic review of frameworks, applications, and evidence gaps
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Big Data and the Emerging Role of Libraries
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The influence of missing data mechanisms and simple missing data handling techniques on fairness
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Hybridizing AVOA and HHO for robust data clustering: a novel optimization framework
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Multimodal machine learning in real estate appraisal: models, data, and trends
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A multimodal data-driven ensemble deep reinforcement learning model for automated cryptocurrency trading
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Data-efficient calibration transfer across operational weather regimes for probabilistic airport hazard prediction
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A novel framework for evaluating the influence of participatory contributions and demographic factors on the positional accuracy of OpenStreetMap data
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Explainable yoga pose correction: a data-centric framework using SHAP-driven pose-specific feature analytics
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Handling extreme imbalanced multi-class data with MCDO-BR: a diversity-based synthetic over-sampling technique
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Navigating the Nexus: Competition Law, Data Privacy, and Regulatory Challenges in the Digital Economy
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Advancing text-based personality detection: a comparative study of machine learning models on behavioral interview data and stream of consciousness essays
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Sequence-aware models for predicting online purchase conversion from clickstream data: a leakage-aware benchmark study with calibration, value, and interpretability
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Digital Twin-based framework for real-time fault diagnosis and prognosis of industrial robots using unsupervised learning and real experimental data
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Automated feature synthesis on big data using cloud computing resources
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Leveraging big data resources and data integration in biology: applying computational systems analyses and machine learning to gain insights into the biology of cancers
