Data Security

Data security remains a critical concern, as visual materials are actively handled, processed, and sometimes transformed for coding, comparison, or potential sharing. During this stage, images, photographs, and video excerpts may be extracted, duplicated, or transferred across devices and analytical tools, increasing the risk of unauthorized access, accidental disclosure, data corruption, or loss. Robust security measures, such as encrypted storage, secure file transfer protocols, multi-factor authentication, restricted access, and regular system updates, are therefore essential to ensure the confidentiality and integrity of the data.

From an open data perspective, it is important to ensure that any preparation for sharing or reuse does not compromise data protection requirements. Analytical workflows should include clear version control procedures and controlled environments, especially in collaborative settings. Access to both raw data and processed materials should be limited to authorized personnel, ensuring that sensitive or identifiable data is not exposed beyond agreed conditions.

Particular attention should also be given to derivative outputs generated during analysis, such as coded datasets, annotated images, or extracted frames. These materials should be stored securely and accompanied by appropriate metadata documenting analytical transformations, consent conditions, and any limitations on reuse. This is essential to enable responsible data sharing and meaningful reuse while preserving the rights of individuals.