Selvinformation

Selvinformation is a multidisciplinary concept that refers to the collection, organization, and interpretation of information about the self drawn from an individual's digital traces. It encompasses data generated by online activity, device sensors, wearables, and self-reported inputs, which are compiled into usable formats such as dashboards, personal profiles, timelines, or narratives. The term is distinct from the information-theoretic notion of self-information and is used primarily in information science, personal data management, and digital identity research.

Origins and scope: The term was introduced in contemporary debates on data stewardship and self-tracking, often in the context of privacy, portability, and digital well-being. It describes both the practice of curating one's own data and the development of systems that reason about the self from connected data sources.

Methods and technologies: Selvinformation relies on consented data collection, data fusion across heterogeneous sources, metadata tagging, and visualization or narrative generation. Practices draw on personal data management, data provenance, and privacy-preserving analytics to support controlled access, sharing, and export of self-related data.

Applications: It informs personal knowledge management, tailored health and wellness insights, career and education planning, and digital identity tools. It can enable users to reflect on patterns, support decision making, and facilitate projects related to heritage or resilience. Ethical and legal considerations shape its deployment.

Challenges and governance: Core concerns include data ownership, consent beyond initial collection, portability, accuracy, and bias. There is ongoing debate over surveillance risks, data misuse by third parties, and the need for standards, transparency in algorithms, and user rights to deletion and amendment.