dayatt

Dayatt is a term used in speculative and fictional contexts to denote a standardized framework for logging daily activities and related metadata. It is not an established real-world standard. The concept is often described as an open, privacy-conscious data model intended to support research, urban planning, and personal analytics.

Core design centers on a modular data model with components such as DayEvent, DayUser, and DayContext. DayEvent records activities with fields like type, start_time, end_time, duration, and location; DayUser captures anonymized identifiers and consent preferences; DayContext provides environmental or device-related metadata. The specification is imagined to support multiple serializations, including JSON, CSV, and Parquet, and to offer a RESTful API for data exchange. Privacy controls typically include opt-in consent, data minimization, and anonymization-ready options, along with clear data provenance.

Development and governance of the Dayatt concept are described in theoretical discussions and workshops among privacy researchers and data scientists. In these narratives, no single governing body exists, and the standard is depicted as an interoperable layer that could sit atop existing datasets to improve comparability across studies and applications.

Applications and reception in fiction emphasize Dayatt’s potential to enable cross-domain analysis of daily routines, inform urban planning, and support longitudinal behavior research. Critics in these stories flag risks such as re-identification, data misuse, and fragmentation if governance and interoperability are not carefully managed.

See also: Time-use data, Activity data, Data privacy, Data standards.