tidsgap

Tidsgap is a term used in time-series analysis to describe the time-related gaps between consecutive observations in a dataset. It serves as a measure of data continuity and is often used to assess data quality, sensor reliability, and transmission integrity in systems that collect timestamped measurements.

In practice, tidsgap refers to the distribution of inter-observation intervals within a defined window. It can be summarized by statistics such as the maximum gap, the median gap, or a chosen quantile of the gaps between recorded timestamps. The value is typically expressed in units of time (seconds, minutes, etc.) and can be normalized relative to the nominal sampling rate to aid comparison across datasets.

Calculation usually involves taking a sorted list of observation times, computing the successive differences, and then summarizing these gaps. For example, gaps gi = ti+1 − ti are computed for all i, and tidsgap can be reported as the maximum gap or as a representative percentile. Presenting multiple measures (e.g., maximum and median) is common to capture both extreme outages and typical performance.

Origin and usage: tidsgap is a neologism formed from “tid” (time) and “gap.” It has appeared in discussions of data quality, sensor networks, and time-series integrity, though it is not yet universally standardized.

Applications: environmental monitoring, industrial Internet of Things, remote sensing, and finance where continuous data streams are important for analyses and decision-making.

Limitations: without a standardized definition, tidsgap interpretations vary. It can be affected by sampling cadence, time zone handling, and how missing data are recorded or reported. Adequate documentation of computation rules is essential when using tidsgap for comparisons. See also data gap and inter-arrival time.