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OPEN A self-organizing, living library of time-series data

Interdisciplinary Studies

OPEN A self-organizing, living library of time-series data

B. D. Fulcher, C. H. Lubba, et al.

Introducing CompEngine, a revolutionary web platform designed to enhance interdisciplinary collaboration among time-series researchers. Developed by Ben D. Fulcher and his team, it allows users to upload data, explore similar datasets, and receive alerts for future matches, all while fostering connections based on data structure. Dive into a world where data sharing bridges the gap between experimental and theoretical science.

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Playback language: English
Abstract
Time-series data are prevalent across various scientific disciplines. CompEngine, a web platform, is introduced as a self-organizing library designed to facilitate interdisciplinary connections between time series. It uses a canonical feature-based representation to place time series in a common feature space, enabling users to upload data and explore similar datasets, receiving alerts for future matches. Unlike metadata-organized databases, CompEngine promotes data sharing by connecting researchers based on data structure, fostering collaboration between experimental and theoretical scientists. Its extensive library also allows for comprehensive time-series algorithm characterization across diverse data types.
Publisher
Scientific Data
Published On
Jul 07, 2020
Authors
Ben D. Fulcher, Carl H. Lubba, Sarab S. Sethi, Nick S. Jones
Tags
time-series data
CompEngine
data sharing
interdisciplinary collaboration
feature-based representation
algorithm characterization
scientific disciplines

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