Web Service for Data Imputation in Univariate Time Series

• Jeremias Lima Abreu UFPA
• Douglas Almeida Vidal UFPA
• Glauco Estacio Gonçalves UFPA

DOI: https://doi.org/10.5753/wcama.2024.2928

Abstract

A common problem in environmental data recording is gaps, which can be mitigated by data imputation. Although there are computational libraries for imputation, these require learning new technologies and programming languages. To meet this need, this work presents a web service for imputing time series data, which allows a client application to request imputations on data with gaps. In addition to describing the architecture of this service, this article shows results of a rigorous evaluation of service performance in terms of imputation time and quality, in order to provide a global view of the trade-off between execution time and accuracy of each algorithm.

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