Dominating Data Diversity and Deluges: Computational Approaches to Integrative Data Management and Analysis in Chronobiology

*Corresponding author: e-mail abohn@itqb.unl.pt, URL http://sbd.itqb.unl.pt Introduction: Over the last decade, technological advances in data acquisition and storage have significantly increased the diversity and the volume of chronobiological data sets. As a consequence, the appropriate and efficient extraction of knowledge from these data sets often requires the application of an entire system of advanced analysis algorithms. Data-rich research in chronobiology is therefore very likely to increasingly benefit from interdisciplinary collaborations between experimental biologists and scientists with a background in mathematics and computation. In the present work we will summarize the results and the analysis strategies chosen in three recent, international, interdisciplinary collaborations between experimental groups in Brazil studying biological rhythms in animals and humans, and the Systems Biodynamics Group at ITQB-UNL in Portugal. Methods: All projects featured the simultaneous in vivo measurement of a multitude of variables, like wrist or body temperature, or activity levels, for time spans between 3 and 32 days, and sampling rates between 2 h–1 and 60 h–1. Analyses were performed by taylor-made cascades of scripts for data pre-processing, analysis and graphical representation, written in the R Language for Statistical Computing. Data storage was based on spreadsheets and data sharing realized by email. Results: While the featured approach yielded some advantages over the use of stand-alone software packages, it became clear that data and workflow management could still be improved by the deployment of correspondent web-based data pipelines for integrated storage and processing. A current parallel project at ITQB- UNL on data integration in microbial ecology sketches how collaborative computational tools and concepts from the semantic web can improve the scientific workflow in multi-partner projects, foster the integration of data sources from diverse origins, and improve the connection of experimental data with numerical modeling and simulations. Conclusions: Integrative computational tools for collaborative data analysis, storage, sharing, and integration have a large potential for extracting the maximum knowledge from diverse and voluminous data sets in chronobiology. Notwithstanding this potential, it should be remarked that informatics alone, without the corresponding interpersonal communication among team members, might not be sufficient for the long-term success of interdisciplinary team sciences. Publication History Article published online: 16 June 2026 © 2009. Brazilian Sleep Academy. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/) Thieme Revinter Publicações Ltda. Rua Rego Freitas, 175, loja 1, República, São Paulo, SP, CEP 01220-010, Brazil