Tired of losing valuable data? Build your lab ecological database as a cornerstone for long-term approaches

Authors

  • Juan Alberti Instituto de Investigaciones Marinas y Costeras (IIMyC), FCEyN, UNMdP-CONICET
  • Octavio Massone Instituto de Investigaciones Marinas y Costeras (IIMyC), FCEyN, UNMdP-CONICET

DOI:

https://doi.org/10.25260/EA.22.32.1.0.1785

Keywords:

relational database, graphical user interface, shiny, step by step guide

Abstract

Long-term ecological data is essential to identify impacts of global change or to analyse the response of local systems to perturbations. Thus, ecologists are facing the compromise to collect and process longer-term data while specific funding for those purposes is extremely scarce. Although more funding to gather and store long term data would be ideal, it is unlikely to occur, at least in the short term. Another (most plausible) option could be to dive among the many spreadsheets belonging to one or more colleagues with shared variables and from several projects over the years. Obviously, this might be an extremely time-consuming and tedious task. To simplify this and save time, it would be ideal to store as much data as possible (individual or lab generated) in a single comprehensive database. Given that the process of building, maintaining and doing queries on such databases could be scary for ecologists not familiarized, here we provide a step-by-step guide to build 1) a generic and versatile ecological database, and 2) a graphical user interface to load, update, verify, view and download data. The scripts to build them are programmed on open-software (MariaDB and R), and we also provide instructions to change them according to many usual situations.

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Tired of losing valuable data? Build your lab ecological database as a cornerstone for long-term approaches

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Published

2022-03-06

How to Cite

Alberti, J., & Massone, O. (2022). Tired of losing valuable data? Build your lab ecological database as a cornerstone for long-term approaches. Ecología Austral, 32(1), 151–157. https://doi.org/10.25260/EA.22.32.1.0.1785