EvoNEST, a modular application for comprehensive species-based sampling and data management in comparative biology
Organism-based research in ecology and evolution often faces challenges in data management due to its commonly nested metadata structure (e.g., phylogenetic, species, samples, subsamples and traits), fragmented data formats and limited accessibility and interoperability. Further, data migration between drives, platforms and formats can hinder data tractability, impede collaboration and risk critical data loss. Here we describe Evolutionary, ecological and biological Nexus of Experiments, Samples and Traits (EvoNEST), a modular full-stack data management application designed to minimize data handling and conversions by integrating all aspects of biodiversity research, from specimen sourcing to publication, into a unified platform. Unlike traditional laboratory information systems that require extensive customisation for biological hierarchies, EvoNEST’s specimen-centric design natively supports taxonomic relationships and parent-child sample structures. We developed EvoNEST Backbone, a Docker-based core version of the software, which can be easily installed and customised for different research contexts. Its architecture, built on Node.js and MongoDB, ensures flexibility for diverse research needs while natively supporting Findability, Accessibility, Interoperability, Reusability (FAIR) data principles. Key features include intuitive graphical user interfaces, digital lab books, automated data import and export, trait analysis, integrated visualisation tools, and unique identifiers with QR codes for the seamless integration with physical objects (specimens, samples and subsamples). The system can be run locally or as a server-based application, facilitating data entry from mobile devices and computers within or outside the home institution. A logbook system assures that all changes to data and metadata are traceable, with live updates ensuring integrity when multiple users are accessing it. To demonstrate how EvoNEST Backbone can be customised to the researchers’ needs, we present a specialised, network-enabled implementation dedicated to the comparative study of spider silk properties across spider species. We also discuss implementation choices and future developments. By providing a centralised, user-friendly system for organism-based data management, EvoNEST aims to accelerate the digitisation and dissemination of phenotypic data, and improving the traceability, documentation and reuse of the scientific output of laboratories. To ensures accessibility and to promote collaborative improvement, we release EvoNEST as an open-source software.
César Pose
Daniele Liprandi
databrick
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