Pierre Grard

Traits: Structuring Species Information for Discoverability, Navigation and Identification

Conventionally, species traits concepts have been conceived from an ecological perspective after grouping them as functional traits, response traits or effect traits: attributes of individual organisms that express phenotypes in response to the environment and its effects on the organism. From an informatics perspective, traits may be conceived to encompass a broader vocabulary that can capture any species attribute including, but not limited to those concerning its morphology, taxonomy, functional role, habitat, ecological interactions, trophic strategies, genetics, evolution, conservation status, anthropological uses, ecosystem services etc. The evolution of such a vocabulary and its standardisation across disciplines and taxa is a challenge, but one that needs imminent attention as the field develops. Furthermore, traits can have values that vary within and across individuals and species. The ability to associate traits with levels of a taxonomic hierarchy, aggregate species traits from individual records, flexibility to attribute categorical text, numeric, temporal and spatial values; associate them with ontologies; and conform to standards, can evolve traits as a flexible framework to structure descriptive, numeric and tabular data on species. Such a framework for structuring descriptive species data will, allow better discoverability and navigation of the information and has potential for developing further applications such as polyclave identification keys and analytical aids for big data. The open source Biodiversity Informatics Platform that powers three international initiatives across Asia and Africa has been evolving as an effective platform to aggregate and build open access databases for varied biodiversity data types. It has ability to handle varied data types such as descriptive data, occurrences, maps and documents. The platform has recently added a traits infrastructure that is participatory and can aggregate traits from curated databases as well as by crowdsourcing from observation and collection data. It is flexible in building vocabularies to structure descriptive species information and media, evolving into a framework which allows flexible yet efficient navigation of species information in an information system. Here, we discuss this model, its application within the applied initiatives, its potential use in classifying multimedia data for species characterization in a complex context and in facilitating trait analysis. We also cover potential applications of the trait framework for developing into a comprehensive and effective infrastructure for aggregating and structuring species information.