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Proceedings of TDWG : Conference Abstract
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Timothée Poisot‡, Dominique Gravel§, Steve Vissault‡,§
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Corresponding author: Timothée Poisot (timothee.poisot@umontreal.ca)
Received: 02 Aug 2017 | Published: 03 Aug 2017
© 2017 Timothée Poisot, Dominique Gravel, Steve Vissault
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citation: Poisot T, Gravel D, Vissault S (2017) mangal - making sense of biotic interaction data. Proceedings of TDWG 1: e19993. https://doi.org/10.3897/tdwgproceedings.1.19993
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Abstract
There are exponentially more species interactions than there are species - and this should entice us to be exponentially more careful when designing a data format to represent species interactions. The tradition in the analysis of species interaction networks was to store matrices, but this format is inefficient, does not offer access to the information in a modular and atomic way, and is poor in meta-data. To help research, faciltiate interaction with other biodiversity data representations, and offer a universal, unified format to represent biotic interactions, we designed mangal.io. At its core, the mangal data format specificies how various component of an interaction should be represented, and the hierarchy between them. In this presentation, we will (i) describe the original data format and explain how it was designed based on ecological principles, (ii) describe the revised data format and why it can function as the standard for biotic interaction data, and (iii) illustrate case studies based on the use of mangal.io, notably related to using AI/machine learning to infer missing biotic interactions and the macroecology of food webs
Keywords
API, biotic interactions
Presenting author
Timothée Poisot