Measures for interoperability of phenotypic data: minimum information requirements and formatting
2016
Hanna Ćwiek-Kupczyńska | Thomas Altmann | Daniel Arend | Elizabeth Arnaud | Dijun Chen | Guillaume Cornut | Fabio Fiorani | Wojciech Frohmberg | Astrid Junker | Christian Klukas | Matthias Lange | Cezary Mazurek | Anahita Nafissi | Pascal Neveu | Jan van Oeveren | Cyril Pommier | Hendrik Poorter | Philippe Rocca-Serra | Susanna-Assunta Sansone | Uwe Scholz | Marco van Schriek | Ümit Seren | Björn Usadel | Stephan Weise | Paul Kersey | Paweł Krajewski
Abstract Background Plant phenotypic data shrouds a wealth of information which, when accurately analysed and linked to other data types, brings to light the knowledge about the mechanisms of life. As phenotyping is a field of research comprising manifold, diverse and time-consuming experiments, the findings can be fostered by reusing and combining existing datasets. Their correct interpretation, and thus replicability, comparability and interoperability, is possible provided that the collected observations are equipped with an adequate set of metadata. So far there have been no common standards governing phenotypic data description, which hampered data exchange and reuse. Results In this paper we propose the guidelines for proper handling of the information about plant phenotyping experiments, in terms of both the recommended content of the description and its formatting. We provide a document called “Minimum Information About a Plant Phenotyping Experiment”, which specifies what information about each experiment should be given, and a Phenotyping Configuration for the ISA-Tab format, which allows to practically organise this information within a dataset. We provide examples of ISA-Tab-formatted phenotypic data, and a general description of a few systems where the recommendations have been implemented. Conclusions Acceptance of the rules described in this paper by the plant phenotyping community will help to achieve findable, accessible, interoperable and reusable data.
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