Measures for interoperability of phenotypic data: minimum information requirements and formatting
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Cwiek-Kupczynska, H.; Altmann, T.; Arend, D.; Arnaud, E.; Chen, D.; Cornut, G.; Fiorani, F.; Frohmberg, W.; Junker, A.; Klukas, C.; Lange, M.; Mazurek, C.; Nafissi, A.; Neveu, P.; van Oeveren, J.; Pommier, C.; Poorter, H.; Rocca-Serra, P.; Sansone, S.; Scholz, U.; van Schriek, M.; Seren, U.; Usadel, B.; Weise, S.; Kersey, P. Krajewski, P. (2016) Measures for interoperability of phenotypic data: minimum information requirements and formatting. Plant Methods 12 (1) p. 44. ISSN: 1746-4811
Permanent link to cite or share this item: http://hdl.handle.net/10568/77807
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. 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. Acceptance of the rules described in this paper by the plant phenotyping community will help to achieve findable, accessible, interoperable and reusable data.