Minimal Information for High Content Screening in Microscopy Experiments (MIHCSME)

User metadata is an essential part of experimental data. Scientists need to understand underlying conditions and experimental procedures in order to model or investigate relevant biological questions. Currently, only a small fraction of the High Content SCreening (HCS) investigations are deposited for reuse by the community, and an even smaller fraction of that data is standards-compliant. For reusing data, scientists need to be able to understand how data was generated, under which experimental conditions. They also need to combine different sources of information for interpretation and validation, which requires standard procedures for collecting and recording metadata.

Starting with the REMBI specification, we have developed a minimum information model (MIHCSME) for describing high content screening experiments. We have increased the semantic richness of the metadata by specifying not only which ontologies to adopt as annotation vocabularies, but also the ranges of terms that should be used for annotation of specific fields.

This investigation contains spreadsheet template and examples for HCS users to download and use for structuring experimental data. Providing tabular metadata templates, that can be populated in Excel or Open office, is a practical way of lowering the barrier for entry to semantic data collection. We follow the same methods and paradigm as was developed during the FAIRDOM project.

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Created: 10th Oct 2022 at 08:44

Last updated: 22nd Feb 2023 at 07:29

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