observation

Edge evidence

• assay or measurement process produces data item METPO:2000202

  Assays and measurements generate data items.

  • DOI:10.1371/journal.pone.0154556 the output of an assay is typically a data item Supports assay outputs as data items.
• data item records measured quality

  Observation data record a measured quality.

  • DOI:10.1371/journal.pone.0154556 measuring its glucose concentration Supports measurement outputs as records of qualities.
• observation is about material entity

  Observation records are about material entities or samples and their qualities.

  • DOI:10.1371/journal.pone.0154556 can be about any material entity Supports observations and study outputs as about material entities.
• observation has context geographic location

  Observation data items require contextual information about time and place of measurement.

  • DOI:10.3233/sw-223096 An observation data item requires a data structure to encompass the contextual information about the time and place etc. of a measurement.
• assay or measurement process has specified input material entity with evaluant role

  An assay has a material entity with evaluant role as specified input.

  • DOI:10.3233/sw-223096 OBI: assay and has_specified_input some (material entity and has role some evaluant role); generalized, not microbe-specific.
• assay or measurement process has output measurement datum

  An assay produces a measurement datum as output of the observation process.

  • DOI:10.3233/sw-223096 SOSA Result and IAO measurement datum are comparable outputs of an observation process.
• planned process has specified input sample

  A planned process takes material entities such as samples as specified inputs.

  • DOI:10.3233/sw-223096 OBI has specified input/output pertain to planned process with material entities (for assays) as targets.
• metadata recorded in MIxS reporting standard

  Sample/source-environment metadata is recorded using MIxS metadata elements.

  • DOI:10.1007/978-1-0716-3838-5_20 MIxS consists of a number of metadata elements that describe a particular characteristic of the sample or its source environment.
• FAIR principles requires metadata unique identifier

  FAIR requires each object or dataset to have a unique identifier and rich metadata.

  • DOI:10.3389/fcimb.2024.1384809 FAIR requires each FAIR object or dataset have a unique identifier and be described with rich metadata.