Topic outline
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Quality Control
The Quality Control (QC) system is established as a machine detection mechanism to prevent wrong information from reaching the repositories and thus, avoid major errors and rolling mistakes based on misleading information. The level of errors spans from blockers to minor which indicates the impact spread on the wrong use of the data.
The following tutorial on this Plazi tool presents:
- how the QC service functions, and
- how to run a QC check
Building on top of the results of this service, several checklists have been produced to reflect what should not be done to avoid committing mistakes in the data processing process and the best way to correct the errors, should those appear.
To be on the safest side possible:
- Document Metadata
- Text Streams
- Check illustrations.
Still, those mistakes occur very normally though there is always a solution to tackle those common errors that refer to:
- Text (see the following screenshot as an example):
- Treatments
- Illustrations
- Material citations
- Bibliographic references
- Taxon names
- Taxonomic names
Enhancing annotations
To improve results and ensure the best quality possible of the annotations, you may get further in the process and obtain more details for the extracted data. At any stage of the process you may come back to the annotations and improve them in a simplified process that comprises several levels of enhancement:
- Edit Annotations Attributes
- Copy Annotation Attributes
- Parse Materials Citations
- Parse References
- Parse Taxon names
- Assign captions for figures and tables
- Find or List Words
- List annotations
- Revise Block Paragraphs
This is also a service provided by PLAZI that has been built in collaboration with other infrastructures and developed under the umbrella of several projects, COST MOBILISE and BiCIKL among others
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