What is an acceptable action for handling the OCRed documents in the data source?

In the context of handling Optical Character Recognition (OCR) documents within data management, excluding OCRed documents and managing them manually can be a sound approach under certain circumstances. Here’s why this action can be acceptable:

When documents are processed through OCR, the accuracy of the text recognition can vary based on factors like the quality of the original document, the technology used, and the presence of complex layouts or unusual fonts. If the OCR accuracy is questionable, and if there is a significant risk that the recognized text could lead to errors in project outcomes or analysis, it may be prudent to exclude these documents from automated processes. Manually handling them allows for a more careful assessment of the content which can help ensure data integrity and reliability.

By adopting this method, resources can be allocated towards verifying and correcting any discrepancies in the OCRed outputs before inclusion in final datasets. This can ultimately lead to improved project quality and decision-making based on the data.

The other choices suggest including OCRed documents in some way without prioritizing accuracy checks, which could lead to potential pitfalls in project management. Thus, manually handling OCRed documents might be viewed as a more cautious and thorough approach in certain situations, ensuring that only the most accurate information is utilized in project workflows.