Tag Scraping
What is Tag Scraping?
Tag scraping is the process of automatically identifying and extracting tag numbers and tag-related data from engineering documentsWhat are Engineering Documents? Engineering documents are th... More, drawings, databases or other repositories. It is used to locate tagged assets and capture the details associated with those assets for analysis, integration or information management purposes.
By automating this activity, organizations can examine large collections of records without manually reviewing every document. This makes tag scraping a practical way to uncover asset-related data that may be distributed throughout an information environment.
What Tags Are & Where They’re Found
A tag is a unique identifier assigned to a physical asset, piece of equipment or instrument that represents its location or function in a facility. Tags follow a predefined format based on its type, and these formats are defined based on set standards.
Because tags are used throughout the asset lifecycle, they usually appear across a wide range of engineering and operational records.
Common sources include:
- P&IDs
- Engineering drawings
- Equipment lists
- Vendor documentation
- Maintenance records
As documentation volumes increase, tag references scatter across many different sources. This widespread use makes tags an effective starting point for locating asset-related content.
How Tag Scraping Works
Tag scraping tools search documents and datasets for patterns that match established tagging conventions.
When a matching tag is identified, the tool captures the reference and may also collect related details located nearby. These results are then organized into a structured output that can be reviewed or processed further.
The exact approach varies depending on the format of the source material and the objectives of the activity.
What Tag Scraping Produces
The output of tag scraping is typically a structured inventory of tag references discovered within the source material.
Depending on the objective, the results may contain:
- Tag numbers
- Equipment descriptions
- Document associations
- Supporting asset attributes
This output provides a consolidated view of information that was previously distributed across multiple records.
What Influences Tag Scraping Results?
The quality of tag scraping results is closely connected to the consistency of the tagging practices used within the source material.
Factors that commonly affect performance include:
- Established tagging conventions
- Document condition
- Formatting practices
- Record completeness
When tags are applied consistently, automated extraction is generally more reliable. Variations in how assets are identified can make interpretation more difficult and may require additional review.
Tag Scraping During Digital Initiatives
Many information improvement efforts begin with a discovery phase focused on understanding the assets represented within existing documentation.
Tag scraping supports this activity by revealing where tagged assets appear and how frequently they are referenced. This visibility helps organizations establish a clearer picture of the information already available before undertaking activities such as data enrichment, migration or asset information validation.
Because of this, tag scraping is often used as an early step in efforts aimed at improving the quality and usability of asset-related information.