Without much fanfare, Google has discreetly revised its Google Search Central documentation to announce the inclusion of .csv file indexing.
This development introduces a fresh avenue for enabling crawling. Conversely, for publishers who wish to prevent the crawling of their .csv files, it might entail revising the robots.txt file to exclude these specific files.
Comma-Separated Values (CSV)
Comma-separated values (CSV) files are text-based documents that store data in a tabular structure, suitable for presentation akin to a spreadsheet.
These files encompass raw data in text format, devoid of stylistic attributes such as fonts, images, or interactive links.
They prove valuable for tasks such as feeding a roster of URLs into software like Screaming Frog for crawling.
Moreover, CSV files offer utility in the structured arrangement of data within a spreadsheet layout.
CSV File Indexing Is New
Google’s capacity to index CSV files marks a novel feature, as conducting a “filetype” search on Google specifically for CSV files presently does not yield results containing CSV files.
Searches like the following currently do not return CSV files:
- filetype:csv site:.gov
- filetype:csv site:.edu
- filetype:csv site:.com
Google has previously used CSV files in an indirect manner
An interesting aspect of Google’s indexing of CSV files is that Google’s Dataset search results have already incorporated CSV files, seemingly when accompanied by structured data descriptions.
Documentation within Google’s previous Developer resources (accessible through Archive.org) regarding dataset structured data indicates that CSV files adhere to the criteria for being featured in dataset search functionalities.
The integration of tabular data into search outcomes dates back to 2018, following Google’s announcement that they would display this type of data in search results, provided it is associated with structured data.
According to the original documentation:
“Datasets are easier to find when you provide supporting information such as their name, description, creator and distribution formats are provided as structured data…
Here are some examples of what can qualify as a dataset:
- A table or a CSV file with some data
- An organized collection of tables
- A file in a proprietary format that contains data
- A collection of files that together constitute some meaningful dataset
- A structured object with data in some other format that you might want to load into a special tool for processing
- Images capturing data
- Files relating to machine learning, such as trained parameters or neural network structure definitions
- Anything that looks like a dataset to you”
In 2022, Google revised the mentioned documentation and redirected it to the new Search Central Documentation.
The updated documentation provides enhanced clarity, emphasizing that Google relies on structured data to utilize CSV files for their dataset search presentation.
However, does this modification imply that Google might eventually begin to crawl CSV files and incorporate them into search results appearances, alongside tabular data indicated within structured data?
This is what the current documentation explains today:
“Datasets are easier to find when you provide supporting information such as their name, description, creator and distribution formats as structured data.
Google’s approach to dataset discovery makes use of schema.org and other metadata standards that can be added to pages that describe datasets…
Here are some examples of what can qualify as a dataset:
A table or a CSV file with some data…”
Is Google’s CSV Indexing Linked to a Recent Update?
A core algorithm update by Google entails making substantial and extensive modifications to their fundamental algorithm.
The nearly simultaneous occurrence of the CSV file indexing and the core algorithm update could be coincidental.
However, it’s worth contemplating whether Google has enhanced its crawling engine to facilitate CSV indexing or if this capability preexisted.
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