Though TIFF file formats are not ideal for eDiscovery, they are widely used. Here is a quick look at how to make a TIFF-formatted production, along with some other useful information about TIFFs productions in GoldFynch, and in general.
Creating TIFF productions in GoldFynch
Production Format, Standard Image Format
As part of your ESI specifications, you will usually be given a production format, standard image format, and load file requirement. These options are all chosen during step 3 of production (Production Output.)
The most common production formats will make use of GoldFynch's 'Loadfile/Database' format either with No natives or choosing to Include natives, and their respective TIFF G4 option.
Once you have selected your production and standard image format, scroll down to the bottom of step 3 of production and select a control parameter profile from the dropdown list.
If you have created a custom profile for this purpose then select that, but if you are not sure which to use, it's most likely you'll need the default 'All fields' control parameter profile, which is a Concordance/Relativity format.
If there is a specification that files should have their Bates number in their file name, select either the 'Bates numbers' or 'Original file names prefixed with Bates number' options, as appropriate, in step 9 of production (File naming options)
Potential differences of TIFFs produced in GoldFynch from incoming TIFF productions
There may be some differences from incoming TIFF productions that you receive:
Information about TIFF productions
The primary cons of this format are:
- The TIFF format that is always specified (TIFF Group IV) was created for fax machines to have a very small file size. As such, they are highly compressed, low-quality images, and it can sometimes be difficult to physically see and read the pages
- Although this production format typically provides a plaintext file for each document with the extracted text, this text has no page or positional information to use for searching and highlighting. For example, the production may have a document consisting of 100 TIFF images and a single text file, but there is no way to know what page or where on the page a particular word in the text file occurs
- Because of the above issue with the text, when ingesting TIFF productions, we first combine the TIFF pages into a single document and then run OCR on the document in order to create a text layer that can be highlighted and to get word position information. However, given the poor image quality, it's hard to ensure OCR accuracy. Additionally, as OCR is a computationally expensive process, generating usable documents from a TIFF production can take quite a lot of time
- When dealing with any imaged production format, whether it be PDF, JPEG, or TIFF, you are still dependent on how the producing party rendered the documents and the quality of the software they used. We would much rather receive the native files and process them ourselves, in order to ensure the integrity of the renderings, metadata, and extracted text content.