Photographs are an important source of evidence demonstrating delay issues, unexpected conditions, safety concerns, or non-conformance in construction disputes. In large scale projects there can be hundreds of thousands of photographs taken over the course of the project. The high volume and the fact most photographs lack extracted text make review of such records potentially quite time consuming and costly.
One thing to keep in mind when dealing with the review of photographs is proportionality, that is, how important the evidence is versus the burden of producing it.
Another factor to consider is whether the evidence is available elsewhere. Many of the important or significant photographs will be reproduced in reports. Or, as in the case of the Elliot Lake Algo Mall collapse, there will be correspondence around the removal of photographs from draft reports. Therefore, it is unlikely it is even necessary to review large volumes of standalone photographs when the truly material photographs are included in other records.
In the event you determine some or all standalone photographs need to be reviewed — either your own photographs or those produced by the opposing party — there are methods to narrow the focus of the review with the goal of reducing time and cost. These methods include the following:
Metadata: Digital photographs contain Exchangeable Image File Format (EXIF) data. This metadata includes the time and date information and GPS information related to when and where the photograph was taken.
Depending on the nature of the dispute, this metadata can be used to isolate the potentially relevant photographs from the others. For example, if the dispute is in relation to a particular event photographs taken before, on or after the event can likely be located. If the dispute involves work that was conducted at a particular location, the GPS data can be used to locate photographs taken of the work done at that location.
Foldering/filing or naming conventions: Ideally the photographs will follow a particular naming convention or are stored in folders with descriptive names, including dates, location similar to the information that you would find in the metadata. If this information has been included in the file names and folders it will then be possible to narrowly target the review on those photographs which are most likely to be responsive.
Deep learning: This machine learning method involves training a neural network to recognize certain objects. Depending on the issues in dispute it might be possible to employ deep learning to identify which photographs contain particular items of interest. This will avoid having to review photographs that contain irrelevant subject matter. This is the same technology used by Google Images.
When dealing with a large volume of standalone photographs it is best to discuss their production with the opposing party and come to an agreement with respect to how they will be produced. Producing large quantities of photographs without consultation can result in disputes among the parties leading to increased costs and potentially sanctions.
Moreover, some software, Apple Photos for example, enable increased functionality by mapping the photographs to geographical locations which can then be viewed on a map. This functionality is not available if the photographs are loaded into a standard review platform.
T. James Cass is manager, review services and senior counsel at Heuristica Discovery Counsel LLP. Heuristica has offices in Toronto and Calgary and is the sole national law firm whose practice is limited to eDiscovery and electronic evidence. Send comments and Industry Perspectives op-ed ideas to email@example.com.