Visual Patent Analysis – What and Why?

For companies it is critical to detect white-spaces and patent minefields early in the R&D cycle each of which can perhaps generate or save millions of dollars at a later stage. Traditional graphs and charts are good for displaying the results of an analysis activity but not for quickening and improving the analysis process.

An increasingly used mechanism is visual analysis of patents that involves 2-Dimensional spatial patent visualization and leverages the capability of the human visual system to identify patterns and anomalies. The key advantages of visual patent analysis are that you can drastically reduce the time-to-insights and explore IP-congested technology spaces in a swift but efficient fashion.

The ease of use and intuitive nature of visual analysis tools makes it easy for even business and R&D teams to use for their analysis needs. (Usually in organizations, the R&D, the patent information team, the legal team, the marketing cum business strategy team and the licensing team are involved in various parts of the IP strategy driving a product.)

Automation Landscape

Other important benefits which visual patent analysis provides:

• Ease of navigation across relationships- Can be used for exploring through networks of relationship between companies, inventors and their research or you can also explore semantic relationships between patent content.
• Quick interpretation – 2-Dimensional spatial mapping of technology clusters remains as one of most comprehensible ways to represent a landscape and can be easily interpreted
• The Peripheral vision advantage – You can benefit from being cognizant of the clusters around your focus area. In some case these “peripheral clusters” may contain the golden nugget you seek.
• Powerful highlighting, search and dissection tools combined with a rich intuitive display makes is easy to detect patterns and irregularities within the patent landscape. Such capabilities make the visualization many times more powerful. For instance Google Maps would’t be as powerful without it’s built in geographical search, highlighting and other navigational options.
• Clusters that are co-located based on semantic similarity are very useful when conducting infringement analysis. (Ofcourse, visual analysis tools must allow for clusters to be generated specifically from the claims section for undertaking infringement analysis)

To sum up, visual analysis is a powerful method to address challenges posed by patent information overload.