For keen travellers, subway maps can provide an endless source of fascination. My personal view is that the Tokyo subway map is the most intricate. The Atlantic has looked at this matter more closely, and pronounced the Moscow subway map to be the best they looked at:
But why can subway maps can be so fascinating and useful?:
- The best subway maps treat each station as a node in a network, and show clearly how to move from one station to the next.
- Nodes (subway stations) are shown in context to other nodes, and this can provide rapid visual clues on the likely importance of each node, for example by it's location or by the number of connections it has.
And in fact, research has suggested that many train networks have common design themes.
Meanwhile, subway maps like many other forms of maps are undergoing a rapid technology revolution. The likes of Google Maps and its on-line competitors are changing the way we look at maps. For example, consider the Moscow subway map presented by Google Maps. In some ways it is not as clear as the image above, but it does feature several additional benefits:
- The information has 'depth', for example selecting any of the listed subways will open up more information. Such depth is simply not possible with more traditional maps as the additional information would crowd out the key points
- The information can be rapidly updated
- It is possible to layer the information, i.e include or hide layers relating to traffic, satelite imagery, weather etc.
- The data integrates very well with a range of display devices, such as smartphones
It is useful to compare and contrast the above to patent searching. Even though the world of cartography is changing rapidly, patent searchers are still searching through lists of patents, and this is largely regardless of what patent search engine we use (although some search engines allow you to search through representive images from the patents, a useful feature). These patent lists are getting a lot smarter, and now almost always include the ability to include depth in the information displayed, for example hyperlinks to further information. But patent searchers are still forced to go through what can be long lists of patents, something we would not think of doing for navigating a subway, for example.
And it is not as though current methods of patent searching are completely successful.
Working on Network Patent Analysis (NPA) led us at Ambercite to ask if we could use similar, graphical based principles to improve patent searching as well as patent landscaping. And this in turn led to AmberScope, which applies some of the best principles of subway and on-line geo- or topographical mapping to patent searching.
Are you ready to move beyond searching through long lists of patents? Visit amberscope.com to find out how you can access the intuitive graphical interface of AmberScope. Our strictly limited free beta trial will be starting very shortly, so register now to take full advantage of this.
