Enterprise Search: Mapless and Lost?
February 5, 2015
One of the content challenges traditional enterprise search trips over is geographic functions. When an employee looks for content, the implicit assumption is that keywords will locate a list of documents in which the information may be located. The user then scans the results list—whether in Google style laundry lists or in the graphic display popularized by Grokker and Kartoo which have gone dark. (Quick aside: Both of these outfits reflect the influence of French information retrieval wizards. I think of these as emulators of Datops “balls” displays.)
A results list displayed by the Grokker system. The idea is that the user explores the circular areas. These contain links to content germane to the user’s keyword query.
The Kartoo interface displays sources connected to related sources. Once again the user clicks and goes through the scan, open, read, extract, and analyze process.
In a broad view, both of these visualizations are maps of information. Do today’s users want these type of hard to understand maps?
In CyberOSINT I explore the role of “maps” or more properly geographic intelligence (geoint), geo-tagging, and geographic outputs) from automatically collected and analyzed data.
The idea is that a next generation information access system recognizes geographic data and displays those data in maps. Think in terms of overlays on the eye popping maps available from commercial imagery vendors.
What do these outputs look like? Let me draw one example from the discussion in CyberOSINT about this important approach to enterprise related information. Keep in mind that an NGIA can process any information made available to the systems; for example, enterprise accounting systems or databased content along with text documents.
In response to either a task, a routine update when new information becomes available, or a request generated by a user with a mobile device, the output looks like this on a laptop:
Source: ClearTerra, 2014
The approach that ClearTerra offers allows a person looking for information about customers, prospects, or other types of data which carries geo-codes appears on a dynamic map. The map can be displayed on the user’s device; for example a mobile phone. In some implementations, the map is a dynamic PDF file which displays locations of items of interest as the item of interest moves. Think of a person driving a delivery truck or an RFID tagged package.
A traditional keyword oriented search system cannot provide this type of output. The keyword vendors have to jump through hoops and license third party tools to output useful maps. Once the technology is available, then many keyword search vendors have to figure out how to extract the geographic data from text, images, and videos.
Is this possible? Yes.
Is this cost effective? No.
Will the cobbled together system work in high demand, high data flow environments? Not likely.
One of the problems that organizations face is that procurement teams looking for a better search system unconsciously or intentionally avoid tackling imagery, geographic features, and outputs with context.
The result is the silliness that talks about “federated” search, data “fusion,” or “information governance.” These terms appear to address the need to extract geographic features, relate the data to other information, and output a compound report that provides high value information.
Exactly where is that delivery person now? Is traffic an issue? Is the customer contacting the vendor demanding delivery information?
Many enterprises need this type of NGIA information access. Yet procurement teams often do not know what they do not know. Furthermore, the mid tier consulting firms are often equally uninformed. The hapless employee has to consult several systems and figure out how to plot the data on a visual display that is useful.
Traditional search vendors offer partial solutions. For example, Exalead has a search system for product development, component procurement, and inventory. However, for an employee working with parts, a geographic output placed on a map of the building showing exactly where the part is located is often helpful. A dynamic map allows the employee to walk to the part location, click on a dynamic map, and see the details of the subcontractors providing the components for the part.
Does the Exalead or AutoCAD PLM system perform this NGIA report?
Not without additional engineering and third party software.
That’s the problem. Keyword search vendors are stuck in a keyword swap and the contextual value of compound displays on geo-type outputs are ignored or viewed as an add on.
Geographic functions, like temporal functions, are central to NGIA information retrieval.
Is your enterprise search system equipped to handle video, digital pictures, and imagery? Does your system extract geo-data? Does your enterprise search system output what users actually need to address a business problem with current information?
The geo-code blind spot is just one of many weaknesses in traditional keyword search systems. Little wonder that keyword centric vendors are chasing customers who are more elusive than a blob of mercury.
NGIA vendors, on the other hand, are gaining traction because their systems do not ignore information rich geo outputs.
A colorful and somewhat wacky Grokker or Kartoo type display is not the type of map that some employees want as a method of information access. Cartoons have their place. Geo displays can be more useful and easier to figure out. Their absence in most enterprise search solutions speaks loudly about the sophistication of a vendor’s enterprise search system.
Learn more about next generation search at www.xenky.com/cyberosint.
Stephen E Arnold, February 5, 2015
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