Building Digital Ecosystem Architectures by Skilton Mark

Author:Skilton, Mark
Language: eng
Format: epub
ISBN: 9781137554116
Publisher: Palgrave Macmillan
Published: 2015-12-16T00:00:00+00:00

In Table 2.1 we see a cup of coffee, but a machine interface needs to understand and interpret this. Indeed, there have been great strides in image recognition, so much so that airports and search engines can scan images of human faces and complex objects to match patterns for recognition. Further information about objects can be gained by sensors. For example, embedded temperature sensors could enhance information about the object. A “smart cup,” for example, could have a built-in heat sensor and another sensor that could detect the liquid’s level in the cup. The temperature sensor could automatically detect the temperature and alert the user to its contents, saying “too hot” or “getting cold.” The liquid level sensor could order a refill or suggest a different beverage via a connection to a mobile app. Yet for all these advances in sensors, does this enable the semantics and pragmatics of the situation to be fully understood? Are all scenarios for a cup of coffee defined? Are all desired outcomes covered? As we can see, there are many potential outcomes, and it is for this reason that in the design and development of digital workspaces we are seeking to establish better outcomes from information at every level from the objects, content, status, relations to users, and environment. This is a recurring theme that is seen in many modern digital enterprise scenarios, where the issue of digital enablement has moved beyond syntax and basic semantic indexing to more advanced semantics and pragmatics in order to create what we describe as the contextualization of information; that is, information relevant and in context for the user’s situation and desired outcomes.

Contextualization

The process by which semantic meaning can be identified and imparted into the situation at hand

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