This section is to track the discussions on the implementation of "User Context" in KDE. For a more general discussion of context in Nepomuk, check out here.
Though there are numerous definitions of Context out there, we would like to refine the important aspects of context to
Typically Desktop applications and widgets have been available as just normal tools which are in no way more "intelligent" than their physical counterparts (ok, apart from their ability to undo things ;)
They have been heaped with functionality which just adds to the clutter the user is already facing with the growing information-overload. They do nothing more that will help the user to reduce his overload, apart from what he tells them to do. So, something has to be done to tackle this now, when information overload is increasing things are becoming more mobile!!
Continuing the passion for desktop innovation with KDE, we want to induce in our apps the "intelligence" to adjust themselves to the work the user is currently doing. Hence ....
Dikku is a new user context framework that exposes the current user activity and location to both plasma widgets as well as other applications, thus enabling them to adjust themselves to the user's needs.
Dikku means direction in Tamil; when we get lost we generally establish context of where we are based on direction. Currently when we are lost in information, we could look forward to Dikku for assisting us ;) So, I think the name fits. Any suggestions ?
Activities are a "more casual" term for things that range from adhoc grouping of apps and widgets for a purpose (like in virtual desktops) to projects (which have deadlines, tasks and resources).
Currently we plan to track the following information in Dikku:
and allow for:
As Nepomuk project has already handled the bulk of work by doing a lot of research in this area, we can just reuse whatever is possible from them (the beauty of open source !)... Check out related Nepomuk links
The context framework could be implemented in three phases:
The Architecture of Dikku can be split into three major parts:
1. Data Model - how the information is actually stored. We plan to use existing Nepomuk ontologies here
2. Learning Model - how the system observes the user, understands what he is doing and learns to suggest things to the user and other interested agents (apps and widgets)
3. User Interaction Model - how the interested agents adjusts themselves according to the system suggestion; and how the user deals the system and possibly corrects its assumptions to start getting results!