Personal Experience Computing

The paper Personal Experience Trace: Orienting Oneself in One’s Activities and Experiences will be presented at the CHI 2010 Workshop on Personal Informatics. The paper talks about vision and concepts behind the ContextDrive and Zeitgeist frameworks and presents their journal UI incarnations, as of January 2010. It is a workshop paper. So it doesn’t present work on related systems, but instead focuses on own results.

Here is the abstract: In this paper, we present steps towards adequate support for answering the central questions of orienting oneself within one’s past, current, and anticipated future activities and experiences, along with application areas, which will benefit from such support. The experience-trace concept is introduced and it is shown how support for mental time-travelling within and via elements of one’s activities and experiences can be implemented as re-finding elements within one’s experience trace. To this end, two interactive journal user interfaces are proposed: ReflAction Journal and (GNOME) Activity Journal. They are enabled by the ContextDrive and Zeitgeist frameworks and their respective experience-trace implementations.

Personal Semantic Technology

Trends in technology development indicate that personal computers could develop into always-on companions, i.e. possibly wearable, personal helpmates. Anticipating this sketch of the future, we aim at designing what we call personal semantic technology. This technology will be capable of reflecting personal meaning of computer-represented objects, as emerging and developing from them being involved in a user’s activities and experiences. We investigate and test our approach with today’s mobile computers, which can be seen as forerunners of the above envisioned machinery. Digital technology is accompanying early adopters in an ever increasing amount of situations. On the one hand, this personal technology is tool and medium for a multitude of its users’ activities and experiences. On the other hand, in the future, it might serve as a personal witness of its users’ activities and experiences, possessing precise and reliable memory.

Personal Experience Trace

Personal experience traces are one of the core concepts enabling personal semantic technology: A user’s experience trace represents a consolidation of “computer-experienced” events related to this user’s activities and experiences. The experience-trace notion reflects that a user’s behavior leaves traces within his/her personal computing machinery, which can be exploited towards this user’s benefit. This is facilitated via logging events and marking them with a variety of labels, some computed and others user-indicated.
The purpose of a personal experience trace is to mirror what a person actually does and experiences by capturing a continuous, comprehensive, and coherent picture of it. This picture encompasses traces referring to objects of retrospective, current, and prospective character. It is continuously evolving as the user acts and experiences. This said, we see and accept the principal gap between what humans do/experience and what computers can sense and represent of it. We respectfully understand this gap as a design challenge and consider it mandatory that a user is and feels in absolute control of this representation.

Supporting Mental Time-Travel

Mental time-travelling is what people do when they use their “mental eye” to situate themselves in what happened in the past or in what they imagine happening in their personal future. Personal calendars are one example of a tool facilitating backward and forward mental time-travel. Additionally, they serve to schedule future “events”. Please note, that the “events” represented by calendar items do not denote the same thing as the events capturing a user’s doing and experiencing into the personal experience trace.
The experience-trace implementations ContextDrive and Zeitgeist can not only capture when a calendar item has been created or modified, but, more importantly, what time span it refers to. Thereby, calendar items are turned into labels and container items for what actually happens during the time span in question. Plus, calendar items can be appropriated, for example, to serve users in relating their preparatory and follow-up activities to the represented “events”. The ReflAction Journal facilitates this via drag’n’drop. Further, the analysis engines of both ContextDrive and Zeitgeist are currently expanded, in order to automatically achieve this relating of events to labels and other higher-level entities. This is brought forward by investigating experience-trace induced notions of relatedness, according to the above introduced personal-semantic-technology approach.
To conclude, experience-trace implementations add an application-independent time-bound layer to the experience of using computers. Users are thereby enabled to relate to and situate themselves within representations of their past, current, and future activities and experiences.

New User Experience: Re-Finding Documents, Re-Situating, and Beyond

Employing the above introduced concepts and means opens up new ways of going back to what one did and experienced.

1. In order to re-find a document D, users can employ their memories of situations in which they created, viewed, modified, or otherwise used this document.
2. Vice versa, users can re-find all situations in which they interacted with a certain document.
3. Users can re-find other items interacted with while, before, or after working with D.
4. Employing “user-language labels”, such as calendar items or task representations, users can re-find “collections of use”. Such a collection of use could, for example, be the working set of documents last used for working on a task, before having switched to another activity.
5. Experience-trace implementations support users in bringing to their minds what they did during the last month, which helps them with reporting tasks.

In referring to the ReflAction Journal as a visualization of their personal experience trace, users see their item-related interaction intervals composed from events. They also have available labels denoting, for example, their scheduled “events” and tasks. Furthermore, properties of these labels and of the item-related events can be employed to search for items and events as well as to filter and scope the result set displayed, according to the users’ needs.

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