Paper-based Sharing of Annotations

As discussed in the previous chapters, collaboration is an important element of document-based knowledge work. While paper documents are well-suited for co- located collaboration in many aspects, they constrain remote collaboration (in com- parison to digital documents) because their contents are only available physically and not digitally.

Section 4.4.1 above described how CoScribe can be used in co-located collabora- tive settings. Each user disposes of his or her personal pen. This enables to attribute the activities of individual users to this user. Moreover, several pens can be used in the same time on one single sheet of paper on one display. Further, the users can work on multiple documents at a time.

One page per sheet

Two pages per sheet Four pages per sheet

Figure 5.15: Example layouts of printouts

This section focuses on the second collaborative setting: remote sharing of an- notations. CoScribe supports asynchronous collaboration over distance. It enables users to share their annotations with collaborators. These can access shared annota- tions in their document viewers and/or print the document including these anno- tations. This section discusses an unobtrusive interaction technique that allows the user to classify the visibility of annotations directly when writing the annotation on paper.

Scenario 9 (Private and Public Annotations). It is absolutely acceptable for Sally to share her annotations of the lecture script with the other members of her learning group. Sometimes she makes off-topic notes, which she prefers to remain personal. For example, she makes an appointment with a fellow student and notes his phone number or she notes what she wants to buy after the lecture. For this reason, she marks these notes as private. They are not shared with other persons.

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Interaction technique. CoScribe offers three levels of visibility with which the user can classify individual annotations:

• Private visibility: The content is not shared with other users.

• Group visibility: Each user can set up groups with several other users. In dif- ferent contexts (e.g. a specific lecture, a seminar etc.), the user can be member of different groups. Content with group visibility is shared with the members of all groups of this user that apply to the given context.

• Public visibility: The content is visible to all users in this given context (e.g. all students attending this lecture, all participants of the seminar etc.).

Our goal was to provide an interaction technique which can be seamlessly inte- grated with annotating and which is quick and reliable. Related research [LGA+07, LGHH08] discusses several means for classifying annotations suggesting spatial differentiation, pen differentiation and differentiation with pen gestures. Provid- ing on the printout separate areas for each visibility level and requiring the user to write a note in the corresponding area is impractical for annotations, which often have to be made at specific context positions on the slides. Using a different pen for each level is intuitive but requires extra hardware. Moreover, research shows that students rather use one single pen than switching among many marking tools [Mar97]. A third solution consists in classifying notes by performing specific pen gestures. However, current digital pens cannot recognize gestures by themselves. Gesture recognition would have to be performed by the back-end system. Hence, it is not possible to provide feedback on success or failure of the gesture recognition in the mobile setting where pen data is not immediately transferred to the back-end system. Moreover, the system would have to distinguish gestures from ordinary handwritings or drawings. For this purpose, the cited research papers suggested to use additional hardware like a foot pedal or a second pen. Novel generations of dig- ital pens which include gesture recognition and buttons could solve these problems in the future.

We therefore propose a fourth concept, which is inspired by buttons in Graphical User Interfaces because the interaction of pressing button is quick, easy and reli- able. For this purpose, a toolbar containing several printed “buttons” is printed in the center region of each paper sheet (see Fig. 5.16). Each button represents one vis- ibility level. A visibility is associated to an individual annotation by tapping with the pen on the corresponding button before or after writing the annotation. More- over, a visibility level can be set or modified later on by making two consecutive pen taps on the button and on the annotation. While no graphical feedback on the tagging is provided on the printed slide unless the user makes additional mark- ings, the visibility level is visualized with specific colors in the CoScribe viewer and on subsequent printouts. The viewer contains similar buttons as the printouts for defining or modifying visibilities. The same interaction technique is used for tag- ging annotations with semantic categories.

Figure 5.16: A button toolbar is printed on each page. These buttons provide for defin- ing the visibility level of annotations (upper buttons) and for tagging them with semantic types (lower buttons)

Discussion. Performing a simple pen tap is quick and can be easily included into the annotation process. Moreover, defining visibility is optional, allowing the user to maintain a natural annotation style. If no visibility is chosen, the default level defined by the user is set. This reduces extraneous cognitive load during the an- notation process. According to the interviews conducted during the evaluations, a very appropriate default level is the group level. With respect to privacy, it is typ- ically not considered critical to share annotations with other members of the own group, as these are personally selected by the user. With this default level, only a small number of annotations that contain private information or that shall be visi- ble to all users must be explicitly classified with a visibility level. If appropriate, the interaction technique could also support less or more than three levels or more than one group the user belongs to.

Applying visibilities to entire annotations instead of unstructured sets of pen strokes requires clustering pen strokes into annotations. For this reason, CoScribe uses a clustering algorithm for handwritten input that relies on temporal and spatial information. Possible errors can be manually corrected by the users. The software viewer therefore provides two functions for splitting annotations and merging pen strokes into one annotation.

In contrast to gesture-based differentiation, our approach is faster and reliable even with current pens that do not include displays nor processing power for ges-

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Figure 5.17: A LED (within the red circle) provides feedback when the pen taps on a printed area

ture recognition. Moreover, it requires only one single pen. A correct interpretation is guaranteed, as determining the pen position on a paper button does not imply uncertainty. Current pens moreover provide graphical feedback to the user at the moment the button area is tapped on (Fig. 5.17). Hence, the user can be sure the classification has been correctly recognized.

A problem of current Anoto pens is that they cannot provide feedback on the cur- rent mode. For this reason, changes in the classification by selecting a button do only apply to the annotation created immediately afterwards, then the system returns to the default classification state. Thus the user does not have to remember a current system state over a longer period of time. If she desires absolute certainty to be in the default mode, she can tap on a ‘default’ button. While a completely modeless design would be preferable, this “semi-modal” design accounts for the two stages of selecting an instrument and an operand and nevertheless copes with the absence of feedback. Novel generations of digital pens that include a display1will solve this problem and make the use of button-based classification more comfortable.