visible artifacts

By: Chris Malek

Apr 13 2009

Category: Articles

No Comments »

Prior work seems organized either around awareness of existing content or awareness of activity, but not both.

Awareness of existing content

Han and Kim 2005: This paper describes a context sensitive navigation sidebar that presents parent pages, child pages and sibling pages of the current page with the idea that this should give people more idea of where they are in the wiki.  They claim that it encourages deeper hierarchical structures (6 levels deep vs 3 levels deep) and more linking from page to page.   They defined sibling pages by looking at pages that the parent page linked to.  They had some kind of relevance measure based on linkage of pages which would determine what pages should be listed as siblings.

Hirsch et. al. 2009:  Visual Wiki adds an independent node-edge graph layer on top of a wiki which links related pages and allows an overview of the knowledge in the system that can be navigated.   The paper describes three attempts to make this work.   The first attempt concerned building a node-edge graph automatically from a semantic wiki, while the second and third attempts used traditional textual wikis, with the graph layer being manually maintained independently from the text layer.  All implementations violate one of my core goals: don’t make more work for people by either requiring either one to make semantic linkages, or maintain the graph manually.

Ding et. al. 2007: The authors created a visualization (”CherryTree”) of a wiki used for sharing project proposals which grouped proposals sited at the same research lab together.  In each group, the visualization showed the people owned projects at that lab, and showed what projects they were leads of, and how recently the project pages had been updated.  They were able to do this because they incorporated information from outside the wiki: data from the corporate directory.   They determined project leads by looking at revision histories of the project pages and finding the people who edited the pages the most.  The visualization could also show number of visitors per project, number of editors and connections between projects (a project has a connection if it has shared editors).  A user could mouse over a project to get more information about it.  This work is, however, intended for a very specific use: wikis that house project proposals.  It was also tailored pretty tightly to how the wiki was used in at IBM, and to the organizational structure of IBM.

Espiritu et. al. 2006: In this wiki augmentation (“ENWiC”), a spider crawls the wiki and builds topic maps based on hyperlinks between pages, and uses emphasized text elements (such as headers) as key terms for the content page.  It then uses TouchGraph to display the topic maps as node-edge graphs and offers a user interface that allows users to hand modify the automatically detected topic maps.  It almost satisfies one of my requirements: and it augments an existing wiki without necessarily requiring users to do extra work.  To make it truly useful, they probably do need to do extra work in adjusting and annotating the graph.  It also depends on having a reasonable number of inter-page links, and differentiated header text. The task is also specifically on learning — being able to answer questions based on information to be found in the wiki.  Is that what I intend with awareness of existing content?

Reinhold 2006: A wiki trail is a directed graph of pages followed by a user through the wiki (Reinhold 2006, p. 49).  It can include reversal of path (A -> B -> A) and cycles (Reinhold 2006, pp. 49-50).  Such trails interrelate the pages traversed in a meaningful way (perhaps only meaningful to the user).  The system augments an existing wiki by tracking users as they traverse pages, generating trails from that tracking data and then augmenting the user interface of the wiki with trail visualization which shows where, when one is on a page, other people tended to come from and go to from that page.  They specifically want to augment existing wiki structure and navigation by extending existing wiki software (Reinhold 2006, p. 49).  They want to “reduce manual maintenance in favor of automatic or semi-automatic aids to increase productivity and efficiency” (Reinhold 2006, p. 50)

Ullmann and Kay 2007: The authors created a graphviz driven node link map of wiki pages to give an overview of the wiki and its use.  They colored the nodes by date of last edit, and encoded the relative number of visits to a page in font size.  They linked the nodes by hyperlinks.   They also encoded information about which tickets were related to which page (the platform was Trac, and the subject of the wiki was support for a software development project).   Hovering over one of the nodes gives more information about the node.  The visualization was generated on demand, and so always contained the most recent information.  The results from interviews with users showed that while it worked well with small wikis (around 30 pages), with larger wikis, the visualization became unusable (too much to look through).

Tagging or semantic wikis: Singh et. al. 2007, Giereth and Ertl 2008, Aumeuller 2005.  These all cause the user to have to go in and annotate pages or sections of pages with either freeform tags or RDF annotations.

Awareness of activity

Liccardi et. al. 2008a, Liccardi et. al. 2008b: This paper is specifically about asynchronous collaborative writing on single documents, specifically parallel writing in which participants are assigned separate sections of the end document, and then merge their sections into a coherent whole (Liccardi et. al. 2008a, p. 265-266).   CAWS is a wiki-like system of their own creation.   First, they have four awareness views: one for the user themselves, which shows the documents they’re currently working on; one which shows what other people have done recently; another which allows them to indicate their status (a la iChat) and a page which contains “group awareness information concerning users’ roles, responsibilities, their positions on issues and their status related to goals that they were initially set. ” (Liccardi et. al. 2008am, p. 266).  CAWS also has a document blog and forum to discuss things about the document, a planning feature in which one assigns roles to different participants; typically the owner of the document does this (Liccardi et. al. 2008b, p. 3).  Roles in this case possibly mean “what section do I edit?”  Users can enter estimates as to how long it will take to do their tasks. Finally, users can annotate sections of the document and refer to those annotations in the discussions.  a planning feature in which one assigns roles to different participants; typically the owner of the document does this (Liccardi et. al. 2008b, p. 3).  Roles in this case possibly mean “what section do I edit?”  Users can enter estimates as to how long it will take to do their tasks.

Atzenback and Hicks 2008: Helping people be aware of the community and of their collaboration partners is a good thing.  Such tools also help integrate newcomers into the community more quickly, because it could help them become aware of both the importance of community and also what their role and position in the group is.  Socs is implemented as a standalone browser for Wikipedia, written for OS X in WebKit and other Apple APIs.  It integrates with AddressBook, Mail.app and other Mac apps.  It presents the user with several windows: a browser window in which the article is presented (not necessarily from Wikipedia (Atzenback and Hicks 2008, p. 7); a window listing contributors to the article and how much they contributed; an address book of authors that the user knows; and a 2D map of a social space which shows the people the user knows, but distributed among the 2D space in a structure of the user’s creation.  In that space, those people the user knows and which also edited the article being viewed are highlighted.  The core of Socs is really this social space.  This space provides social reminding and social data mining.  The assumption in this article is that the kind of collaboration in Wikipedia is again that of a group of people making one document, while in a team knowledge base, this is not necessarily the case.   Teams have different goals for their wiki usage than do wikipedia teams.

Suh et. al. 2008: This paper presents an augmentation of Wikipedia which attempts to provide social translucence in an attempt to improve the percieved accountability and trustworthiness of Wikipedia articles.  The tool appears to be a filter for Wikipedia (you view Wikipedia through this other website), and it adds a dashboard to each article and user page.  Above each article which shows (a) a graph of edit activity in the article and its associated “talk” page (b) the list of users with links to their user pages) and (c) a graph for each user showing edit history on the article over time.   On each user page, it shows a similar dashboard, but in this case it shows (a) a graph of the user’s activity over time (b) the list of pages the user has edited (c) graphs for each page showing edit activity on the page over time and (d) a drill down ability which shows each individual edit by the user on a page.  The user page gives an overview of what topics a person is interested in as well as an evolution of those topic areas.

References

• D. Aumueller, “SHAWN: Structure helps a wiki navigate,” in Proceedings of the BTW-Workshop WebDB Meets IR, 2005.
• C. Atzenbeck and D. Hicks, “Socs: Increasing social and group awareness for wikis by example of Wikipedia,” in Procceedings of the 2008 International Symposium on Wikis (WikiSym) Porto, Portugal, 2008.
• X. Ding, C. Danis, T. Erickson, and W. Kellogg, “Visualizing an enterprise Wiki,” in CHI ‘07: CHI ‘07 extended abstracts on Human factors in computing systems, San Jose, CA, USA, 2007, pp. 2189-2194.
• C. Espiritu, E. Stroulia, T. Tirapat, and Insticc, “ENWiC: Visualizing wiki semantics as topic maps – An automated topic discovery and visualization tool,” in 8th International Conference on Enterprise Information Systems (ICEIS 2006), Paphos, CYPRUS, 2006, pp. 35-42.
• M. Giereth and T. Ertl, “Visualization enhanced semantic wikis for patent information,” in 12th International Conference Information Visualisation 2008, London, ENGLAND, 2008, pp. 185-190.
• H.-S. Han and H. Kim, “Eyes of a Wiki: Automated Navigation Map,” in Digital Libraries: Implementing Strategies and Sharing Experiences, 2005, pp. 186-193.
• C. Hirsch, J. Hosking, J. Grundy, T. Chaffe, D. MacDonald, and Y. Halytsky, “The Visual Wiki: A New Metaphor for Knowledge Access and Management,” in System Sciences, 2009. HICSS ‘09. 42nd Hawaii International Conference on, 2009, pp. 1-10.
• I. Liccardi, H. C. Davis, and S. White, “CAWS: an awareness based wiki system to improve team collaboration,” in 8th IEEE International Conference on Advanced Learning Technologies, Santander, SPAIN, 2008, pp. 265-267.
• I. Liccardi, H. C. Davis, S. White, and H. S. O. Southampton, “CAWS: Visualizing awareness to improve the effectiveness of co-authoring activities,” Special issue of Collaborative Computing in IEEE Distributed Systems Online, 2008.
• S. Reinhold, “WikiTrails: augmenting Wiki structure for collaborative, interdisciplinary learning,” in WikiSym’06: Proceedings of the international symposium on Symposium on Wikis, 2006, pp. 47-58.
• A. V. Singh, A. Wombacher, and K. Aberer, “Personalized information access in a wiki using structured tagging,” in OTM Confederated International Conference and Workshop, Vilamoura, PORTUGAL, 2007, pp. 427-436.
• B. Suh, E. Chi, A. Kittur, and B. Pendleton, “Lifting the veil: improving accountability and social transparency in Wikipedia with wikidashboard,” in CHI ‘08: Proceeding of the twenty-sixth annual SIGCHI conference on Human factors in computing systems, 2008, pp. 1037-1040.
• A. Ullman and J. Kay, “WikiNavMap: a visualisation to supplement team-based wikis,” in CHI ‘07: CHI ‘07 extended abstracts on Human factors in computing systems, 2007, pp. 2711-2716.