I stumbled upon this architecture competition entry titled “Quameleon” by Ayssar Arida Associates:  http://q-news.archsitestudio.com/files/AA_MEIAC_MIMESIS.pdf.  This project allows occupants to design their own temporary public spaces by using light/sound qualities to augment existing spaces.  Occupants may upload new sound files or video files into database or choose from existing uploaded files/qualities.  As a networked system that compiles a community database of information, it is potentially very effective in creating a democratic, participatory design solution for the problem of the design of public space by committee.  However, a search engine is not a part of this system.  This lack of searching ability limits not only the access of users to information as database grows, but also limits the capacity of the system to build toward a consensus “design” of public space.  In applying concepts from our class discussion, there seems to be an opportunity for a PageRank inspired search engine to identify the most popular light/sound qualities based on their induction of desired moods or atmospheres.  These moods/atmospheres have the potential of becoming popularized by different communities with different agendas, taking the project a step further in its effort at creating a democratic model for the development of public space.  How would this system, which I’m calling Public SpaceRank, work based on the PageRank model?      

The system could use PageRank logic to rank combinations of spatial qualities (light/sound) that are the most popular ways to induce desired moods/atmospheres, adjusting and constantly updating the ranking as different qualities are uploaded into the network through the addition of sound/video files.  Users would begin to assign keywords to specific combinations of qualities as they modify the public spaces. For example, Isaac Hayes music, red coloration, and low lighting levels might be assigned the keywork “romantic” or “sexy”.  Users could search this keyword database to identify desired atmosphere/moods.  Based on the PageRank logic, two types of ranking systems would be needed to then translate these keywords to specific combinations of qualities.  First, qualities are ranked based on the number of in-links they have currently attributed to them by relevant keywords.  Second, keywords would also carry a score based on their number of links to other relevant qualities.  The final ranking system would consider both of these criteria, identifying keywords that seem to select more popular qualities, and qualities that seem to be selected by a greater number of keywords.  A keyword search would yield qualities deemed communally most popular.  In this way, a search system based upon the PageRank logic may be able to yield powerful community access to shared moods/atmospheres and thereby provide the means for emergence of unique community identity in the evolution of the ongoing design of public space.