The lifestream by being an example of a digital text, that is volatile, fragmented, distributable and doubtful in terms of its authorship (Bayne 2010) illustrates this dynamism very well, especially in terms of temporal and ontological blurring.

Unable to log on every day, I create discontinuity in the stream. However, the software sometimes fills in those gaps by tampering with the time stamp of a given feed. So although physically offline one day, it looks like I am present. Would that be an example of disembodied presence, a very convoluted example due to the feed being time-stamped backwards!? This happens because the software seems to be taking into account the date the online resource was posted, not when I favourited it. So to make things even stranger my absence/presence has been embodied by somebody else’s online activity.

Immediate questions arise as to the authorship. Who is creating this stream? How can you-not-being-there be assessed ? Uncanny indeed!

Following our discussions of the “uncanny” I began to think about the online ghosts or echos of dead content which still exist in some form, say perhaps in a wiki version history or a Google cached page (lifestream 09.10.2011 #1).  Such data, when it “lived”, might have been considered absolute and definitive, but through constant editing and revision combined with new insights into old knowledge, it has lost its currency and been replaced or updated.  Yet it exists and in many cases is still accessible, thus offering the interested researcher a unique view into the process of learning and refinement that occurred in a given knowledge domain.

A slightly different interpretation of the uncanny can be seen in the result new literacies produce within our existing structures and modes of learning.  The emergence of new literacy skills such as crowd sourced tagging and folksonomy creation “that is controlled by the community of users, rather than an elite group”, (Merchant, 2007) challenges the traditional structures and hierarchies of knowledge coding and classification within the academy.  Given the possibilities for vague usage or personal interpretations of meaning, such informal metadata can produce very different views into a body of knowledge.  When viewed from one perspective verses another (based on something as simple as changing the tags used as filters), one can see the many potential sets of interpretation that might occur.  This truly is a ghost in the machine, an unintended consequence of the growing complexity of the system.  But this ghost need not terrify us. There is nothing false or incorrect about such views into datasets, indeed one might legitimately claim that these ghosts can compliment one another, offering learners the chance at a richer and more complete understanding of a knowledge domain through a “generative uncanny pedagogy”, (Bayne, 2010).