opening it up with Common Lisp

Favorite weblogs

Lisp Related

Bill Clementson

Finding Lisp

Lemonodor

Lispmeister.com

Planet Lisp

Politics

Orcinus

Talking Points Memo

This Modern World

Working for Change

Other home

Polliblog

Recent Readings

Book review: Darwinia
Reviewed: Friday, August 11, 2006

Summer reading: Spin
Reviewed: Saturday, August 5, 2006

Runner
Reviewed: Tuesday, July 18, 2006

the Omnivoire's Delimma
Reviewed: Wednesday, July 12, 2006

the Golem's Eye
Reviewed: Wednesday, May 31, 2006





tinderbox

Information Ecology: Open System Environment for Data, Memories and Knowing
Geoffrey C. Bowker and Karen S. Baker, 2000 , (Paper URL)
Saturday, October 16, 2004

Bowker and Baker examine in the interconnections between memory, data, information and knowledge in the context of a study within the Long Term Ecological Research (LTER) community. In our time, databases have become fundamental but the "data [within them] never stands alone." Indeed, the memory of an organization exists in multiple interacting forms and includes both data and procedures. As organizations grow, the data and the interacting web of procedures grow with them. This becomes especially problematic when data must be shared across space and time; standards must be created and agreed upon, units must be unified, formats must be formed and all must be maintained. The obvious answer is to make heavy use of metadata. Here, however, the problem recurses -- how are to set standards for the metadata? Indeed, "the proliferation of metadata standards within environmental science [is] as significant as the proliferation of data standards themselves." "This suggests the need to accept that there are very real social, organizational and cognitive machineries of difference which continually fracture standards into local versions." The solution for this requires not more standards but a "careful analysis of the political and organizational economy of memory practices..."

The authors posit two dimensions: data and knowledge. Data can be local or global; knowledge can be tacit or explicit. This creates four quadrants:

  • Local data, Tacit knowledge: Data management
  • Global data, Tacit knowledge: Information management
  • Global data, Explicit knowledge: Domain knowledge
  • Local data, Explicit knowledge: Research knowing

Information flows from quadrant to quadrant with feedback across boundaries and with change within each quadrant. The whole forms an ecology of information. If the dynamic flux of this ecology is ignored, we "risk putting in place systems that create barriers to inquiry." The examples the authors present are suggestive and show that more than technology is required for database management.

Another insight of this paper is that the process of infrastructure building is far more complex than it first appears. It is hard to define what Information Managers do.

Software engineers write programs that can be demonstrated in conferences and written up in journals. Domain scientists produce data which can be run through a research protocol and published in journal. Information managers on the other hand service, manage, and design the flow of information (as do librarians). They take the materials -- organizational, technical and data -- which are at hand and make it all work together. Their work is rarely written about; when spoken of, it frequently has the 'what I did during my holiday' patina: it is too specific to generalize and seems too small scale to label important. It is the work of bricolage as much as work of engineering, in Levi-Strauss's (1966) terms.

Information management is a vital part of any system but we "don't have good ways of talking about [it]..." This process oriented work is "frequently invisible and rarely supported." In attempting to bring this work to the forefront, Bowker and Baker are performing a valuable service. As they put it, we live in a tension between homogenization and diversification. "The question then is not only 'with what epistemological and ontological frameworks shall we work?' but also 'how can we work at the intersection between different frameworks?" The goal of long term studies and real world data mining is not 'how can we capture the data?' but rather 'how can we build an open information ecology in which the changing data can live and prosper today and tomorrow?'

This is challenging paper from well outside the standard views of Computer Science. Perhaps that is why it feels so refreshing and correct to me. It is easy for technologists to view problems in simple terms but real problems and answers must live in contradiction with one another in a world open to change. I believe that the broader analysis of systems in political, organizational and essentially human terms will help us do better science and produce better answers for a complex world.


Home | About | Quotes | Recent | Archives

Copyright -- Gary Warren King, 2004 - 2006