Uses and Potential of Information and Communication
Technologies in Water Development
Water & Development Term Paper
Josiah Johnston, December 14, 2007
This paper reviews theories of information and knowledge, current applications of
Information and Communication Technologies (ICT) in water development, and potential
of ICT in this sector.
Introduction: Theory of knowledge
What is information?
To understand the roles of Information and Communication Technologies (ICT) in water
development, it is necessary to first examine the concept of “information”: what is it, how
is it constructed and legitimized, how is it communicated? “Information” can be thought
of as a recorded piece of knowledge abstracted from context; a telephone number, for
example. However, to interpret a telephone number, one must understand the a larger
context of a telecommunications system will translate a number into an audio connection
with a specific person as well as social conventions of times and situations in which it is
appropriate to call someone. As long as everyone is operating with the same basic
context, we can communicate in informational shorthand with a 10 digit number. Without
that context however, the number is meaningless.
All information and knowledge is embedded in a larger context. When we communicate,
we generally have an implicit assumption that our audience has sufficient background to
interpret our statements. In the case of communication of technical knowledge through
scholarly articles, the audience is assumed to understand the context and have high
reading comprehension. A well-structured communication starts with an estimation of
what background knowledge the audience already possesses, and whatever background
may be missing. The context needed to interpret information in a scholarly article is
usually quite significant. To make the publication process tractable, the audience is
narrowed and most of the context is left out or given as references. These practices grew
from the historic technologies of pens and printing presses in which duplication or
modification of contextual information was expensive. But even if all necessary
contextual information was referenced, comprehension of it would require a significant
investment into education. In most modern societies, significant educational investments
have only been made in a small fraction of the population.
Who are the actors involved?
According to knowledge management theory, there are three roles involved in the
creation and reuse of knowledge: producers, intermediaries, and consumers [1]. These
roles may be distributed among different people, or filled by the one person. Producers
and consumers are self-explanatory. Intermediaries package knowledge to make it more
useful to consumers. Consumers can be divided into four classes that each have distinct
needs. Shared work producers are members of the same team, and produce knowledge
such as working documents or emails that they later reference. Shared work practitioners
have similar educational and professional backgrounds, but work at different sites on
different projects. Expertise-seeking novices have occasional need for detailed
knowledge, and cannot be assumed to possess the technical
Under traditional views, a population can be divided into four sets: academics or experts,
policy-makers, practitioners, and the general public. Practitioners are the most
heterogeneous set; depending on the context, practitioners could be regional water
boards, civil engineers, farmers, or community residents. Academics, policy-makers, and
a subset of practitioners are assumed to have high levels of reading comprehension, and
at least passing familiarity with the paradigms of technical design and policy discourse.
How is information created and legitimized?
The scientific method is regarded as the process by which “legitimate” knowledge is
discovered. This is typically viewed as a linear process in which highly trained academic
experts make new discoveries, then publish them in journals that are read by academics,
policy makers, and well-educated practitioners. Eventually these academic papers trickle
down to the larger audience of practitioners via adult education, books, trade
publications, manuals, etc.
According to Karl Popper, the process of knowledge creation begins with abduction, an
inexplicable psychological process through which we use our imagination to create a
theory. Next, the theory is developed sufficiently to make an observable prediction that, if
not observed, could disprove the theory. If the theory passes a rigorous test of
falsification, it is accepted as a working theory [ref]. In practice, theory development and
testing are generally accompanied by background readings, which are easier for people
with high levels of education and experience than those without. Still, knowledge
creation can be a democratized process, even though it is easier for some than others.
Knowledge legitimization, however, is a messier process. According to Thomas Kuhn,
scientific knowledge is usually advanced by filling in the blanks of an accepted paradigm.
Developing a new paradigm requires developing a well-defensible theory, convincing
young academics of its truth, then waiting for older academics that hold contrary theories
to die [ref]. Kuhn’s theory does little to describe the process of legitimization in mundane
terms of individual actions. In practical terms, knowledge legitimization means
publishing a paper in a respected, peer-reviewed journal. Educational credentials and
institutional affiliations help considerably in the review process. Also, because reviewers
are people who have previously published in the journal, there is a danger of journals
developing an exclusive policy that is biased against submissions by authors who are
outside of an inner circle. For example, the journal “Cell” is largely considered to be
inaccessible to authors outside of its clique [ref]. Consequently, a group of elite academic
experts controls the means of knowledge legitimization.
How is information disseminated or found?
Under traditional views, information originates with experts, then passes through peerreviewed journal and into the wider public domain. To understand the perspective of an
end-user of information, a more nuanced picture is needed. Marketing campaigns that
initiate communication with an audience proceed quite differently than user-initiated
searches for information. For example, hygiene-related information is often conveyed
through public education campaigns that include mass media, personal conversations,
pamphlets, and primary school curriculums. User-initiated acquisition of information
utilizes self-study (e.g. reading at a library or online research), conversations with peers
(e.g. talking to experienced practitioners or neighbors), or conversations with experts
(e.g. attending classes, hiring consultants, or talking to extension agents). User-initiated
information retrieval requires access to certain resources, a basic understanding of
background issues and terminology, and time.
Increased participation
Dublin Principle 2 sets a goal of increased participation, “Water development and
management should be base on a participatory approach, involving users, planners and
policy-makers at all levels.” From a theoretical perspective, increasing the involvement
of practitioners in knowledge creation and dissemination could increase the rates of those
activities. Knowledge is developed by creating theories and pitting them against realworld experience. Increasing the number of people who create and test theories (through
increased participation) would then speed up the process of knowledge creation.
Similarly, increased participation in sharing knowledge (e.g. through radio-call ins shows
that focus on irrigation practices, or conversations between farmers), would speed up the
rate of knowledge dissemination.
Actual roles: Set up context & running examples
Hygiene knowledge, in theory, could spread at no cost if neighborneighbor conversations transmitted it. In practice, it often needs
jump-starts with school programs, facilitated community meetings,
pamphlets, radio programs, etc. Other knowledge requires more
educational commitment to master than is typically transferred
through informal lines or brochures: engineering knowledge on
laying pipe, maintenance schedules; accounting & managerial
knowledge on capital costs, keeping books, scheduling O&M, etc.
Current Uses of ICT in Water Development
ICT has x majors roles in Water Development: lowering costs of publication and peerreview, organizing content, facilitating greater public participation in water planning
content creation, supporting integrated water-resource planning for river basins, and
making technical information available to non-specialists.
Journal Publication
Academic -> academics + policy-makers: Journal Publication
Low cost to publish documents online. Higher costs to send through
referee process: office space, staff, editors, web hosting, printing
costs, publishers profit margin. Most journals make profits by selling
advertisements as well as extracting publication fees from authors
and subscription fees from readers.
New trend of Open-Access journals that do not charge subscription
fees for online access. They recover costs by charging higher
submission fees and generating lower-or-no profits. [Elaborate on
PLOS model, look for open-access specific to water and/or
development,
Technology highlight:
Free text searches.
Google: docs are weighted by popularity and reference words
Can restrict to scholarly publications or a subset of journals
Limitations: Cost. Also, articles are written in a specialized
vocabulary and assume a high level of familiarity with the field. This
type of publication is consequently largely inaccessible to
practitioners who lack a high level of formal education or high levels
of reading comprehension.
Academic -> practitioners
Water Development Toolkit by Asian Development Bank
Extension agents
Trade journals
Workshops, Trade conferences
Consultants
Practitioner <-> markets + practitioners
India: eChoupal, etc
Blue Water Run’s peer grant review
Modeling hydrological cycles and withdrawals
Potential
Collaborative publication of overview documents to unify the
field
Social construct of collaborative working group is needed.
Technology merely lowers certain costs of collaboration
Means are available: Connexions, Wiki books
If I build it, will they come?
Practitioner involvement
Informatics
Aggregation
Unify publications and mailing list responses through structured
publication.
Indexing beyond free text searches
Structured vocabulary
Based around describable things (measures, ranking, categorical
keywords, written summaries, etc)
Allows users to navigate without a
Accessibility of interface
Promoting consistent data collection methodology; providing data
collection templates that providing a starting point for project
analysis that, once filled out, provides means of finding comparable
projects and enables quantitative analysis.
Pattern Recognition Analysis
numeric and categorical data: Expanding point-representation to
probabilities and class distributions
Intro to applications:
Our memories and knowledge describe both things we have experienced
and things we have not. Application: examine the pdf of a subclass to
which an incoming project belongs to identify what ranges of
unconstrained variables would lead to desirable outcomes.
Application: Identify similar communities to guarantee a certain
percentage of peer-reviewers for Blue Water Run. Big personal benefit
is trading notes. Big research benefit is reading their notes, doing
comparative analysis, and documenting the findings.
Technical intro:
Transition to numeric descriptions. Subjectivity inherent collection and
interpretation. One methodology incorporates all proposed variables
and determines which affects outcome. Limitation: small number of
variables are allowed relative to a finite number of samples. Number of
variables also limited by comprehensibility of model.
Pattern recognition offers blind selection of relevant variables from a
set, which reduces biases. Modern pattern recognition tools also allow
large number of variables relative to the number of samples and classes.
Example from face recognition.
: how we interpret the descriptions depends on our world view and
beliefs of what indicators are relevant, corrections for collector biases,
Outline of approach
Example of two correlated variables. Build from scatter-plot to
histogram to estimate of probability density function. New way of
building pdf from instances by assuming each instance (aka point), is
really a pdf whose kernel width is based on data collection error (e.g.
the standard error of the mean). Identifying sub-populations, or superclasses.
Expand to hyper-dimensional space, give worm example. Point out that
this is first quantitative documentation of discrete developmental
states in morphology, post sexual maturity. It indicates that our
aging process is regulated and not mere chaos, and that it is a
target for transformative interventions, not the mere gradualism
offered by existing paradigms. Dimensionality of space, number
of classes, number of samples, prediction accuracy from blind
trials. Identification & correction for systematic errors…
1.
Markus, M.L., Toward a Theory of Knowledge Reuse: Types of
Knowledge Reuse Situations and Factors in Reuse Success, in
Journal of management information systems. 2001. p.
file://localhost/Users/josiah/Documents/Papers/2001/Markus/Jour
nal%20of%20management%20information%20systems%202001
%20Markus.pdf.