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.