Building a Knowledge Infrastructure for Learning Communities

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Building a Knowledge Infrastructure for Learning Communities Kate O’Dubhchair Senior Lecturer, Faculty of Informatics and Director of the Higher Bridges Regional Studies Centre, University of Ulster, Northern Ireland [email protected]

James K. Scott Assistant Research Professor and Program Director of the Community Analysis Center University of MissouriColumbia, USA [email protected]

Thomas G. Johnson Frank E. Miller Professor of Agricultural Economics and Director of the Community Policy Analysis Center University of MissouriColumbia, USA [email protected]

Throughout the world, local communities are being asked to take greater responsibility for their collective future. These communities must both interface with the changing face of local and regional administration, redefining roles and functions, (Scott and Henness, 1999) and meet the challenge of competing in the global marketplace while yet retaining a sense of place and a community. Communities must acknowledge that the nature of modern society is one of ongoing change. The most important factor in the viability of communities is their capacities to learn how to manage this change together.

While much of today’s change is related to the growing importance of information, the management of change has been greatly facilitated by advances in information and communications technology (ICT), and partic ularly by advances in the field of informatics. However the theoretical underpinnings of informatics have been developed almost exclusively for organizations in the private sector. In the main, the aim of this work has been to create methodologies and associated tools and techniques to deliver an ‘added value’ information product. The advent of community informatics takes the discipline into a new arena and one in which there are dual goals of promoting information services and the information product as a factor in economic development and ensuring access to information as a means of social equity and social inclusion.

To date, community use of information and ICT’s has developed in a ‘piecemeal’ fashion as a series of rather unconnected initiatives. Community applications have focused on information access or information creation. 1 To be effective in the global knowledge-based economy, we argue that communities will need a much more comprehensive, systematic approach. Local community members will need more than ICT centers or information networks. They will

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See Gurstein, 2000 for an excellent history of the development of community uses of ICT.

The Electronic Journal on Information Systems in Developing Countries http://www.ejisdc.org

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need to build a new knowledge infrastructure that will facilitate the ongoing process of knowledge generation, and support collective learning.

In this paper, we define what we mean by ‘knowledge infrastructure’ and assert its importance to community informatics. We will outline our argument in four main sections. First, we review the wider context of changes affecting communities in a rapidly globalizing world. Next, we define the concept of knowledge infrastructure and describe its key components and processes. Then, we report initial results from a project designed to build this type of infrastructure in rural communities in Ireland. Finally, we draw on this experience to propose a series of issues for future research. Development Trends at the Community Level Our work in rural communities in Ireland and in the United States has convinced us of the vast and critical need for local knowledge infrastructure. We start by reviewing key trends in social and economic development, particularly noting the effects these trends have on rural or disadvantaged communities around the world.

Technological change Technological change is so ubiquitous that it heads most lists of change. From the perspective of rural communities, technological change affects more than just the way in which products and services are produced. Technological change has and will alter the very economic bases of communities, their relationship with the rest of the national and global economies, and their internal social structure.

In production, the most significant economic forces are the rising importance of information, communication, nanoscience, genetic engineering, and other technological applications. In addition to the direct effects of the changes on employment, these innovations have led to increased use of services (particularly information related services), and reduced use of goods (particularly, raw materials) in the production processes of other manufacturers.

Technological change also affects the relationship that people share with each other, with their communities and with their governments. People are more mobile, more flexible in their

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choices of employment and residence, and have greater access to information. Technology, then, facilitates and, indeed, foments globalization, localization, and the various aspects of changing governance.

Globalization Increased trade and global competition among firms is usually the assumed consequence of this globalization. Of greater significance to communities, however, is the movement of information, technology, capital and people. In addition to the competition in markets for goods and services, then, is the heightened competition among communities around the world for jobs, residents, and finances. Globalization has left many communities unsure of their best strategies. Public investment in human capital often increases the mobility of a community’s labor force. In declining communities, this undoubtedly reduces the incentive to invest in people. Industrialization incentive programs are very risky and, when successful, attract employers that can as easily be lured away again by another community with an attractive incentive offer.

Localization Localization is the growing role of local conditions and local choices in determining the prosperity of a community. The reasons for the growing primacy of local circumstances include technological change, changing social and political attitudes, and, ironically, the globalization that has opened competition with the world.

Overall we observe an emerging economy in which the definitions of economic base, services, public and private enterprise, competition, and even sectors themselves have become blurred. We see an economy in which trusted linkages—linkages between production growth and employment growth, between base and non-base indus tries, between activity and place—have been severed. We see an economy in which linkages have become more numerous but more decentralized, and where distance can become a resource rather than a cost or constraint.

Settlement Patterns Changing settlement patterns also affect the nature of contemporary community life. In the developed world, Increasingly, people are fleeing the congestion, crime and high cost of

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urban life for the quieter, safer and more affordable surroundings of the rural and metropolitan fringe areas. The availability of an information highway infrastructure makes this more possible today than previously. In many areas, rural jurisdictions lack the planning resources and the physical infrastructure to respond to this kind of “exurban” growth. This growth then exacerbates existing fiscal constraints for local governments, and in some cases, contributes to problems with water quality, air quality and other key natural resources.

In the developing world, migration often flows in the opposite direction. Lack of employment and human services in rural regions pushes many households to relocate to the cities. In 1995, approximately 55% of the world’s population lived in rural areas. By 2000, only 50% lived outside major cities. By 2010, demographers believe that rural areas will be home to less than 40% of the world’s people. These opposite migration flows in the developed and the developing worlds, if unchecked, will contribute to massive economic, socio-political and ecological problems on a global scale. No matter how we address changing settlement patterns, communities will need new knowledge to explore alternatives and to act in their collective interests.

Changing Governance Throughout the world, many nations are working to decentralize governance and decision making, wherever possible to the local level. Communities are faced with the prospect of making more decisions of greater import, than ever before. At the community level, this is often a tall order given small staffs and resources, and limited experience with many of the new areas of responsibility. Each new area of responsibility creates its own problems. In economic development, communities, often neighboring communities, find themselves pitted against each in the competition for migrating employers. In health care, education and social services, communities are faced with new mandates and numerous alternatives for satisfying them.

New governance is a larger trend than just devolution however. It includes a fundamental rethinking of how policy decisions are made and how public services are delivered. Governance systems are changing partially in response to change in societal value s and expectations, and partially due to technological change. One aspect of changing governance is the growing reliance on performance-based budgeting and decision making.

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Performance-Based Government Performance-based government is designed to target limited public resources for maximum impact, to provide incentives for government units to improve the delivery of public services and to hold government more accountable to specific measurable objectives. This trend is seen in a variety of policy contexts. Communities will be expected to devise local strategies to achieve specific, targeted objectives. The central government will then provide financial assistance and the regulatory flexibility to implement that strategy provided the community achieves its stated objectives. Communities that do not meet these objectives will have fewer resources and/or more restrictions on how central funds are invested.

This trend places even more importance on the capacity of communities to manage information, and develop strategies to interact with that information in ways that help them achieve measurable improvements in the delivery of public services.

Decentralization of Decision Making The most fundamental aspect of changing governance is the tendency toward greater decentralization in the decision making process itself. Throughout the world, local people are demanding more direct influence over the decisions affecting their communities. Information technology and communication infrastructure tends to support this decentralization process by reducing the transactions costs involved in becoming informed. They also facilitate the process of achieving agreement by reducing the transaction costs involved in communication.

Community Knowledge Infrastructure In many ways, these changes experienced by communities are all symptomatic of a global transformation from an industrial to a knowledge economy. In the late nineteenth century, communities adapted to a major economic change from an agricultural to an industrial age. At that time, changes in industrial technology and improvements in transportation systems facilitated mass manufacturing and economic exchange at greater distances. Progressive communities responded to these new opportunities by investing in physical infrastructure. Mass production of goods required improved streets and roads, rail systems, and other key

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components such as reliable electrical, natural gas, water and waste water systems. The viability of most communities depended on the availability and capacity of these systems. In the 21st century, physical infrastructure is necessary, but insufficient. In today’s economy, what companies produce is not as important as what they know, and how they apply that knowledge. As they did in the previous century, communities that keep pace with economic change will need to build a new kind of local infrastructure designed to help their employers and residents generate and apply new knowledge. We define community knowledge infrastructure as the set of locally specific physical, informational, educational, organizational and cultural resources needed to facilitate community learning and action toward a desired collective future.

Clearly, investments in this type of infrastructure must go well beyond assuring general access to the Internet and ICT. Thus far, most national policies with regard to information and communication infrastructure in rural communities have focused on the "supply" side. That is, a key objective is to assure some minimal level of access to telecommunications infrastructure to residents of all places—great and small. Addressing "demand" side issues is of equal or greater importance. In this case, demand is the capacity and desire to use information technologies. The European Union now funds a broad range of projects designed to enhance demand, and build the capacity of local residents and community leaders to use information technologies to make better decisions in the private, public and voluntary sectors. The program, called the Information Society (IS), provides funding for training in computer literacy and application, as well as the development of computer-based community decision support systems. The capacity of individuals to participate in the Information Society is determined by the quality of information and telecommunication infrastructure, as one would expect. However, other factors include widespread education and training in the use of information, effective promotion of IS, technical support for the diffusion of IS activities, and public awareness.

The key concept and components of a community knowledge infrastructure are outlined in Figure 1 from a socio-technical perspective. In this section, we briefly introduce these features, working clockwise from the outside of the diagram to its center. We follow the same approach to organize the main body of the paper to illustrate and discuss the theoretical and

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practical importance of each feature for the development and growth of community knowledge infrastructure.

Before we examine each term, a general observation is required. While both social and technical elements are needed in community informatics, the diagram illustrates the criticality of the social or cultural context in the development and growth of knowledge infrastructure. Gurstein (2000), Malhotra (2000) and others have shown that in times of rapid change, it is very important to build information systems and knowledge management strategies that reflect and support the social nature of knowledge work. An information processing approach to building knowledge infrastructure would focus on the structure and limitations of a prescribed information system. People who want to learn from this information system must conform their inquiries to the model and structure of the IS. The approach described in Figure 1 is much more dynamic. It focuses on how people actually produce and use knowledge in a social setting. The most important components in a meaningful community knowledge infrastructure are the cultural, organizational, and programmatic resources in place to cultivate its use by community members.

Key Knowledge Infrastructure Concepts: Cultivating Community Knowledge

Three key components of the necessary cultivating resources are listed in the outer circle of the diagram, under the heading of “cultivating community knowledge. Since a commitment to these resources is fundamental to community knowledge infrastructure, it is appropriate to begin our discussion by elaborating on each.

Public Engagement

Sound development theory, and practical community informatics begin from a strong commitment to broad, authentic public engagement. The work of building, maintaining and applying a local knowledge infrastructure for use in development would be impossible without drawing on all available organizational and institutional resources of the community. Project leaders with access to the most sophisticated technological, analytical and financial resources could not achieve success in community informatics, unless the system was designed with and for all interested stakeholders.

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Figure 1: Key Components of Community Knowledge

Cultivating Community KnowldedgeLearning Knowledge

LEARNING

ACTION COMMUNITY MEMORY

KNOWLEDGE

Public involvement must occur at every stage, from asset mapping and needs assessment, to user analysis, system design, development and implementation. As the knowledge infrastructure becomes more broadly and deeply linked with the life of local organizations, and institutions, the probability of success increases. The infrastructure must support the objectives and work of all key stakeholder groups; and this support must include outreach activities, demonstrations, training and technical assistance, and, when necessary mediation between the groups the technology. Information Quality Public engagement is the first step in building knowledge infrastructure. However, this engagement is of limited use if stakeho lders are uninformed, or misinformed about key community issues. A second feature of a learning community is a strong commitment to collecting, managing and disseminating quality information. This commitment must be ongoing, flexible, and community-directed. Public agencies and NGOs now collect a wide range of data that is potentially relevant to local community and economic development groups and local governments. Often these data are collected and used by individual agencies

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for their own purposes – but they are rarely linked and stored in a single comprehensive local information system. Consequently, local development groups often lack the information they need to adequately plan, implement and evaluate their local service delivery. Communities that want a knowledge infrastructure will do well to partner with all agencies that collect primary or secondary data at the community level, and find a way to keep this information current.

ICT Access and Applications Finally, general access to ICT services and the availability of specifically-adapted analytic and decision support applications are obviously critical to local knowledge infrastructure. To date, most community information projects have been focused, almost entirely on providing access to computers and the Internet to all interested citizens. In the last fifteen years, community partnerships sprang up thorough out the world to build freenets, community information networks, tele-centers, and computer access in schools, libraries, information kiosks, etc., with the goal of assuring the widest access possible to new technology. Again, these efforts are necessary but not sufficient. With access (and the requisite training and technical support) project leaders must also assure that the system can be used by local stakeholders to address specific issues or needs as directly as possible. For example, Bhatnagar (2000) lists three different types of applications for local knowledge infrastructures: 1) improved public service provision (such as on- line registration or technical assistance for constituents; 2) decision support for community groups and local government officials; and 3) access to useful (market) information for businesses and community groups. Some of these applications can be based on more or less generic software and information products (Cf., Scott, Johnson and Mundell, 2000). However, effective applications will often need to be customized to meet unique local circumstances.

Communities that seek to build dynamic and useful knowledge infrastructure must work hard to cultivate demand for these services among a broad range of users. They must also build a culture that values information access, and commits to developing and supporting an expanding number of local applications.

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Learning, Knowledge and Action: A Continuous Process With a local culture and program in place to cultivate community knowledge, we move to the center triangle in Figure 1 – the most important part of the infrastructure. The diagram illustrates that gaining knowledge is a continuing process, which proceeds from learning, to knowledge to action. As an individual, one learns and become knowledgeable. Senge ( 1999) points out that in the Western world we often confuse knowledge and information, missing the vital link of knowledge and action. Senge quotes Humberto Maturna as saying, “ All knowledge is doing. All doing is knowledge.” He goes on to say “knowing about” concerns information. He adopts John Searle’s definition of knowledge as the capacity for effective action. Senge suggests that learning only diffuses when there are learning processes whereby human beings develop new capacities for effective action. In defining key concepts it is important that we consider in more detail the role of information, knowledge, and memory in the process of learning. As we have said, in many respects, learning by a community (and the role of information, knowledge and memory) is like learning by individuals.

“Learning occurs by improving actions through better knowledge and understanding (Foil and Lyles, 1985), encoding inferences from history into routines that guide behavior (Levitt and March 1988), and developing insights, knowledge, and associations between past actions, the effectiveness of those actions, and future actions (Foil and Lyles, 1985). It involves the understanding of reasons beyond immediate events (Croasdell, 1997).”

”A learning organization is one where members of the organization learn individually but also interact on an on-going basis and collectively reflect on the results of their action (Eppel and Conklin, undated).” A learning community is composed of individuals committed to increasing their and their community’s knowledge base. A learning community must be underpinned by an infrastructure that encourages growth of the knowledge base and distribution of the knowledge throughout the community. Advance in the private sector has shown that learning organizations do not just happen. They require the right conditions and leadership to affect the change. Communities must learn to learn. “Public learning is the principle through which individuals are encouraged to openly learn and explore that which they do not know… Team learning is the

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discipline whereby groups of individuals develop capacities for coordinated action such that the intelligence and capacity of the team improves to a point that it exceeds the aggregate intelligence and capacity of the individuals that make up the team (Guthrie, undated).” Community learning is therefore primarily a group activity and as such can be assisted by a group support system that aims to reduce process costs and increase process effectiveness and efficiency. Like wise community learning could be alternatively described as the process of enhancing and using the community knowledge base. As a caveat to this section on ‘learning’ it must be added that a learning community will be one that has also mastered the ability to ‘unlearn’. Unlearning is the process whereby learners discard knowledge and make way for new responses and mental maps. 2 In a time of change, unlearning becomes a vital part of the process. Communities must recall, reevaluate and make new responses to new situations. ICTs can provide a framework within which facilitates learning and unlearning. Perhaps the most important conceptual tool for facilitating community learning is found in the distinction between information and knowledge. Information is data, organized in a manner that has meaning in a particular context. For example, we can build a regional database collating all the appropriate information about the region into one central resource. This is an information product with added value because of the manner in which the data have been organized. Knowledge however involves a process between such information and a person or persons. This assimilation of information with existing knowledge leads in turn to new knowledge. Learning and knowledge are inextricably linked. A ‘knowledge-based’ society implies something more than simply a society of knowledgeable people. It implies knowledge in relationship with action. Information is a flow of messages, new meanings, or additional insights, which affects existing knowledge, changes it and thus is part of a process that generates new knowledge. Information is a commodity that is understood within the context of the beliefs and values of the recipient.

There are two types of knowledge that are critical components of a community knowledge infrastructure (O’Dubhchair, Scott and Johnson, 1999). Universal or global knowledge refers to that body of knowledge that has been made explicit through the scientific method. In fact a much bigger body of knowledge is that of tacit knowledge or local knowledge, knowledge

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For a more detailed discussion of ‘unlearning’, see Scott, Johnson and Mundell (2000).

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which is not of immediate commercial value but which underpins the foundations of society. Polanyi (1966) drew a distinction between tacit knowledge and what he termed explicit knowledge. According to Polanyi, tacit knowledge is personal, context-specific and hard to communicate. Explicit knowledge is codified and transmittable in formal systematic language. For each individual, tacit knowledge includes both knowledge of ‘what is’ and also knowledge of ‘what ought to be’.

Nonaka, (1990) developed the generic concepts of the process of ‘knowledge conversion’. Nonaka visualizes the process as a spiral, a continuous pattern of growth and change. We tend to restrict our thinking in the West by assuming that making knowledge explicit must involve passage through language. In fact it can be argued that transfer of tacit language is least efficient by language. The most enduring model we have of successful transmission of tacit knowledge and of the spiral of knowledge growth is that of the apprentice and master craftsman where tacit knowledge is made explicit in action and learning occurs through observation, imitation and practice.

Knowledge Work Important aspects for consideration in moving to a knowledge-based community are the characteristics and role of the knowledge worker. “Knowledge organizations are the container for knowledge workers, the vehicle through which they apply their knowledge (Conklin, 1996).” Knowledge workers are changed by the information in their environment, and they in turn seek to change others through information.

Shum (1996) describes knowledge work as follows:

1. 2.

3. 4.

Knowledge work is conducted in teams. The problems faced by knowledge workers are difficult to control. Requirements, constraints and solutions must be regularly renegotiated. The problems are so complicated (“wicked”) that they can only be tackled through argumentative methods. Knowledge work is increasingly interdisciplinary. The different disciplines of team members lead to inevitable conflict, debate, negotiation and compromise (Shum).

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Knowledge work is dominated by communication, especially negotiation and augmentation. Rittle (site) tells us in fact that ‘wicked ‘ problems can only be tackled through augmentation. Collaborative augmentation tools are one example of new software developments to meet the needs of knowledge workers. These tools provide the media for arguing and evaluating in the meeting process and in doing so, “encourage an important degree of precision and explicitness for manipulating and experimenting with knowledge, coupled with augmentation of human social processes” (Buckingham, 1996).

Community Communications Support System Current thinking on communications tends to be restricted to e- mail or Internet access. Considering community informatics as providing the backbone of a community decision support system, a group support system, there are many other facets to be considered. Community informatics demands a shift from the view of an information system as one that develops and distributes information in packages of technology to a multi-purpose system, where the infrastructure facilitates access and interpretation by (potentially) differing individuals and groups.

A good community communications support system will offer: 1. 2. 3. 4.

A means of overcoming ignorance and confusion through dissemination of appropriate information; Neutral space to encourage participation; A medium through which all voices can be heard; An environment in which the communications mode is matched optimally to the task.

The interface component of the system would communicate information both ways. It would accept requests from users, respond with information or questions, process information and knowledge, and communicate knowledge. It would also “learn” about the user, adapt to the user’s preferences and record processes. In this sense the community communications support system is not only a flexible access to the community knowledge and memory, but also a creator of knowledge and memory.

Early theorists in studying group work advocated ‘group support’ to increase effectiveness and help avoid ‘process losses’. GSS software is available and provides help for many of the process tasks that groups undertake: agenda setting, identifying problems, generating

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alternatives, recording meetings’ etc. However, research indicates a need to take further account of task type, information richness requirement and individual adaptation and interface needs. At the community level a community Process Support System would incorporate existing software tools by guiding group selection and thus facilitating quality outcomes.

The ideal community process support system reflects the idiosyncratic nature of each community. It reflects and accommodates different preferences. It also includes indicators and measures of the distributional nature of impacts, and both reflects and supports the community’s decision- making process rules. For example, since communities are typically spatially arrayed, maps and geographic information systems are common components. The spatially arrayed consequences of public choices then articulate many of the distributional consequences of the public choices. Many decisions are semi- structured or unstructured. Structured decisions are simple rule-based cases with no latitude in choice. Unstructured decisions are intuitive and based on past experience. Semi-structured decisions are partially but not strictly rulebased. Decision support for unstructured decisions is best if it is simulation based. Models best support semi-structured decisions. The ideal community process support component, as part of a full-blown community decision support system will help community members make decisions in these cases as well. It will capture, articulate and store various types of information and knowledge. Formal knowledge is that which we are most familiar. It is codified or easy to codify, easy to quantify and transmit, and universal in availability. Informal knowledge is more personal and local. It is often about the process rather than the product of decision- making. It is difficult to quantify, capture or communicate. Reliance on formal research knowledge often ignores important cultural or historical issues that are critical to effective and efficient community decisions. CDSS attempts to achieve a balance between both types of knowledge. The process component endeavors to acquire, manage, integrate and articulate both formal and informal knowledge, so that both can be employed in collective decision-making.

Community Memory

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The community memory system at the center of Figure 1 represents the most techno logical feature of the knowledge infrastructure. Walsh and Ungson (1991) refer to organizational memory as stored information from an organization’s history that can be brought to bear on present decisions. “By their definition, organizational memory provides information that reduces transaction costs, contributes to effective and efficient decision- making, and is a basis for power within organizations (Croasdell, undated).” Croasdell summarizes the literature as follows: “Organizational memory is a generic concept used to describe saving, representing, and sharing corporate knowledge. It supports cooperation in a multiple task and multiple user environment. The concept includes technical, functional, and social aspects of the work, the worker, and the workplace (Durstewitz, 1994). Organizational memory includes both formal knowledge - that which can be conveyed by the written record (e.g., corporate manuals, databases, filing systems, etc.) and informal knowledge (e.g., interpretations, intuitions, conventio ns and process shortcuts). (Ackerman, 1996).” Organizational memory, when efficiently produced, organized and applied, generates several types of benefits for the knowledge-based community. For example: 1. 2. 3. 4.

It helps make thinking explicit, reducing the time required to solve problems; Meetings and team work become more efficient; Coordination among team members is improved; New team members become productive more quickly because knowledge of the project is explicit; and 5. Departing team members leave some of their informal knowledge with the team (Conklin, undated). However, in a community application, the concept of memory has a more fundamental role than simply a means to efficiency. Technology has contributed to a hijacking of the notion of memory. O’Donaghue, (1994) reminds us that human beings identity is crucially dependent on memory. Origin, place, direction, all arise from the integration of memory and experience. Therefore, we see that community memory is more than a warehouse of information. It is a dynamic resource continually growing and changing. It is the collective knowledge of the community and is greater than the sum of individual knowledge. A community remembers its unique character and values and determines its reaction to and with the wider environment through the memory system. Necessary conditions for the development of community

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memory include both the creation of an appropriate culture and the provision of the necessary technological infrastructure. 3

Community memory is a storage and retrieval system for the community knowledge, much of which is informal. It makes the community decision- making process faster and more efficient by avoiding needless repetition. It also provides continuity over time and space and reduces disagreement by community members over facts. It includes a record of process (procedural knowledge) and associates individuals with processes and events. Community memory requires a flattening of the governance structure where all interested community residents are involved in the generation, acquisition, distribution, interpretation and use of information. On the other hand, it has been pointed out, that community memory creates its own flatter organization by empowering individuals. In order to encourage learning, communities must move away from mechanistic hierarchical structures and adopt a more flexible and organic form of governance. This requires partnership and a new style of leadership that encourages openness, reflectivity, and the acceptance of error and uncertainty (Morgan, 1986). A Case Study: The Show Me Project The Show Me project was established to develop and test community knowledge infrastructure for Irish communities and, in so doing, help them to become learning communities. It is a collaborative, interdisciplinary and international venture between Fermanagh District Council, Udaras na Gaeltachta, the University of Ulster, and the University of Missouri, USA. The project involves two communities—County Fermanagh in Northern Ireland and the Gaeltacht (or Irish-speaking) region of County Donegal in the Republic of Ireland. The project was funded under the EU Special Program for Peace and Reconciliation and so, Show Me has a secondary agenda in developing new mechanisms for inter- institutional cross-border cooperation.

The Show Me Project’s four primary objectives are to: • •

Develop, implement, and evaluate quantitative community decision support tools, including a community information system; Train and equip local community leaders in the use of this CDSS and in so doing assist them to develop community learning skills;

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For a more detailed discussion of the conceptual framework for and the ideal components of community memory systems, see Scott, Johnson and Mundell, 2000.

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Assist the community members in applying CDSS tools to address pressing community issues; and Demonstrate results and disseminate them to other rural regions within Northern Ireland and the Republic of Ireland.

The project achieved wide community involvement through community advisory panels (CAPs), sectoral focus groups, and the collection of primary data. The advisory panels represent various sub-regions, sectors and interests in the communities. These panels and focus groups represent fundamental components in the communities’ knowledge infrastructure. Panel members represent as much of the socioeconomic, demographic, and geographic diversity of the communities as possible. The CAPs have guided each step of the project and has taken ownership of the products.

The CAPs, through their definition of economic sectors and sub-regions within the community, are incorporating informal knowledge into their emerging community information system. The data collection process also captured this perspective. For example, the Fermanagh CAP identified “education and training” as a distinct sector and as an issue for in-depth analysis. The CAP has also designed questionnaires and the structure of the resulting Social Accounting Matrices.

In order to gather sensitive and often informal information about the community, and to better understand specific sectors and issues, several focus groups were convened. The focus groups continue to generate valuable quantitative and qualitative information about the communities and provide forums for ongoing debate of key local issues. A computerized simulation game, called Show Me Sam, is the first of several planned software products. Show Me Sam was developed to help community residents understand economic linkages both within and between regions. Players create a simple economy and watch the linkages among sectors lead to income and employment multipliers. The game was produced on CD-ROM and made available to schools and community groups as the first stage of a major capacity building exercise.

Each community was asked to identify a key local issue on which they would like a sectoral profile produced from the Show Me database. As in many areas the future of health and social services in rural Northern Ireland is very uncertain. CAP members in Fermanagh

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therefore asked the project team to prepare a report on the Economic Importance of Health and Social Services to the County. This report has now been completed, and is being used to inform the debate about the rationalization of acute services. The Donegal CAP chose the Irish Colleges sector for their first profile.

The first decision support tools, inter-industry accounts, were completed in Fall 1999. Other quantitative decision support tools will follow. In the second phase, the decision support tools will be utilized to build community decision support systems. This will involve the development of data collection interfaces, a dynamic community information system, interfaces for the various community decision support tools, and other services needed for each community’s knowledge infrastructure. Throughout the project community decisionmaking capacity is being enhanced through education, the nurturing of community processes and the empowerment of residents. Even while this leaning process occurs, community decision- makers are applying the tools being generated by the Show Me project. Both communities now see themselves as learning communities and are increasingly aware of the asset of their community memory coupled with the assets of human partnership and collective planning. Both are investing further in the creation of a knowledge infrastructure and in the derivation of suitable performance indicators and measures of success.

The Show Me Project in Ireland has created discernable changes in the communities in question. The two communities have started to identify their common issues and interests. In both communities the advisory panels have started to widen their membership and scope. Both communities are getting youth involved in the priority setting processes. In both cases, the communities have taken ownership of their respective projects. Discussion: Towards a Research Agenda The Show Me Project and other experiment sin community knowledge infrastructure development are just beginning. Many lessons have been learned, but much more research is needed. As research continues, we expect applications of community informatics and the development of community knowledge infrastructure will yield very important results, both for informatics as a discipline, and for the future of developing countries. In his seminal book, “The Lexus and the Olive Tree”, Thomas Friedman (1999) concludes that the greatest dual challenge we face in the next decade is to prepare communities to compete in the fast-

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paced global economy, while also helping them to foster and support the local heritage and quality of life. The work of building knowledge infrastructure may be the most important response to such a challenge. The following section describes the most pressing research needs in this area as we see them.

Empirical Research Informatics is a young discipline. In terms of a theoretical base for the discipline it would be fair to say that computer scientists have concentrated on building the body of knowledge that underpins the technology rather than its implementation. We have hypothesized that the social processes and programs that foster and support community knowledge are critical to the success of projects in community informatics. Applications of these projects are growing rapidly in number (Cf., Gurstein, 2000 and Scott, Johnson and Mundell, 2000). Comprehensive evaluations of these projects will greatly enhance our ability to test this hypothesis, and to learn what worked and what did not. Theoretical Development A second area of needed research involves the theoretical underpinnings of community informatics. Our work on community learning and community memory grows out of the organizational learning and learning organizations literature (Senge, 1990). Boland and colleagues (1994) warn that this framework can result in significant simplification of key issues and in serious limits to the effectiveness of the local knowledge infrastructure. Specifically, they argue that community learning and knowledge projects that feature a consensus building approach will severely limit opportunities for group learning and effective actions – particularly in times of rapid change. To address these limitations, Boland, et. al. draw on the fields of hermeneutics and semiotics to develop a framework they call ‘distributed cognition’. We believe this approach offers community informatics opportunities for important new research directions.

Similarly, Malhotra (2000) argues that knowledge management must foster multiple perspectives on past and present conditions to best anticipate the future. Almost every important challenge for communities involves multiple stakeholder groups with conflicting views of the issues. To be effective, community informatics must develop new theoretical tools to accommodate and thrive on these differences.

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Sustainability A third area for future research in community informatics involves the sustainability of such projects. Clearly, the costs of: 1) building and maintaining information systems, 2) engaging individuals and groups with effective outreach and communication support, 3) assuring general access to ICT and its applications, 4) providing continuing mediation and technical assistance, and 5) providing appropriate incentives for prospective users of the infrastructure, are significant and ongoing. How to cover these costs, and how to address related issues of scalability, legal and ethical standards, and customization, particularly for disadvantaged communities, will be a key to the success or collapse of community informatics.

The challenges of building a knowledge infrastructure for developing communities are many. Nevertheless, communities of the 21st century cannot compete without advanced ICT applications, and without a commitment to build on a continuing process of learning, knowledge and action. References Ackerman, M.S. (1996) Definitional and Contextual Issues in Community and Group Memories. Information Technology and People Amidon, D. (1998) Collaborative Innovation and the Knowledge Economy: Towards the ‘World Trade of Ideas’. http://www.entovation.au.info/future.htm published for the Society of Management Accountants, Canada. Balasubramanian, V. Undated Organizational Learning and Information Systems Bhatnagar, S. (2000) Social Implications of Information and Communications Technology in Developing Countries: Lessons from Asian Success Stories. The Electronic Journal on Information Systems in Developing Countries, 1, 4, 1-10. http://www.is.cityu.edu.hk/ejisdc/vol1/v1r4.pdf. Boland, R., Ramkrishnan, V.T. and Te'eni, D. (1994) Designing Information Technology to Support Distributed Cognition, Organization Science 5(3):456-475 Conklin, E.J. Undated Designing Organizational Memory: Preserving Intellectual Assets in a Knowledge Economy. http://www.gdss.com/DOM.htm Croasdell, D.T. Undated Using Information Technology To Support Memory And Learning In Organizations. http://hsb.baylor.edu/ramsower/ais.ac.97/papers/croasde2.htm

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Drucker, P. (1994) Knowledge Work and Knowledge Society, the social transformation of this country. http://www.clayton.edu/kohler/drucker.htm Eppel, R.C. and Conklin, E.J. (undated) Blending Cultural Transformation and Groupware to Create a Learning Organization, http://www.gdss.com/learning.htm Fiol, C.M. and Lyles, M.A. (1985) Organizational Learning. Academy of Management Review, 10/4: 803-813. Friedman, T.L. (1999) The Lexus and the Olive Tree: Understanding Globalization. New York: Anchor Books, 1st Edition. Gurstein, M. (2000) Community Informatics: Enabling Community Uses of Information and Communications Technology. Hershey, PA: Idea Group Publishing. Levitt, B. and March, J.G. (1988) Organizational Learning, Annual Review of Sociology, 14, 319-340. Malhotra, Y. (1998) Deciphering the Knowledge Management Hype. Journal of Quality and Participation 21(4): 58ff. Malhotra, Y. (2000) Knowledge Management and Virtual Organizations. Hershey, PA: Idea Group Publishing. Morgan, G. (1986) Images of Organizations. CA: Sage Publications, Inc. O’Dubhchair, K., Scott, J.K. and Johnson, T.G. (2000) Community Decision Support Systems: Managing Knowledge for Community and Economic Development, in: Garson, G.D. (Ed.), Handbook of Public Information Systems. New York: Marcel Dekker, Inc. Polanyi, K. (1966) The Tacit Dimension. London: Routledge & Kegan Paul. Scott, J.K., Johnson, T.G. and Mundell, M. (2000) Community Memory: An Internet-Based Approach to Enhancing Community Learning, Knowledge Management and Public Participation in Local Governance. Paper Presented at the Conference on “Which Public Administration in the Information Society”. Brussels. Senge, P.M. (1990) The Leader's New Work: Building Learning Organizations. Sloan Management Review, Fall: 7-23. Walsh, J.P. and Ungson, G.R. (1991) Community Memory, Academy of Management Review, Vol. 16, No.1, 57-91.

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