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INTERNET AND THE DISSEMINATION STRATEGY:A CASE OF MARCOM ASSOCIATES LTD. Presenter: Agaba Francis Uganda

INTERNET AND THE DISSEMINATION STRATEGY:A CASE OF MARCOM ASSOCIATES LTD. Presenter: Agaba Francis Uganda. Objectives. Participants to appreciate the role of internet in statistical data dissemination Understand the importance of data dissemination Know the key points for data dissemination

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INTERNET AND THE DISSEMINATION STRATEGY:A CASE OF MARCOM ASSOCIATES LTD. Presenter: Agaba Francis Uganda

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  1. INTERNET AND THE DISSEMINATION STRATEGY:A CASE OF MARCOM ASSOCIATES LTD.Presenter: Agaba FrancisUganda

  2. Objectives Participants to appreciate the role of internet in statistical data dissemination Understand the importance of data dissemination Know the key points for data dissemination Understand the need to adopt the project model other than Traditional Public Administration model (TPA)

  3. INTRODUCTION . What is the Internet? The Internet is a worldwide network of thousands of linked computers compared to "a giant international plumbing system" (University of California, Berkeley, 1997). Remember that the Internet is not just one3 gigantic computer with all of the information; rather there are many computer centers, and we are connected to this "plumbing system" somewhere along the line.

  4. In Uganda, the cost of browsing the internet for most last mile consumers of Uganda Telecom’s data service is expected to fall with an increase in the number of customers with the arrival of the seacom submarine cable. In the past, Uganda Telecom has been receiving bandwidth via satellite and this has been quite costly. To day, the new bandwidth being delivered over fibre not only means more capacity and higher speeds but also that increased bandwidth.

  5. Our recent efforts are concentrated on improving local public access to statistical data and encouraging local statistical data to be more accessible for global communities. We are trying to put up a well connected infrastructure and web based information management systems to realize these objectives.

  6. DATA DISSEMINATION • What is data dissemination? It is the process of extracting raw statistical information from a data base or data repository to produce statistical output that can be understood and used and has relevancy to the statistical query (objective) it seeks to satisfy.

  7. IMPORTANCE OF DATA DISSEMINATION • Knowledge base: Statistical data form an integral component of the knowledge base required by nations, governments, regional authorities, companies and individuals to understand the constant changes that occur within a society. • Policy making: Statistical data is essential to the development of informed policy formulation, implementation and evaluation. With out appropriate data, policy decisions must be made within a vacuum with little understanding of the impact or the effect on individuals or society in general.

  8. Research: Scientific research utilizes statistical data in one form or another. Not only is it important to be able to compare data within a country consistently over time, but comparisons between countries within a region are also increasingly becoming the focus of research. It is clear that international comparability of data including concepts, classifications and dissemination standards need to be addressed as high priority areas.

  9. Theory of economic and social development. Priotise statistics coupled with new technologies (Agaba Francis 2009) It states that for nations especially developing countries to take off economically and socially, they must at all possible costs priotise statistics for proper planning while considering changes in new technologies. For the world has changed, we must change with it. The achievement of this will not just create employment opportunities but a frame work for growth. Most nations have the capacity to priotise statistics but there are many competing priorities.

  10. MARCOM ASSOCIATES LTD At Marcom Associates, we are training the local councils on how to use one of the most adopted research tool called generative picture. The objective is to have the community participate and avoid the bias associated with the so called expert. The traditional models of data collection and analysis have one thing in common, i.e. the data collection and analysis is done by the outsider excluding the participants e.g. the researcher.

  11. Because of the obvious biases associated with the traditional methods of data collection, the project model has come up with its own peculiar methods of collecting data and analyzing it with the concerned people Some of these methods include, PRA and RPRA. The supremacy of these models is the community people are the ones who, -I identifies the problem -analyze their problem -why there are problems -propose solutions or strategies for solving the problem.

  12. The so called expert does not need to carry any data collection instrument because the people them selves do the data collection. Some of the tools used include, community mapping, resource maps, transect walk etc. These participatory approaches derives from the work and writings of a renowned Brazilian Community work and Scholar known as Paulo Freire. Using the Generative Picture and drawing from Paulo Freire’s Community Empowerment Theory, the questions below can be answered.

  13. Questions • Give the most appropriate title for the Generative picture • Identify five main problems faced by the community in picture providing two reasons why you think so. • What are the most probable causes for each of the problems identified above? • Suggest practical solutions to each of the problems.

  14. Key points for data dissemination • Ensure that the data is extracted correctly • Full explanation of meta data is included as footnotes or summary notes • Confidentiality should not be compromised • Use efficient tools to extract data • Deliver data to the user in a form it can be used • Deliver data on time

  15. The way forward The national statistical office needs to evaluate the objectives and the fundamental principles behind its dissemination strategy. Issues that need to be addressed include but not limited to; • The potential to attract new data users. • The potential effect on existing dissemination channels. • The availability, efficiency and cost of the new service. In order to bring together producers and users of information, there is need to adopt a system of UNdata which is an internet based data service that brings UN statistical data bases within easy reach of users through a single entry point.

  16. Conclusion Statistical data needs to be disseminated to the widest possible audience so that the greatest benefit can be achieved from the investment made by the national statistical office. Statistical data is not just necessary but fundamental to the majority of public policy decisions therefore the data must be readily available in a timely and easily accessible manner in the medium of choice of the user.

  17. END

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