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Research On Information Provenance And Long-term Revolving Around Data Visualization

Posted on:2018-09-04Degree:MasterType:Thesis
Country:ChinaCandidate:L J RenFull Text:PDF
GTID:2348330536968489Subject:Education Technology
Abstract/Summary:PDF Full Text Request
At present stage,information provenance and long-term retention of information resources around the world is conducive to using information resources with maximal efficacy,promoting the development of social,and raising national competitiveness in resource utilization.Information resource carries the memory of a nation,is a concentrated reflection characteristic of age in various areas,in order to realize the extension of national memory,need to inheritance and preservation of information resources.In the new information environment,information resources with its proliferating formats and expanding quantity become the mainstream,which poses challenges to the inheritance and preservation practice.This paper analyses the stages of the information resource lifecycle of preservation techniques,legal regulations,difficulties in national policy levels,if it is not resolved in a timely manner the policy is bound to cause the disappearance of permanent information resource,for national cultural heritage brought an indelible memory and human losses.Summarizing information heritage and preservation policy research and ensure the sustainable use of resources,and provide references for further study.Currently,data visualization technology and its applications always suffer from the issues,such as low-accurate visualization,limited representation solutions and blurred inherent information.In order to overcome the shortages caused by these issues,this paper claims a research program to investigate web-access information via visualizing its inherent huge data in the manner of three-dimensional maps.This research program utilizes Maple-based data processing design,and consequently founds dedicated thematic maps to illustrate the processed results based on ArcGIS geographic information system.Via accomplishing visual comments on the resulting maps,this research brings in six visualization methods to carry out analyses and visual expression operations.Based on these achievements,this research successfully proposes a novel solution that will find out the inherent information within web-access data.Besides,this paper finishes several experiments to prove that the mentioned research program will advance the precision insides data visualization applications and the variety of representation work.Cartogram is a map depicting attributes of spatial data by distorting two dimensional original maps while preserving their topology.In this paper,a novel cartogram thematic map is adopted to express population growth.The best fitting model is proposed to predict the population of randomly selected modern cities in a provincial area of P R China.The result is visualized with cartograms to produce useful findings for scheming a population planning.It is expected that this method will be an essence for the study of population prediction models.Scale of population is considered as an important index into economic development and reliable and effective models for prediction of population provide perhaps the only governing measure over both population control and its dynamic impact on economy.Based on historical demographic data around the cities in a province of P R China,the results of three prediction models the GM(1,1)gray model,the Malthus population growth model and the linear regression model are presented,with prediction errors being less than 1%,which proves the efficiency of these models.The average of the gray model and the linear regression model is used in predicting population and a cross-platform Cartogram visualization system is developed to represent the trends of population change by integrating geographic information and population data to form comparative cases for the revelation on population control and economic growth.
Keywords/Search Tags:Information provenance, Information retention, Cartogram, Topic map
PDF Full Text Request
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