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No / Many datasets are available in the form of conventional databases, or simplified comma separated values. The machines do not adequately handle these types of unstructured data. There are compatibility issues as well, which are not addressed well to manage the transformation. The literature describes several rigid techniques that do the transformation from unstructured or conventional data sources to Resource Description Framework (RDF) with data loss and limited customization. These techniques do not present any remote way that helps to avoid compatibility issues among these data forms simultaneous utilization. In this article, a new approach has been introduced that allows data mapping. This mapping can be used to understand their differences at the level of data representations. The mapping is done using Extensible Markup Language (XML) based data structures as intermediate data presenter. This approach also allows bi-directional data transformation from conventional data format and RDF without data loss and with improved remote availability of data. This is a solution to the issue concerning update when dealing with any change in the remote environment for the data. Thus, traditional systems can easily be transformed into Semantic Web-based system. The same is true when transforming data back to conventional data format, i.e. Database (DB). This bidirectional transformation results in no data loss, which creates compatibility between both traditional and semantic form of data. It will allow applying inference and reasoning on conventional systems. The census un-employment dataset is used which is being collected from US different states. Remote bi-directional transformation is mapped on the dataset and developed linkage using relationships between data elements. This approach will help to handle both types of data formats to co-exist at the same time, which will create opportunities for data compatibility, statistical powers and inference on linked data found in remote areas.

Geographic Information Systems (GIS) can assist in using information from census data to investigate questions for national and local government planning purposes, such as socio-economic profiles and needs of communities. I will be doing this on the data from the Ethiopian census, scheduled for 2006. . As no Ethiopian geo-referenced data is available at this stage. I am using the 10% sample of the South African Census 2001 data for KwaZulu-Natal (KZN), as a hypothetical population. KZN was chosen as this provides a setting with urban and rural populations, as well as mountainous and flat areas, and so is in some ways similar to Ethiopia. The questions to be asked of the Ethiopian census data are of the form: · What exists at a specific location or in a specific area? (eg what health facilities are there, what is the population)? · What access does the population have to facilities in the area? Does the road network need to be improved to resolve the problem of access · Where are groups of people in greatest need of … (eg where are there clusters of people with disabilities, and are there facilities for them) · What are the characteristics of ... (eg female headed households) and what are these related to (eg HIV/AIDS or migrant labour?) · What changes need to be made to infrastructure to increase service to communities in need? The results for the hypothetical population show that there are areas with high unemployment rates, low school attendance and education levels, high levels of female headed household, and difficulties of access to educational and health facilities. Many households do not have toilet facilities, and obtain water from rivers, which could impact on the health of the communities. Migrant workers were investigated to see if these were likely to be migrants from neighbouring countries, or from other provinces. The numbers in the hypothetical population in these cases are small, so little can be concluded from this.

Gentrification methodologies rarely intersect. Analysis of the process has been cornered to incorporate either in-depth, neighborhood case studies or large-scale empirical investigations. Understanding the timing and extent of gentrification has been limited by this dichotomy. This research attempts to fuse quantitative and qualitative methods to discern the impact of gentrification between census tracts in East Nashville, Tennessee. By employing archival research, field surveys, and census data analysis this project attempts to comprehend the conditions suitable for gentrification to occur and its subsequent effect on residents and the built environment. A model was generated to determine the relationship between a-priori knowledge and empirical indicators of gentrification. Trends were gleaned between these methods, although gentrification’s chaotic and complex nature makes it difficult to pin down.

This paper formally analyzes the role of yearly snowfall in explaining the changes in home valuations near ski resorts in the western United States. Using data on housing values for selected U.S. Census tracts, combined with detailed weather data, passenger arrival data from 10% of all commercial air traffic, and characteristics of nearby ski resorts, I find precise and consistent estimates of days of snowfall and number of available destinations by airport on housing values.

O propósito deste trabalho é investigar as características dos dados sobre aglomerados subnormais, na subprefeitura de São Mateus - município de São Paulo - SP, tendo em vista a realização de análises temporais. Os censos demográficos, por meio dos setores de aglomerados subnormais, são uma importante fonte de dados socioeconômicos e demográficos sobre favelas, coletados periodicamente e disponibilizados pelo IBGE para todos os municípios brasileiros. No entanto, pesquisadores e poder público estão sujeitos às controvérsias metodológicas e questões cartográficas que ainda dificultam o uso dessas informações. No presente estudo, foram identificadas e sistematizadas as características dos aglomerados subnormais. Posteriormente, essas informações foram verificadas quanto à sua ocorrência e significância por meio do estudo de caso, com sobreposição das malhas censitárias dos censos 2000 e 2010, e das bases cadastrais da prefeitura em um sistema de informação geográfica (SIG). Aprimoramentos foram observados nos processos e resultados do censo de 2010, comparado com o censo de 2000. Entretanto, os dados sobre aglomerados subnormais ainda apresentam características que dificultam a realização de análises temporais, destacando-se os seguintes resultados: a) 96,5% dos setores subnormais do estudo de caso, identificados como tal somente em 2010 são constituídos por favelas implantadas até 1999; b) 42,5% dos setores subnormais de 2010 referem-se à novas identificações de favelas em relação a 2000; c) 55% dos setores subnormais identificados em 2010 são resultantes de subdivisão ou agregação dos setores do censo 2000; d) em 26% dos setores subnormais em 2010 há conjuntos habitacionais ou residências não consideradas favelas pela prefeitura; e) três setores subnormais em 2010 não possuem em sua área, favelas cadastradas pela PMSP e quatro favelas cadastradas na PMSP não foram demarcadas como setores subnormais no censo 2010. As contradições nos dados censitários entre 2000 e 2010 e destes em relação às favelas da prefeitura tornam as análises temporais pouco precisas. O fato de que os dados estão agregados em setores que foram muito modificados entre um censo e outro agrava esta situação, na medida em que limita a comparação dos dados entre os períodos. / The purpose of this research is to analyze the data on subnormal agglomerates (special enumeration districts to identify the most common kind of slum in Brazil, the favelas), provided by the Brazilian Statistics Office, through the case study area, São Mateus borough, located in Sao Paulo city, with regard to achieving temporal analysis. The population census, through the subnormal agglomerates enumeration districts, are an important source of socioeconomic and demographic data on favelas, collected periodically and available to all Brazilian municipalities. However, researchers and public authorities have been subject to methodological controversies and cartographic issues that still complicate the use of this information. This research identifies and systematizes the characteristics relating to subnormal agglomerates. In the sequence, this information is verified according to its occurrence and significance through the case study area, by overlaying the vector census zoning 2000-2010 and the cadastral databases from Sao Paulo city hall, in geographic information system (GIS). Improvements in the processes and results of 2010 census were observed, compared to the 2000 census. However, the subnormal agglomerates data still present characteristics that complicates the accomplishment of temporal analysis. The highlighted results are: a) 96.5% of the subnormal enumeration districts in the case study, identified only in 2010 are favelas implemented until 1999; b) 42.5% of subnormal enumeration districts in 2010 were new favelas identifications; c) 55% of subnormal enumeration districts identified in 2010 are the result of subdivision or aggregation of the 2000 census enumeration districts; d) in 26% of subnormal enumeration districts in 2010 there are social housing buildings or houses not considered favelas by the municipal cadastre; e) three subnormal enumeration districts in 2010 have no correspondence with favelas registered by the municipality and four favelas registered by the municipality were not delineated as subnormal agglomerates in the 2010 census. The contradictions in census data between 2000 and 2010, and the differences found in comparison to the favela municipal database become the temporal analysis less accurate. This imprecision tends to expand due the deep modifications on the enumeration districts, which limit the data comparison.

This dissertation investigates transportation subsidies as sources of urban sprawl. Apart from tolls, motorists do not pay highway user-fees, but they do pay gasoline taxes. Gasoline tax revenues are insufficient to cover the U.S. highway costs. Government, therefore, uses general tax revenues to cover highway expenditures. Since users do not pay the full cost of their travel, they have an incentive to travel longer commuting distances. Highway subsidies are, therefore, a potential contributor to urban sprawl. A similar argument applies to public transit. To capture the effects of subsidized automobile and public transit travel, we ex-tend the standard urban spatial single-mode model (Brueckner, 1987) to incorporate public subsidies for both one and two modes. Comparative static analysis of both models produces empirically testable hypotheses. Our most important theoretical result is that transit subsidies are inversely related to urban sprawl while auto subsidies are directly related to urban sprawl. The empirical analysis focuses on tests of the two-mode model. For consistency with the monocentric assumption of our models, our sample consists of urbanized areas located within a single county and having only one central city. Spatial size of the urbanized area is the dependent variable. Following our theory, explanatory variables comprise the transit subsidy, the highway subsidy, number of households, agricultural land rent, mean household income, and fixed and variable costs for transit and auto. We find that the spatial size of the urbanized area shrinks with an increase in the transit subsidy. The effect of highway subsidies, however, is ambiguous. We apply both ordinary least squares and two-stage least square regression analyses, and the results are qualitatively the same for both methods of estimation.

BACKGROUND: During the 20th century the Czech Republic went through profound changes in female employment, gender roles, population and family policies, and public childcare. The educational structure of the female population changed tremendously. At the same time, completed cohort fertility fluctuated between 1.8 and 2.2 children per woman. OBJECTIVE: This article analyses the changes in the level of completed cohort fertility by education, during educational expansion in the Czech population under the economic, cultural, and institutional background of the state socialist regime, and after its breakdown. METHODS: The changes in the level of completed cohort fertility by education are analysed by means of decomposition, complemented by the analysis of parity composition. RESULTS: uring the 20th century, education-specific completed cohort fertility increased, rather than declined. Fertility levels converged upwards, contributing to high uniformity within educational categories. The overall changes in fertility levels were driven by changes in the educational structure. These trends resulted in the dominance of the twochild family, while large families were disappearing and childlessness dropped to the biological minimum. CONCLUSIONS: An egalitarian economic system with traditional family-friendly policies, in combination with a family-unfriendly labour market, developed into a male breadwinner model of low gender equity. Future family policies should focus on the reconciliation of work and family. CONTRIBUTION: he study contributes to the discussion on links between education and fertility, adding a new picture to the mosaic of country-level analyses. The Czech Republic is an example of a country with high educational homogeneity of fertility behaviour where the education-specific levels of fertility converged upwards.

abstract: Over 2 billion people are using online social network services, such as Facebook, Twitter, Google+, LinkedIn, and Pinterest. Users update their status, post their photos, share their information, and chat with others in these social network sites every day; however, not everyone shares the same amount of information. This thesis explores methods of linking publicly available data sources as a means of extrapolating missing information of Facebook. An application named "Visual Friends Income Map" has been created on Facebook to collect social network data and explore geodemographic properties to link publicly available data, such as the US census data. Multiple predictors are implemented to link data sets and extrapolate missing information from Facebook with accurate predictions. The location based predictor matches Facebook users' locations with census data at the city level for income and demographic predictions. Age and relationship based predictors are created to improve the accuracy of the proposed location based predictor utilizing social network link information. In the case where a user does not share any location information on their Facebook profile, a kernel density estimation location predictor is created. This predictor utilizes publicly available telephone record information of all people with the same surname of this user in the US to create a likelihood distribution of the user's location. This is combined with the user's IP level information in order to narrow the probability estimation down to a local regional constraint. / Dissertation/Thesis / M.S. Computer Science 2012

O propósito deste trabalho é investigar as características dos dados sobre aglomerados subnormais, na subprefeitura de São Mateus - município de São Paulo - SP, tendo em vista a realização de análises temporais. Os censos demográficos, por meio dos setores de aglomerados subnormais, são uma importante fonte de dados socioeconômicos e demográficos sobre favelas, coletados periodicamente e disponibilizados pelo IBGE para todos os municípios brasileiros. No entanto, pesquisadores e poder público estão sujeitos às controvérsias metodológicas e questões cartográficas que ainda dificultam o uso dessas informações. No presente estudo, foram identificadas e sistematizadas as características dos aglomerados subnormais. Posteriormente, essas informações foram verificadas quanto à sua ocorrência e significância por meio do estudo de caso, com sobreposição das malhas censitárias dos censos 2000 e 2010, e das bases cadastrais da prefeitura em um sistema de informação geográfica (SIG). Aprimoramentos foram observados nos processos e resultados do censo de 2010, comparado com o censo de 2000. Entretanto, os dados sobre aglomerados subnormais ainda apresentam características que dificultam a realização de análises temporais, destacando-se os seguintes resultados: a) 96,5% dos setores subnormais do estudo de caso, identificados como tal somente em 2010 são constituídos por favelas implantadas até 1999; b) 42,5% dos setores subnormais de 2010 referem-se à novas identificações de favelas em relação a 2000; c) 55% dos setores subnormais identificados em 2010 são resultantes de subdivisão ou agregação dos setores do censo 2000; d) em 26% dos setores subnormais em 2010 há conjuntos habitacionais ou residências não consideradas favelas pela prefeitura; e) três setores subnormais em 2010 não possuem em sua área, favelas cadastradas pela PMSP e quatro favelas cadastradas na PMSP não foram demarcadas como setores subnormais no censo 2010. As contradições nos dados censitários entre 2000 e 2010 e destes em relação às favelas da prefeitura tornam as análises temporais pouco precisas. O fato de que os dados estão agregados em setores que foram muito modificados entre um censo e outro agrava esta situação, na medida em que limita a comparação dos dados entre os períodos. / The purpose of this research is to analyze the data on subnormal agglomerates (special enumeration districts to identify the most common kind of slum in Brazil, the favelas), provided by the Brazilian Statistics Office, through the case study area, São Mateus borough, located in Sao Paulo city, with regard to achieving temporal analysis. The population census, through the subnormal agglomerates enumeration districts, are an important source of socioeconomic and demographic data on favelas, collected periodically and available to all Brazilian municipalities. However, researchers and public authorities have been subject to methodological controversies and cartographic issues that still complicate the use of this information. This research identifies and systematizes the characteristics relating to subnormal agglomerates. In the sequence, this information is verified according to its occurrence and significance through the case study area, by overlaying the vector census zoning 2000-2010 and the cadastral databases from Sao Paulo city hall, in geographic information system (GIS). Improvements in the processes and results of 2010 census were observed, compared to the 2000 census. However, the subnormal agglomerates data still present characteristics that complicates the accomplishment of temporal analysis. The highlighted results are: a) 96.5% of the subnormal enumeration districts in the case study, identified only in 2010 are favelas implemented until 1999; b) 42.5% of subnormal enumeration districts in 2010 were new favelas identifications; c) 55% of subnormal enumeration districts identified in 2010 are the result of subdivision or aggregation of the 2000 census enumeration districts; d) in 26% of subnormal enumeration districts in 2010 there are social housing buildings or houses not considered favelas by the municipal cadastre; e) three subnormal enumeration districts in 2010 have no correspondence with favelas registered by the municipality and four favelas registered by the municipality were not delineated as subnormal agglomerates in the 2010 census. The contradictions in census data between 2000 and 2010, and the differences found in comparison to the favela municipal database become the temporal analysis less accurate. This imprecision tends to expand due the deep modifications on the enumeration districts, which limit the data comparison.