[pt] Dados estatísticos são considerados uma das principais fontes de informação e são essenciais em muitos campos, uma vez que podem funcionar como indicadores sociais e econômicos. Um conjunto de dados estatísticos compreende um conjunto de observações feitas em determinados pontos de um espaço lógico e é muitas vezes organizado como o que se chama de cubo de dados. A definição correta dos cubos de dados, especialmente das suas dimensões, ajuda a processar as observações e, mais importante, ajuda a combinar as observações de diferentes cubos de dados. Neste contexto, os princípios de Linked Data podem ser proveitosamente aplicados à definição de cubos de dados, no sentido de que os princípios oferecem uma estratégia para proporcionar a semântica ausentes das suas dimensões, incluindo os seus valores. Esta dissertação descreve inicialmente uma arquitetura de mediação para ajudar a descrever e consumir dados estatísticos, expostos como triplas RDF, mas armazenados em bancos de dados relacionais. Uma das características desta mediação é o Catálogo de Descrições de Cubos de Dados Interligados, que vai ser descrito em detalhes na dissertação. Este catálogo contém uma descrição padronizada em RDF para cada cubo de dados, que está realmente armazenado em cada banco de dados (relacional). Portanto, a principal discussão nesta dissertação é sobre a forma de representar em RDF cubos representando dados estatísticos e armazenados em bancos de dados relacionais, ou seja, como mapear os conceitos de banco de dados para RDF de uma forma em que seja fácil consultar, analisar e reutilizar dados estatísticos no formato RDF. / [en] Statistical Data are considered one of the major sources of information and are essential in many fields as they can work as social and economic indicators. A statistical data set comprises a colletion of observations made at some points of a logical space and is often organized as what is called a data cube. The proper definition of the data cubes, especially of theis dimensions, helps processing the observations and, more importantly, helps combining observations from different data cubes. In this contexto, the Linked Data principles can be profitably applied to the definition of data cubes, in the sense that the principles offer a strategy to provide the missing semantics of the dimensions, including their values. This dissertion first describes a mediation architecture to help describing and consuming statistical data, exposed as RDFtriples, but stored in relational databases. One of the features of this architesture is the Catalogue of Linked Data Cube Descriptions, which is described in detail in the dissertation. This catalogue has a standardized description in RDF of each data cube actually stored in statistical (relational) databases. Therefore, the main discussion in this dissertation is how to represent the data cubes in RDF, i.e., how to map the database concepts to RDF in a way that makes it easy to query, analyze and reuse statistical data in the RDF format.

[pt] Um banco de dados estatístico consiste de um conjunto de observações feitas em pontos de um espaço lógico, e, muitas vezes, são organizados como cubos de dados. A definição adequada de cubos de dados, em especial de suas dimensões, ajuda a processar as suas observações e, mais importante, ajuda a combinar observações de cubos de dados diferentes. Neste contexto, os princípios de dados interligados podem ser proveitosamente aplicados à definição de cubos de dados, oferecendo uma estratégia para fornecer a semântica das dimensões, incluindo seus valores. Este trabalho introduz uma arquitetura de mediação para auxiliar no consumo de cubos de dados, expostos como triplas RDF e armazenados em bancos de dados relacionais. Os cubos de dados são descritos em um catálogo usando vocabulários padronizados e são acessados por métodos HTTP usando os princípios de REST. Portanto, este trabalho busca tirar proveito tanto dos princípios de dados interligados quanto dos princípios de REST para descrever e consumir os cubos de dados interligados de forma simples e eficiente. / [en] A statistical data set comprises a collection of observations made at some points across a logical space and is often organized as what is called a data cube. The proper definition of the data cubes, especially of their dimensions, helps to process the observations and, more importantly, helps to combine observations from different data cubes. In this context, the Linked Data Principles can be profitably applied to the definition of data cubes, in the sense that the principles offer a strategy to provide the missing semantics of the dimensions, including their values. This work introduces a mediation architecture to help consume linked data cubes, exposed as RDF triples, but stored in relational databases. The data cubes are described in a catalogue using standardized vocabularies and are accessed by HTTP methods using REST principles. Therefore, this work aims at taking advantage of both Linked Data and REST principles in order to describe and consume linked data cubes in a simple but efficient way.

Neste estudo, foram analisadas relações existentes entre liderança, motivação, clima organizacional, trabalho em equipe e o comprometimento organizacional e ocupacional. O estudo exploratório foi realizado em três partes, na primeira procurou-se identificar os fatores de desempenho mais importantes numa relação maior resultantes da pesquisa bibliográfica e na segunda buscou-se quantificar os quatro fatores de desempenho junto aos comprometimentos organizacional e ocupacional. Na primeira parte foi realizada uma pesquisa exploratória e na segunda parte foram entrevistados 52 servidores do CCTM no Instituto de Pesquisas Energéticas e Nucleares IPEN e 252 servidores do IAE no Centro Técnico Aeroespacial CTA. A pesquisa utilizou 18 indicadores de comprometimento organizacional e 18 indicadores de comprometimento ocupacional, todos extraídos do instrumento de Meyer, Allen e Smith. Além destes, foram utilizadas 7 variáveis demográficas e 71 variáveis de desempenho construídas a partir da revisão teórica realizada. Os resultados obtidos com a pesquisa exploratória da primeira parte identificaram os quatro fatores de desempenho já citados e na segunda parte os resultados obtidos nos dois principais locais comprovaram a hipótese que os locais ou grupos de servidores que apresentam maior grau de comprometimento tendem a um maior grau de desempenho. Na terceira parte do estudo utilizou-se a técnica de modelagem de equações estruturais partindo de um modelo teórico definido com as 12 variáveis de desempenho mais importantes em ambos locais da pesquisa e com o apoio dos softwares estatísticos SPSS e LISREL obteve-se um modelo de relacionamento causal mais fortalecido para explicar as variáveis envolvidas. / In this work relation among leadership, motivation, organizational climate, teamwork, and the organizational and occupational commitment, were studied. The exploratory study was accomplished in three parts. In the first it was identified the more important performance factors in a larger relation resultant of the bibliographical research and in the second, it was undertaken a quantification the 4 performance factors together to the organizational and occupational commitments. In the first part, it was accomplished an exploratory research close to some experienced servants, with emphasis in the management area. In the second part it was interviewed 52 employees of the CCTM\'s at the Energy and Nuclear Research Institute IPEN and 252 employees of the IAE at the Aerospace Technical Center CTA. This research used 18 indicators of the organizational commitment and 18 indicators of the occupational commitment, all extracted from the instrument of Meyer, Allen and Smith. Beyond of these, it was used 7 demographic variables and 71 performance variables built from the theoretical revision. The results obtained with the exploratory research of the first part identified the 4 factors aforementioned performance factors. In the second part the obtained results in the two firsts places proved the hypothesis that the servants locations or groups that show a higher degree of commitment tend to a higher degree of performance. In the third part of this study it was used the Structural Equations Modelling SEM, from one theoretic model defined with the 12 more important variables from performance in both researched locals and with assistance of two statistical softwares SPSS and LISREL it was obtained a model of causal relations more strengthened to explain the relationship among the used variables.

The thesis deals with the possibilities of visualization of multivariate statistical data. Since this is a very broad area the thesis is divided into four sections, two of which are theoretically and two practically oriented. The first section is devoted to theoretical aspects of data visualization. It contains information about the building blocks of graphs, and how the brain processes graphs in various stages of perception. The second section charts the available chart types that can be used to display data. Selected types of graphs for continuous and discontinuous multidimensional data are described in detail. The third section focuses on available software tools for creating graphs. The section describes several programs, with focus on STATISTICA, R and MS Excel. The knowledge gained in previous chapters was sufficient source of information to perform a graphical analysis of multidimensional continuous and discrete data and using advanced analytical methods in the last section. This analysis is performed separately on the data file with continuous variables and on a data file with discontinuous (categorical) variables.

Current conventional weather forecasts are based on high-dimensional numerical models. They are usually only skillful up to a maximum lead time of around 7 days due to the chaotic nature of the climate dynamics and the related exponential growth of model and data initialisation errors. Even the fully detailed medium-range predictions made for instance at the European Centre for Medium-Range Weather Forecasts do not exceed lead times of 14 days, while even longer-range predictions are limited to time-averaged forecast outputs only. Many sectors would profit significantly from accurate forecasts on seasonal time scales without needing the wealth of details a full dynamical model can deliver. In this thesis, we aim to study the potential of a much cheaper data-based statistical approach to provide predictions of comparable or even better skill up to seasonal lead times, using as an examplary forecast target the time until the next occurrence of frost. To this end, we first analyse the properties of the temperature anomaly time series obtained from measured data by subtracting a sinusoidal seasonal cycle, as well as the distribution properties of the first passage times to frost. The possibility of generating additional temperature anomaly data with the same properties by using very simple autoregressive model processes to potentially reduce the statistical fluctuations in our analysis is investigated and ultimately rejected. In a next step, we study the potential for predictability using only conditional first passage time distributions derived from the temperature anomaly time series and confirm a significant dependence of the distributions on the initial conditions. After this preliminary analysis, we issue data-based out-of-sample forecasts for three different prediction targets: The specific date of first frost, the probability of observing frost before summer for forecasts issued in spring, and the full probability distribution of the first passage times to frost. We then study the possibility of improving the forecast quality first by enhancing the stationarity of the temperature anomaly time series and then by adding as an additional input variable the state of the North Atlantic Oscillation on the date the predictions are issued. We are able to obtain significant forecast skill up to seasonal lead times when comparing our results to an unskilled reference forecast. A first comparison between the data-based forecasts and corresponding predictions gathered from a dynamical weather model, necessarily using a lead time of only up to 15 days, shows that our simple statistical schemes are only outperformed (and then only slightly) if further statistical post-processing is applied to the model output. / Aktuelle Wetterprognosen werden mit Hilfe von hochdimensionalen, numerischen Modellen generiert. Durch die dem Klima zugrunde liegende chaotische Dynamik wachsen Modellfehler und Ungenauigkeiten in der Modellinitialisierung exponentiell an, sodass Vorhersagen mit signifikanter Güte üblicherweise nur für eine Vorlaufzeit von maximal sieben Tagen möglich sind. Selbst die detaillierten Prognosen des Europäischen Zentrums für mittelfristige Wettervorhersagen gehen nicht über eine Vorlaufzeit von 14 Tagen hinaus, während noch längerfristigere Vorhersagen auf zeitgemittelte Größen beschränkt sind. Viele Branchen würden signifikant von akkuraten Vorhersagen auf saisonalen Zeitskalen pro-fitieren, ohne das ganze Ausmaß an Details zu benötigen, das von einem vollständigen dynamischen Modell geliefert werden kann. In dieser Dissertation beabsichtigen wir, am Beispiel einer Vorhersage der Zeitdauer bis zum nächsten Eintreten von Frost zu untersuchen, inwieweit deutlich kostengünstigere, datenbasierte statistische Verfahren Prognosen von gleicher oder sogar besserer Güte auf bis zu saisonalen Zeitskalen liefern können. Dazu analysieren wir zunächst die Eigenschaften der Zeitreihe der Temperaturanomalien, die aus den Messdaten durch das Subtrahieren eines sinusförmigen Jahresganges erhalten werden, sowie die Charakteristiken der Wahrscheinlichkeitsverteilungen der Zeitdauer bis zum nächsten Eintreten von Frost. Die Möglichkeit, durch einen einfachen autoregressiven Modellprozess zusätzliche Datenpunkte gleicher statistischer Eigenschaften wie der Temperaturanomalien zu generieren, um die statistischen Fluktuationen in der Analyse zu reduzieren, wird untersucht und letztendlich verworfen. Im nächsten Schritt analysieren wir das Vorhersagepotential, wenn ausschließlich aus den Temperaturanomalien gewonnene bedingte Wahrscheinlichkeitsverteilungen der Wartezeit bis zum nächsten Frost verwendet werden, und können eine signifikante Abhängigkeit der Verteilungen von den Anfangsbedingungen nachweisen. Nach dieser einleitenden Untersuchung erstellen wir datenbasierte Prognosen für drei verschiedene Vorhersagegrößen: Das konkrete Datum, an dem es das nächste Mal Frost geben wird; die Wahrscheinlichkeit, noch vor dem Sommer Frost zu beobachten, wenn die Vorhersagen im Frühjahr ausgegeben werden; und die volle Wahrscheinlichkeitsverteilung der Zeitdauer bis zum nächsten Eintreten von Frost. Anschließend untersuchen wir die Möglichkeit, die Vorhersagegüte weiter zu erhöhen - zunächst durch eine Verbesserung der Stationarität der Temperaturanomalien und dann durch die zusätzliche Berücksichtigung der Nordatlantischen Oszillation als einer zweiten, den Anfangszustand charakterisierenden Variablen im Vorhersageschema. Wir sind in der Lage, im Vergleich mit einem naiven Referenzvorhersageschema eine signifikante Verbesserung der Vorhersagegüte auch auf saisonalen Zeitskalen zu erreichen. Ein erster Vergleich zwischen den datenbasierten Vorhersagen und entsprechenden, aus den dynamischen Wettermodellen gewonnenen Prognosen, der sich notwendigerweise auf eine Vorlaufzeit der Vorhersagen von lediglich 15 Tagen beschränkt, zeigt, dass letztere unsere simplen statistischen Vorhersageschemata nur schlagen (und zwar knapp), wenn der Modelloutput noch einer statistischen Nachbearbeitung unterzogen wird.

This diploma thesis presents a comprehensive overview of the issue of land valuation for expropriation. The work includes a comparison of the frequency of the process of expropriation and the variance amount of compensation for expropriation in the Czech Republic and Austria. They were approached by employees of institutions that deal with the subject of this work. There was a consultation with ŘSD, Ministry for Regional Development, the Department of expropriation office, torts and state supervision in the České Budějovice, and others. The territory of Austria were approached eg. company employees Asfinag. In chapter Results are placed proposals improvement measures that can assist in potential future adjustment problems being solved.

[pt] A produção de indicadores sociais e sua disponibilização na Web é uma importante iniciativa de democratização e transparência que os governos em todo mundo vêm realizando nas últimas duas décadas. No Brasil diversas instituições governamentais ou ligadas ao governo publicam indicadores relevantes para acompanhamento do desempenho do governo nas áreas de saúde, educação, meio ambiente entre outras. O acesso, a consulta e a correlação destes dados demanda grande esforço, principalmente, em um cenário que envolve diferentes organizações. Assim, o desenvolvimento de ferramentas com foco na integração e disponibilização das informações de tais bases, torna-se um esforço relevante. Outro aspecto que se destaca no caso particular do Brasil é a dificuldade em se identificar dados estatísticos dentre outros tipos de dados armazenados no mesmo banco de dados. Esta dissertação propõe um arcabouço de software que cobre a identificação das bases de dados estatísticas no banco de dados de origem e o enriquecimento de seus metadados utilizando ontologias padronizadas pelo W3C, como base para o processo de triplificação. / [en] The production of social indicators and their availability on the Web is an important initiative for the democratization and transparency that governments have been doing in the last two decades. In Brazil, several government or government-linked institutions publish relevant indicators to help assess the government performance in the areas of health, education, environment and others. The access, query and correlation of these data demand substantial effort, especially in a scenario involving different organizations. Thus, the development of tools, with a focus on the integration and availability of information stored in such bases, becomes a significant effort. Another aspect that requires attention, in the case of Brazil, is the difficulty in identifying statistical databases among others type of data that share the same database. This dissertation proposes a software framework which covers the identification of statistical data in the database of origin and the enrichment of their metadata using W3C standardized ontologies, as a basis for the triplification process.

Neste estudo, foram analisadas relações existentes entre liderança, motivação, clima organizacional, trabalho em equipe e o comprometimento organizacional e ocupacional. O estudo exploratório foi realizado em três partes, na primeira procurou-se identificar os fatores de desempenho mais importantes numa relação maior resultantes da pesquisa bibliográfica e na segunda buscou-se quantificar os quatro fatores de desempenho junto aos comprometimentos organizacional e ocupacional. Na primeira parte foi realizada uma pesquisa exploratória e na segunda parte foram entrevistados 52 servidores do CCTM no Instituto de Pesquisas Energéticas e Nucleares IPEN e 252 servidores do IAE no Centro Técnico Aeroespacial CTA. A pesquisa utilizou 18 indicadores de comprometimento organizacional e 18 indicadores de comprometimento ocupacional, todos extraídos do instrumento de Meyer, Allen e Smith. Além destes, foram utilizadas 7 variáveis demográficas e 71 variáveis de desempenho construídas a partir da revisão teórica realizada. Os resultados obtidos com a pesquisa exploratória da primeira parte identificaram os quatro fatores de desempenho já citados e na segunda parte os resultados obtidos nos dois principais locais comprovaram a hipótese que os locais ou grupos de servidores que apresentam maior grau de comprometimento tendem a um maior grau de desempenho. Na terceira parte do estudo utilizou-se a técnica de modelagem de equações estruturais partindo de um modelo teórico definido com as 12 variáveis de desempenho mais importantes em ambos locais da pesquisa e com o apoio dos softwares estatísticos SPSS e LISREL obteve-se um modelo de relacionamento causal mais fortalecido para explicar as variáveis envolvidas. / In this work relation among leadership, motivation, organizational climate, teamwork, and the organizational and occupational commitment, were studied. The exploratory study was accomplished in three parts. In the first it was identified the more important performance factors in a larger relation resultant of the bibliographical research and in the second, it was undertaken a quantification the 4 performance factors together to the organizational and occupational commitments. In the first part, it was accomplished an exploratory research close to some experienced servants, with emphasis in the management area. In the second part it was interviewed 52 employees of the CCTM\'s at the Energy and Nuclear Research Institute IPEN and 252 employees of the IAE at the Aerospace Technical Center CTA. This research used 18 indicators of the organizational commitment and 18 indicators of the occupational commitment, all extracted from the instrument of Meyer, Allen and Smith. Beyond of these, it was used 7 demographic variables and 71 performance variables built from the theoretical revision. The results obtained with the exploratory research of the first part identified the 4 factors aforementioned performance factors. In the second part the obtained results in the two firsts places proved the hypothesis that the servants locations or groups that show a higher degree of commitment tend to a higher degree of performance. In the third part of this study it was used the Structural Equations Modelling SEM, from one theoretic model defined with the 12 more important variables from performance in both researched locals and with assistance of two statistical softwares SPSS and LISREL it was obtained a model of causal relations more strengthened to explain the relationship among the used variables.

On the topic of development of information society in Europe with emphases on activities performed by the European Union. A short remark on origin and development of the concept of information society and general economic impact of using information and communication technologies. It brings together a summary of policies and strategies encouraging the development of information society carried out in between the years 2000-2010. A note on preparation of strategy on information society for 2011-2015. Financing programmes using assets of the budget of the European Union for financial period 2007-2013. European Commission and the Information Society and Media Directorate General provide the administrative process support and the background of the preparation for information society policies. An overview of the European statistical data on information society. A list of the European legislation concerning information society with an aim to support use of information and communication technologies.

Current conventional weather forecasts are based on high-dimensional numerical models. They are usually only skillful up to a maximum lead time of around 7 days due to the chaotic nature of the climate dynamics and the related exponential growth of model and data initialisation errors. Even the fully detailed medium-range predictions made for instance at the European Centre for Medium-Range Weather Forecasts do not exceed lead times of 14 days, while even longer-range predictions are limited to time-averaged forecast outputs only. Many sectors would profit significantly from accurate forecasts on seasonal time scales without needing the wealth of details a full dynamical model can deliver. In this thesis, we aim to study the potential of a much cheaper data-based statistical approach to provide predictions of comparable or even better skill up to seasonal lead times, using as an examplary forecast target the time until the next occurrence of frost. To this end, we first analyse the properties of the temperature anomaly time series obtained from measured data by subtracting a sinusoidal seasonal cycle, as well as the distribution properties of the first passage times to frost. The possibility of generating additional temperature anomaly data with the same properties by using very simple autoregressive model processes to potentially reduce the statistical fluctuations in our analysis is investigated and ultimately rejected. In a next step, we study the potential for predictability using only conditional first passage time distributions derived from the temperature anomaly time series and confirm a significant dependence of the distributions on the initial conditions. After this preliminary analysis, we issue data-based out-of-sample forecasts for three different prediction targets: The specific date of first frost, the probability of observing frost before summer for forecasts issued in spring, and the full probability distribution of the first passage times to frost. We then study the possibility of improving the forecast quality first by enhancing the stationarity of the temperature anomaly time series and then by adding as an additional input variable the state of the North Atlantic Oscillation on the date the predictions are issued. We are able to obtain significant forecast skill up to seasonal lead times when comparing our results to an unskilled reference forecast. A first comparison between the data-based forecasts and corresponding predictions gathered from a dynamical weather model, necessarily using a lead time of only up to 15 days, shows that our simple statistical schemes are only outperformed (and then only slightly) if further statistical post-processing is applied to the model output. / Aktuelle Wetterprognosen werden mit Hilfe von hochdimensionalen, numerischen Modellen generiert. Durch die dem Klima zugrunde liegende chaotische Dynamik wachsen Modellfehler und Ungenauigkeiten in der Modellinitialisierung exponentiell an, sodass Vorhersagen mit signifikanter Güte üblicherweise nur für eine Vorlaufzeit von maximal sieben Tagen möglich sind. Selbst die detaillierten Prognosen des Europäischen Zentrums für mittelfristige Wettervorhersagen gehen nicht über eine Vorlaufzeit von 14 Tagen hinaus, während noch längerfristigere Vorhersagen auf zeitgemittelte Größen beschränkt sind. Viele Branchen würden signifikant von akkuraten Vorhersagen auf saisonalen Zeitskalen pro-fitieren, ohne das ganze Ausmaß an Details zu benötigen, das von einem vollständigen dynamischen Modell geliefert werden kann. In dieser Dissertation beabsichtigen wir, am Beispiel einer Vorhersage der Zeitdauer bis zum nächsten Eintreten von Frost zu untersuchen, inwieweit deutlich kostengünstigere, datenbasierte statistische Verfahren Prognosen von gleicher oder sogar besserer Güte auf bis zu saisonalen Zeitskalen liefern können. Dazu analysieren wir zunächst die Eigenschaften der Zeitreihe der Temperaturanomalien, die aus den Messdaten durch das Subtrahieren eines sinusförmigen Jahresganges erhalten werden, sowie die Charakteristiken der Wahrscheinlichkeitsverteilungen der Zeitdauer bis zum nächsten Eintreten von Frost. Die Möglichkeit, durch einen einfachen autoregressiven Modellprozess zusätzliche Datenpunkte gleicher statistischer Eigenschaften wie der Temperaturanomalien zu generieren, um die statistischen Fluktuationen in der Analyse zu reduzieren, wird untersucht und letztendlich verworfen. Im nächsten Schritt analysieren wir das Vorhersagepotential, wenn ausschließlich aus den Temperaturanomalien gewonnene bedingte Wahrscheinlichkeitsverteilungen der Wartezeit bis zum nächsten Frost verwendet werden, und können eine signifikante Abhängigkeit der Verteilungen von den Anfangsbedingungen nachweisen. Nach dieser einleitenden Untersuchung erstellen wir datenbasierte Prognosen für drei verschiedene Vorhersagegrößen: Das konkrete Datum, an dem es das nächste Mal Frost geben wird; die Wahrscheinlichkeit, noch vor dem Sommer Frost zu beobachten, wenn die Vorhersagen im Frühjahr ausgegeben werden; und die volle Wahrscheinlichkeitsverteilung der Zeitdauer bis zum nächsten Eintreten von Frost. Anschließend untersuchen wir die Möglichkeit, die Vorhersagegüte weiter zu erhöhen - zunächst durch eine Verbesserung der Stationarität der Temperaturanomalien und dann durch die zusätzliche Berücksichtigung der Nordatlantischen Oszillation als einer zweiten, den Anfangszustand charakterisierenden Variablen im Vorhersageschema. Wir sind in der Lage, im Vergleich mit einem naiven Referenzvorhersageschema eine signifikante Verbesserung der Vorhersagegüte auch auf saisonalen Zeitskalen zu erreichen. Ein erster Vergleich zwischen den datenbasierten Vorhersagen und entsprechenden, aus den dynamischen Wettermodellen gewonnenen Prognosen, der sich notwendigerweise auf eine Vorlaufzeit der Vorhersagen von lediglich 15 Tagen beschränkt, zeigt, dass letztere unsere simplen statistischen Vorhersageschemata nur schlagen (und zwar knapp), wenn der Modelloutput noch einer statistischen Nachbearbeitung unterzogen wird.