In the last decade, the Resource Description Framework (RDF) has become the de-facto standard for publishing semantic data on the Web. This steady adoption has led to a significant increase in the number and volume of available RDF datasets, exceeding the capabilities of traditional RDF stores. This scenario has introduced severe big semantic data challenges when it comes to managing and querying RDF data at Web scale. Despite the existence of various off-the-shelf Big Data platforms, processing RDF in a distributed environment remains a significant challenge. In this position paper, based on an indepth analysis of the state of the art, we propose to manage large RDF datasets in Flink, a well-known scalable distributed Big Data processing framework. Our approach, which we refer to as FLINKer extends the native graph abstraction of Flink, called Gelly, with RDF graph and SPARQL query processing capabilities.

‘Accounting has come to occupy an ever more significant position in the functioning of modern industrial societies’ (Burchell et al 1980: 5). Almost 40 years have elapsed since this comment was made and during that time the UK accounting profession has secured a fundamental presence in the neoliberal global economy, wielding great power. However, the scale and scope of accounting’s success has been gender asymmetrical; women accountants have not achieved commensurate success with men either in terms of ICAEW membership or Big 4 partner numbers. This thesis charts the role and performance of women in the UK accounting profession from 1870 to 2013, critically assessing the reasons why women fail to do as well as men.

As it becomes more common for individuals to work in many different jobs throughout their lives, career adaptability becomes more important to understanding how individuals deal with this changing environment. This study examined the history and background of career adaptability and personality, as well as current research in the field. A total of 196 students from a large Midwestern university completed the Career Futures Inventory – Revised and a Big Five measure from the International Personality Item Pool to examine potential relationships between individual personality traits and career adaptability. Pearson correlations, linear and hierarchical regression analyses, and analysis of variance were used to analyze possible relationships. The results of the study indicated that 39.7% of career adaptability was accounted for by the Big Five personality traits. All five personality traits and career adaptability were moderately correlated and neuroticism, conscientiousness, and extraversion predicted participants’ overall career adaptability. Hierarchical regression analyses showed that career adaptability and career agency both predicted major satisfaction above and beyond personality. Key words: career adaptability, Big Five personality, major satisfaction

Tese (doutorado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-graduação em Engenharia e Gestão do Conhecimento, Florianópolis, 2015 / Made available in DSpace on 2016-02-09T03:05:12Z (GMT). No. of bitstreams: 1 337380.pdf: 2007643 bytes, checksum: e50278c850a3956933c9f017a119ccb2 (MD5) Previous issue date: 2015 / A curadoria de informações é uma nova área de estudo cuja importância é cada vez maior devido às consequências da combinação de dois fenômenos recentes na internet: a Avalancha Informativa e os Grandes Dados (Big Data). Ao filtrar, selecionar, agregar valor e disseminar recomendações, a curadoria contribui para aumentar a estruturação e difusão de informações e intensificar o fluxo de conteúdos necessários à produção de conhecimento. Por se tratar de uma área ainda pouco estudada foi necessário definir termos como dado, notícia, informação, conhecimento, bem como processos de curadoria de informações, fluxo de informações e espaços informativos. A curadoria de informações foi tomada como tema central do trabalho por sua função na disseminação de informações voltadas para a produção de conhecimento em comunidades de usuários. Os procedimentos metodológicos adotados no desenvolvimento do trabalho foram orientados pela Teoria Fundamentada em Dados (Grounded Theory) e pela obra de John Creswell sobre organização de pesquisas acadêmicas. A análise do processo de curadoria de informações partiu da coleta de dados obtidos durante seis meses de monitoramento do blog Content Curation World. Estes dados foram posteriormente interpretados com base nas teorias de Max Boisot, sobre fluxos informativos. A análise de 17.907 reações dos receptores às 167 postagens com recomendações do curador mostrou a relevância do papel do fluxo de dados na alimentação da produção de conhecimento numa rede social frequentada por 4.120 usuários aglutinados em torno da preocupação com a curadoria de informações.<br> / Abstract : Content curation is a brand new area of academic research whose growing relevance is the result of the combination of two interconnected processes: the information overload and the Big Data. By filtering, selecting, aggregating value and disseminating recommendations, the content curation process increases the structuring and diffusion of information and strengthens the flow of contents aiming the production of social relevant knowledge. The English academic literature uses the expression content curation while in Portuguese the equivalent is information curation. Thus we use the expression content curation in this abstract. Due to the fact that this is an area still scarcely researched, especially in Brazil, it?s necessary to set up specific definitions for terms such as data, news, information, knowledge and processes like curation, information flow, news flow and information spaces. Information curation is taken as a key reference due to it?s importance in the diffusion of information (recommendations) related to the knowledge production process in communities of users. The methodological procedures used in this thesis are based on the Grounded Theory and on the works of John Creswell about academic researches. The study of content curation process was based on a six month monitoring of the blog Content Curation World. The data collected was analyzed using the Max Boisot theories of information flows as a framework. The interpretation of 17.907 reactions from the receivers of the 167 recommendations posted by the curator revealed the importance of the role of data flux in the feeding of the knowledge production process inside a social network or information space defined by the blog?s 4.120 users whose common interest is the content curation activity.

Doctor of Philosophy / Department of Human Ecology-Personal Financial Planning / Martin Seay / Little is known about the relationships between personality characteristics and financial satisfaction. This dissertation examines three questions. First, what are the relationships between personality characteristics and financial satisfaction at the American state level? Second, what are the relationships between personality characteristics and financial satisfaction at the individual level? Third, what are the relationships between personality characteristics and financial satisfaction among financially strained households? Essay one utilizes data aggregated at the state level from two nationally representative datasets in order to examine the relationships between Big Five personality traits (openness to experience, conscientiousness, extraversion, agreeableness, and neuroticism) and financial satisfaction at the American state level. Results from bivariate analyses and a two-block hierarchical regression model indicate that conscientiousness is negatively associated with financial satisfaction and extraversion is positively associated with financial satisfaction at the American state level. Essay two utilizes data from the 2012 wave of the Health and Retirement Study (HRS) to examine relationships between personality characteristics (Big Five personality traits and positive/negative affect) and financial satisfaction at the individual level. Results from a three-block ordinal logistic regression model indicate that personality characteristics are important predictors of financial satisfaction. Extraversion is positively associated with financial satisfaction while neuroticism and agreeableness are negatively associated with financial satisfaction when Big Five personality traits were the only personality characteristics incorporated into the model. However, when positive affect and negative affect were added to the model, only agreeableness remained negatively associated with financial satisfaction, while both positive and negative affect were positively and negatively associated with financial satisfaction, respectively. Essay three utilizes data from the 2012 wave of the HRS to examine relationships between personality characteristics (Big Five personality traits and positive/negative affect) and financial satisfaction among individuals in households exhibiting both objective and subjective indicators of financial strain. Results from a series of ordinal logistic regressions indicate that individual level associations between personality characteristics and financial satisfaction remained largely the same among households exhibiting financial strain, though evidence suggests that interventions aimed at influencing positive affect may be an effective means to enhancing well-being among financially strained populations. Overall, personality characteristics were found to be important predictors of financial satisfaction which have been largely overlooked in prior models of financial satisfaction. Going forward, a better understanding of the relationships between personality characteristics and subjective measures of economic well-being will be needed in order to determine how consumer well-being can be most effectively promoted.

Made available in DSpace on 2018-08-01T21:59:50Z (GMT). No. of bitstreams: 1 tese_11448_Tese final Andre Luiz Alves Lima - PPGFis.pdf: 4483830 bytes, checksum: 73c10ae115a7b4575ece1730f9f6e7de (MD5) Previous issue date: 2017-09-20 / Esta tese é uma investigação de modelos cosmológicos duais sob uma inversão do fator de escala no tempo conforme, na gravitação de Einstein. A transformação de Dualidade do Fator de Escala no tempo conforme (DFE) atua como um mapa entre altas e baixas energias, e entre evoluções aceleradas e desaceleradas do universo. Utilizada enquanto um princípio de simetria, a DFE seleciona modelos com duas fases de aceleração, simétricos por reflexão ao redor do ponto em que aceleração é nula. Encontramos uma classe desses modelos, correspondente a um gás de Chaplygin modificado, que pode ser usada como ferramenta de discussão em diversos regimes fenomenológicos, e.g. uma fase inflacionária do tipo hilltop, ou um universo de quintessência. A DFE, na gravitação de Einstein, é análoga a uma dualidade bem conhecida da gravitação dilatônica, em que a inversão do fator de escala (no quadro de cordas) junto com uma transformação apropriada do dilaton fornecem uma simetria das equações gravidilatônicas para uma classe muito restrita de potenciais. Apesar de ser uma simetria das equações de Friedmann no quadro de Einstein, as soluções duais da DFE, para qualquer potencial, podem ser interpretadas no quadro de cordas, onde fornecem transformações relacionando grandes e pequenos valores do fator de escala. A dualidade gravidilatônica da origem ao chamado Cenário Prée-Big-Bang na cosmologia de cordas. De maneira similar, um universo dual pela DFE pode ser interpretado como estando antes da singularidade, na gravitação de Einstein. Concentramo-nos em analisar as cosmologias duais em que a fase pré-big-bang é um universo em expansão eterna (ao contrário dos modelos usuais de ricochete), e sua fase final, acelerada, faz o papel da inflação antes do big-bang do universo seguinte. Essa idéia é reminiscente da idéia de uma `Cosmologia Conforme Cíclica'. A transição através da singularidade requer uma identificação conforme; abordamos esse problema utilizando a correspondência dS/CFT e o grupo de renormalização holográfico.

"NoSQL solution" is today a term that represents a wide spectrum of ways of storing and requesting data. From graph-oriented databases to key-value databases, each solution has been developed to be the best choice in a specific case and for given parameters. As NoSQL solutions are new, there is no guide explaining which solution is best depending on someone's use case. In the first part of this document, we give an overview of each type of solution, explaining when and why a certain type of solution would be a good or a poor choice for a given use case. Once a company has chosen the technology that seems to fit well its need, it faces another problem : how to deploy this new type of data store. Directly deploying a production store would certainly result in poor performances, because some pieces of knowledge are absolutely necessary to implement an efficient NoSQL store. However, there is no "best practices" guide to get this knowledge. This is the reason why building a prototype, with fewer resources, can improve everyone's knowledge. Then, with the experience retrieved from this first experience, engineers and technicians can deploy a store that will be much more efficient than the store they would have deployed without the prototype experience. For this reason, we decided to implement a MongoDB prototype store. Building this prototype, we have tested several configurations that resulted in different levels of performance. In the second part of this document, we explain the main result we got from our experiments. These results could be useful for other companies that are willing to use MongoDB, but they mostly show why a specific knowledge is essential to deploy a good NoSQL store.

Magíster en Gestión para la Globalización / El objetivo de este trabajo es la implementación de la metodología People Analytics en el mercado chileno, a través de una consultoría realizada en la empresa Antofagasta Minerals S.A. (en adelante AMSA). Este estudio le permite a AMSA obtener información cuantitativa sobre un proceso específico de su gestión de personas. La metodología bajo la cual se realizó este trabajo fue, en primera instancia, recopilación de información teórica y obtención de conocimiento sobre los procesos de la Empresa. Una vez definido que el foco del estudio sería la relación existente entre los resultados de la evaluación de desempeño y los resultados de la encuesta de compromiso aplicada en el año 2014 en AMSA, se realizaron varias reuniones para comprender los procesos de gestión de desempeño. Adicionalmente, se extrajo información del Sistema de Recursos Humanos que tiene implementado AMSA y se realizaron todos los análisis necesarios para la obtención de los resultados. Todo esto con el objeto de dar solución y recomendaciones al problema actual de la Compañía, que es cómo mantener los altos niveles de compromiso de los empleados, luego de haber disminuido los recursos tanto de personal como económicos, dada la difícil situación de la minería en Chile. Seguidamente de desarrollar todos los análisis, se obtuvo como resultado que no existía una correlación clara y objetiva entre los objetos de estudio, que fueron los resultados de compromiso versus los resultados de la evaluación de desempeño. Lo cual se puede deber a varias razones que se dan a conocer en el detalle del trabajo. De igual forma se utilizó la información ya analizada para buscar las mejores medidas a implementar para dar solución al problema. Las principales conclusiones de este trabajo de consultoría una vez realizados los análisis, es que se cumplieron los objeticos planteados al inicio del trabajo, obteniendo recomendaciones que permitirán la obtención de beneficios, tales como aumento de productividad y disminución de costos relacionados con el proceso de gestión de personas. Estas recomendaciones permitirán replicar el estudio nuevamente y acercarse al modelo de empresa de alto desempeño que busca AMSA. El paso a seguir es, una vez implementadas las recomendaciones, es internalizar el concepto de People Analytics sobre manejo de la información al interior de la Organización y tomar un nuevo foco para aplicar este método. Así también sería de gran aporte que AMSA cuente con un colaborador en el Área de Recursos Humanos que esté a cargo del manejo y análisis de la información.

L’augmentation de la quantité de données à visualiser due au phénomène du Big Data entraîne de nouveaux défis pour le domaine de la visualisation d’information. D’une part, la quantité d’information à représenter dépasse l’espace disponible à l’écran, entraînant de l’occlusion. D’autre part, ces données ne peuvent pas être stockées et traitées sur une machine conventionnelle. Un système de visualisation de données massives doit permettre la scalabilité de perception et de performances. Dans cette thèse, nous proposons une solution à ces deux problèmes au travers de l’abstraction multi-échelle des données. Plusieurs niveaux de détail sont précalculés sur une infrastructure Big Data pour permettre de visualiser de grands jeux de données jusqu’à plusieurs milliards de points. Pour cela, nous proposons deux approches pour implémenter l’algorithme de canopy clustering sur une plateforme de calcul distribué. Nous présentons une application de notre méthode à des données géolocalisées représentées sous forme de carte de chaleur, ainsi qu’à des grands graphes. Ces deux applications sont réalisées à l’aide de la bibliothèque de visualisation dynamique Fatum, également présentée dans cette thèse. / With the advent of the Big Data era come new challenges for Information Visualization. First, the amount of data to be visualized exceeds the available screen space. Second, the data cannot be stored and processed on a conventional computer. To alleviate both of these problems, a Big Data visualization system must provide perceptual and performance scalability. In this thesis, we propose to use multi-scale abstractions as a solution to both of these issues. Several levels of detail can be precomputed using a Big Data Infrastructure in order to visualize big datasets up to several billion points. For that, we propose two approaches to implementing the canopy clustering algorithm for a distributed computation cluster. We present applications of our method to geolocalized data visualized through a heatmap, and big graphs. Both of these applications use the dynamic visualization library, which is also presented in this thesis

The four major ecological variables, soils, climate, vegetation and fauna, were studied from May 1966 to November 1967 and again for a short period in 1969 on important California bighorn sheep {Ovis canadensis califomiana Douglas) ranges in the Ashnola region. Emphasis in this investigation was placed on completing the basic extensive resource inventory as well as on initiating experimental range rehabilitation practices for future management of critical forage resources on the winter ranges. The soils inventory was based primarily on the survey recently completed for the Canada Department of Agriculture (Green, in print) for the Princeton map sheet. Extrapolation for the eastern half of the study area was accomplished with the use of air photos and some additional ground surveys. The climatic factors measured were: air and soil temperature, precipitation, snow depth and evaporation. This was done by establishing two summer climatic transects and one snow depth transect. These transects were altitudinally spaced along available access roads. The vegetation analysis was conducted with the use of site specific species lists, point quadrat and line transects and air photos. Both the habitat and soil type maps were constructed from available air photo coverage and ground surveys. Ungulate distributions were mapped from ground observations, aerial helicopter surveys and previous reports. Range rejuvenation experiments, using large exclosures, fertilization and reseeding, were conducted concurrently with the inventory. Five sites were chosen for these rehabilitation trials. Soils in the study area vary from Brown and Dark Brown to Alpine Dystric Brunisols. The mid-grasslands occur predominantly on Chernozem!c, the Rego Dark Gray to Orthic Black soils. Related in large measure to the physiography of the region, large areas have nonproductive soils, talus slopes and sheer rocks; vegetative production is extremely limited on such sites. Altitude and exposure greatly affect the temperature and precipitation regime within the area. At low altitudes the moisture supply limits productivity. Summer evaporation is very high on exposed low grassland slopes. With rising elevation the precipitation generally increases, and evaporation and mean temperatures decrease. Exposure greatly affects the overall climatic regime. This is reflected in the variable vegetative cover and productivity. Climatic change, variable between years, caused considerable fluctuation in forage production between years. Vegetative zonation is clearly recognizable in the area. The zones and thus habitat types are altitudinally delimited. Fire, logging and ungulate grazing have caused much disturbance. Reseeding was not very successful, especially on stable plant communities on Juniper and South Slope. Fertilization had considerable effect on forage production on all sites. Standing crop increases, as measured by a single annual clipping during late July, were sustained for at least three years on the Poa sp. and Agropyron spicatum sites. Excluding ungulates from the five fenced sites resulted in changes in species composition, plant vigor and increased forage production. Some progressive trends towards climax were recognized on at least two sites in 1969. Climatic factors, primarily temperature and moisture supply, grazing history and soils, all contributed to local and annual variability in forage yields. Periodic protection of important grasslands from use and fertilization of some slopes show promise as management tools. / Land and Food Systems, Faculty of / Graduate