14 research outputs found

    Multi-Level Visual Tours of Weather Linked Data

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    International audienceThe recent trend of adopting linked-data principles to integrate and publish semantically described open data using W3C standards has led to a large amount of available resources. In particular, meteorological sensor data have been uplifted into public weather-focused RDF graphs, such as WeKG-MF which offers access to a large set of meteorological variables described through spatial and temporal dimensions. Nevertheless, these resources include huge numbers of raw observations that are tedious to explore by lay users. In this article, we aim at providing them with visual exploratory "tours", benefiting from RDF data cubes to present high-level aggregated views together with on-demand fine-grained details through a unified Web interface

    Связанные статистические данные: актуальность и перспективы

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    After a detailed argumentation of the study’s relevance, this article discusses the prospects for introducing the concept of linked open statistics produced within the framework of a single information environment that ensures efficient production, dissemination, and reuse of statistical and administrative data. The implementation of this qualitatively new concept based on technological innovations and aimed to meet rapidly growing user demands is a key task of digital transformation, defined by the Government of the Russian Federation in the field of official statistics. The major part of open data concerns statistics such as demographic, economic and social indicators. Describing and presenting them in the form of linked open statistics sets an important background for accelerating socio-economic development by introducing new socially significant state, municipal, non-commercial and commercial services/products.Linked Open Statistical Data (LOSD) allows performing analysis based on a coordinated, integrated information environment as an alternative to using disparate and often controversial data sets. National statistical institutes and government bodies in many countries, together with international organizations, have already chosen the paradigm of linked open statistics. The authors discuss the advantages of this approach, as well as its practical application in international projects.The article presents the examples and best practices of linked open statistics in a number of publications and strategic documents within the European Statistical System. It also shows the constraints of the linked open statistics development due to the lack of accessible ontologies and standards - the extensions necessary to meet the requirements for classification and management of various concepts in statistics domain. The analysis of projects and initiatives carried out in the article reflects the possibilities and prospects of solving this problem in the field of state statistics. The authors formulate a set of recommendations based both on the analysis of international practice and on the results of their own development experience within the research project «Center of Semantic Integration».В данной статье после развернутой аргументации актуальности проведенного исследования рассмотрены перспективы внедрения концепции связанных статистических данных, формируемых в рамках единого информационного пространства, обеспечивающего эффективное производство, распространение и повторное использование статистических и административных данных. Реализация этой качественно новой концепции на основе технологических новаций, предпринимаемая в целях более полного удовлетворения быстро возрастающих потребностей пользователей - ключевая задача цифровой трансформации, определенная Правительством Российской Федерации в области официальной статистики. Большая часть открытых данных связана со статистикой: демографическими, экономическими и социальными показателями. Их описание и представление в виде связанных данных могло бы стать важной основой для ускорения социально-экономического развития страны путем создания новых общественно значимых государственных, муниципальных, некоммерческих и коммерческих услуг/продуктов.В статистике связанные открытые данные (Linked Open Statistical Data, LOSD) позволяют выполнять анализ на основе скоординированной, интегрированной информационной базы как альтернативы использованию разрозненных и часто противоречивых наборов данных. Национальные статистические службы и государственные органы целого ряда стран, а также международные организации уже перешли на парадигму связанных данных. Авторы статьи рассматривают преимущества этого подхода, а также практику его применения в международных проектах.Приведены примеры и лучший опыт создания связанных открытых статистических данных в публикациях и стратегических документах в рамках Европейской статистической системы. Показано, что развитие связанных статистических данных сдерживается отсутствием доступных онтологий и стандартов - расширений, необходимых для обеспечения требований к классификации различных концептов в статистике и управлению ими. Проведенный в статье анализ проектов и инициатив отражает возможности и перспективы решения данной проблемы в сфере государственной статистики. Сформулированные авторами рекомендации основаны как на анализе международной практики, так и на результатах собственного опыта разработок в рамках научно-исследовательского проекта «Центр семантической интеграции»

    Using Semantic Web technologies in the development of data warehouses: A systematic mapping

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    The exploration and use of Semantic Web technologies have attracted considerable attention from researchers examining data warehouse (DW) development. However, the impact of this research and the maturity level of its results are still unclear. The objective of this study is to examine recently published research articles that take into account the use of Semantic Web technologies in the DW arena with the intention of summarizing their results, classifying their contributions to the field according to publication type, evaluating the maturity level of the results, and identifying future research challenges. Three main conclusions were derived from this study: (a) there is a major technological gap that inhibits the wide adoption of Semantic Web technologies in the business domain;(b) there is limited evidence that the results of the analyzed studies are applicable and transferable to industrial use; and (c) interest in researching the relationship between DWs and Semantic Web has decreased because new paradigms, such as linked open data, have attracted the interest of researchers.This study was supported by the Universidad de La Frontera, Chile, PROY. DI15-0020. Universidad de la Frontera, Chile, Grant Numbers: DI15-0020 and DI17-0043

    CubeViz.js: A Lightweight Framework for Discovering and Visualizing RDF Data Cubes

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    In this paper we present CubeViz.js, the successor of CubeViz, as an approach for lightweight visualization and exploration of statistical data using the RDF Data Cube vocabulary. In several use cases, such as the European Unions Open Data Portal, in which we deployed CubeViz, we were able to gather various requirements that eventually led to the decision of reimplementing CubeViz as JavaScript-only application. As part of this paper we showcase major functionalities of CubeViz.js and its improvements in comparison to the prior version

    Exploring meta-analysis for historical corpus linguistics based on linked data

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    Empirical work on English historical corpus linguistics is plentiful but fragmented, and some of it is hard to come by. This paper proposes a solution for making it more accessible and reusable for meta-analysis. We present an online Language Change Database (LCD), which provides comparative, real-time baseline data from earlier corpus-based studies. LCD entries summarize the findings and include numerical data from the articles. We discuss the LCD from the perspective of database design and linked data management. Furthermore, we illustrate the reuse of LCD data through a meta-analysis of the history of English connectives. For this purpose, we have developed an application called the LCD Aggregated Data Analysis workbench (LADA). We show how researchers can use LADA to filter, refine and visualize LCD data. Thus we are paving the way for a future where both research results and research data are regularly available for verification, validation and re-use.Peer reviewe

    QB4OLAP : Enabling business intelligence over semantic web data

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    Premio Primer puesto otorgado por la Academia Nacional de Ingeniería.The World-Wide Web was initially conceived as a repository of information tailored for human consumption. In the last decade, the idea of transforming the web into a machine-understandable web of data, has gained momentum. To this end, the World Wide Web Consortium (W3C) maintains a set of standards, referred to as the Semantic Web (SW), which allow to openly share data and metadata. Among these is the Resource Description Framework (RDF), which represents data as graphs, RDF-S and OWL to describe the data structure via ontologies or vocabularies, and SPARQL, the RDF query language. On top of the RDF data model, standards and recommendations can be built to represent data that adheres to other models. The multidimensional (MD) model views data in an n-dimensional space, usually called a data cube, composed of dimensions and facts. The former reflect the perspectives from which data are viewed, and the latter correspond to points in this space, associated with (usually) quantitative data (also known as measures). Facts can be aggregated, disaggregated, and filtered using the dimensions. This process is called Online Analytical Processing (OLAP). Despite the RDF Data Cube Vocabulary (QB) is the W3C standard to represent statistical data, which resembles MD data, it does not include key features needed for OLAP analysis, like dimension hierarchies, dimension level attributes, and aggregate functions. To enable this kind of analysis over SW data cubes, in this thesis we propose the QB4 OLAP vocabulary, an extension of QB. A problem remains, however: writing efficient analytical queries over SW data cubes requires a deep knowledge of RDF and SPARQL, unlikely to be found in typical OLAP users. We address this problem in this thesis. Our approach is based on allowing analytical users to write queries using what they know best: OLAP operations over data cubes, without dealing with SW technicalities. For this, we devised CQL, a simple, high-level query language over data cubes. Then we make use of the structural metadata provided by QB4 OLAP to translate CQL queries into SPARQL ones. We adapt general-purpose SPARQL query optimization techniques, and propose query improvement strategies to produce efficient SPARQL queries. We evaluate our implementation tailoring the well known Star-Schema benchmark, which allows us to compare our proposal against existing ones in a fair way. We show that our approach outperforms other ones. Finally, as another result, our experiments allow us to study which combinations of improvement strategies fits better to an analytical scenario.La World-Wide Web fue concebida como un repositorio de informa- ción a ser procesada y consumida por humanos. Pero en la última década ha ganado impulso la idea de transformar a la Web en una gran base de datos procesables por máquinas. Con este fin, el World Wide Web Consortium (W3C) ha establecido una serie de estándares también conocidos como estándares para la Web Semántica (WS), los cuales permiten compartir datos y metadatos en formatos abiertos. Entre estos estándares se destacan: el Resource Description Framework (RDF), un modelo de datos basado en grafos para representar datos y relaciones entre ellos, RDF-S y OWL que permiten describir la estructura y el significado de los datos por medio de ontologías o vocabu- larios, y el lenguaje de consultas SPARQL. Estos estándares pueden ser utilizados para construir representaciones de otros modelos de datos, por ejemplo datos tabulares o datos relacionales. El modelo de datos multidimensional (MD) representa a los datos dentro de un espacio n-dimensional, usualmente denominado cubo de datos, que se compone de dimensiones y hechos. Las primeras reflejan las perspectivas desde las cuales interesa analizar los datos, mientras que las segundas corresponden a puntos en este espacio n- dimensional, a los cuales se asocian valores usualmente numéricos, conocidos como medidas. Los hechos pueden ser agregados y resumidos, desagregados, y filtrados utilizando las dimensiones. Este pro- ceso es conocido como Online Analytical Processing (OLAP). Pese a que la W3C ha establecido un estándar que puede ser utilizado para publicación de datos multidimensionales, conocido como el RDF Data Cube Vocabulary (QB), éste no incluye algunos aspectos del modelo MD que son imprescindibles para realizar análisis tipo OLAP como son las jerarquías de dimensión, los atributos en los niveles de dimensión, y las funciones de agregaciónpara resumir valores de medidas. Para permitir este tipo de análisis sobre cubos en la SW, en esta tesis se propone un vocabulario que extiende el vocabulario QB denominado QB4OLAP. Sin embargo, para realizar análisis tipo OLAP en forma eficiente sobre cubos QB4OLAP es necesario un conocimiento profundo de RDF y SPARQL, los cuales distan de ser populares entre los usuarios OLAP típicos. Esta tesis también aborda este problema. Nuestro enfoque consiste en brindar un conjunto de operaciones clásicas para los usuarios OLAP, y luego realizar la traducción en forma automática de estas operaciones en consultas SPARQL. Comenzamos definiendo un lenguaje de consultas para cubos en alto nivel: Cube Query Language (CQL), y luego explotamos la metadata representada mediante QB4OLAP para realizar la traducción a SPARQL. Asimismo, mejoramos el rendimiento de las consultas obtenidas, adaptando y aplicando técnicas existentes de optimización de consultas SPARQL. Para evaluar nuestra propuesta adaptamos a los estándares de la SW el Star Schema benchmark, el cual es el estándar para la evaluación de sistemas tipo OLAP. Esto permite comparar nuestro enfoque con otras propuestas existentes, asi como evaluar el impacto de nuestras estrategias de mejoras de consultas SPARQL. De esta comparación podemos concluir que nuestro enfoque supera a otras propuestas existentes, y que nuestras técnicas de mejoras logran incrementar en 10 veces el rendimiento del sistema
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