The Experts below are selected from a list of 312 Experts worldwide ranked by ideXlab platform
Michèle Basseville - One of the best experts on this subject based on the ideXlab platform.
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Divergence measures for Statistical Data processing—An annotated bibliography
Signal Processing, 2013Co-Authors: Michèle BassevilleAbstract:This paper provides an annotated bibliography for investigations based on or related to divergence measures for Statistical Data processing and inference problems.
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review divergence measures for Statistical Data processing an annotated bibliography
Signal Processing, 2013Co-Authors: Michèle BassevilleAbstract:This paper provides an annotated bibliography for investigations based on or related to divergence measures for Statistical Data processing and inference problems.
Konstantinos Tarabanis - One of the best experts on this subject based on the ideXlab platform.
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Towards Interoperable Open Statistical Data
2019Co-Authors: Evangelos Kalampokis, Areti Karamanou, Konstantinos TarabanisAbstract:An important part of Open Data is of Statistical nature and describes economic and social indicators monitoring population size, inflation, trade, and employment. Combining and analysing Open Data from multiple Datasets and sources enable the performance of advanced Data analytics scenarios that could result in valuable services and Data products. However, it is still difficult to discover and combine open Statistical Data that reside in different Data portals. Although Linked Open Statistical Data (LOSD) provide standards and approaches to facilitate combining statistics on the Web, various interoperability challenges still exist. In this paper, we define interoperability conflicts that hamper combining and analysing LOSD from different portals. Towards this end, we start from a thorough literature review on Databases and Data warehouses interoperability conflicts. Based on this review, we define interoperability conflicts that may appear in LOSD. We defined two types of schema-level conflicts namely, naming conflicts and structural conflicts. Naming conflicts include homonyms and synonyms and result from the different URIs used in the Data cubes. Structural conflicts result from different practices of modelling the structure of Data cubes.
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On modeling linked open Statistical Data
Journal of Web Semantics, 2019Co-Authors: Evangelos Kalampokis, Dimitris Zeginis, Konstantinos TarabanisAbstract:Abstract A major part of Open Data concerns statistics such as economic and social indicators. Statistical Data are structured in a multidimensional manner creating Data cubes. Recently, National Statistical Institutes and public authorities adopted the Linked Data paradigm to publish their Statistical Data on the Web. Many vocabularies have been created to enable modeling Data cubes as RDF graphs, and thus creating Linked Open Statistical Data (LOSD). However, the creation of LOSD remains a demanding task mainly because of modeling challenges related either to the conceptual definition of the cube, or to the way of modeling cubes as linked Data. The aim of this paper is to identify and clarify (a) modeling challenges related to the creation of LOSD and (b) approaches to address them. Towards this end, nine LOSD experts were involved in an interactive feedback collection and consensus-building process that was based on Delphi method. We anticipate that the results of this paper will contribute towards the formulation of best practices for creating LOSD, and thus facilitate combining and analyzing Statistical Data from diverse sources on the Web.
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Open Statistical Data: Potential and Challenges
2016Co-Authors: Efthimios Tambouris, Marijn Janssen, Evangelos Kalampokis, Bill Roberts, Paul Hermans, T. Alcorn, Konstantinos TarabanisAbstract:Opening up Data is a political priority worldwide. Linked open Data is considered as the most mature technology for publishing and reusing open Data. A large number of open Data is numerical and actually concerns statistics. In the literature, Statistical Data have been heavily studied using the Data cube model. Recently, ICT tools have emerged aiming to exploit linked open Data technologies for providing advanced visualizations and analytics of open Statistical Data residing in geographically dispersed open Data portals. The aim of this panel is to discuss the potential and challenges of open Statistical Data.
Evangelos Kalampokis - One of the best experts on this subject based on the ideXlab platform.
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Towards Interoperable Open Statistical Data
2019Co-Authors: Evangelos Kalampokis, Areti Karamanou, Konstantinos TarabanisAbstract:An important part of Open Data is of Statistical nature and describes economic and social indicators monitoring population size, inflation, trade, and employment. Combining and analysing Open Data from multiple Datasets and sources enable the performance of advanced Data analytics scenarios that could result in valuable services and Data products. However, it is still difficult to discover and combine open Statistical Data that reside in different Data portals. Although Linked Open Statistical Data (LOSD) provide standards and approaches to facilitate combining statistics on the Web, various interoperability challenges still exist. In this paper, we define interoperability conflicts that hamper combining and analysing LOSD from different portals. Towards this end, we start from a thorough literature review on Databases and Data warehouses interoperability conflicts. Based on this review, we define interoperability conflicts that may appear in LOSD. We defined two types of schema-level conflicts namely, naming conflicts and structural conflicts. Naming conflicts include homonyms and synonyms and result from the different URIs used in the Data cubes. Structural conflicts result from different practices of modelling the structure of Data cubes.
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On modeling linked open Statistical Data
Journal of Web Semantics, 2019Co-Authors: Evangelos Kalampokis, Dimitris Zeginis, Konstantinos TarabanisAbstract:Abstract A major part of Open Data concerns statistics such as economic and social indicators. Statistical Data are structured in a multidimensional manner creating Data cubes. Recently, National Statistical Institutes and public authorities adopted the Linked Data paradigm to publish their Statistical Data on the Web. Many vocabularies have been created to enable modeling Data cubes as RDF graphs, and thus creating Linked Open Statistical Data (LOSD). However, the creation of LOSD remains a demanding task mainly because of modeling challenges related either to the conceptual definition of the cube, or to the way of modeling cubes as linked Data. The aim of this paper is to identify and clarify (a) modeling challenges related to the creation of LOSD and (b) approaches to address them. Towards this end, nine LOSD experts were involved in an interactive feedback collection and consensus-building process that was based on Delphi method. We anticipate that the results of this paper will contribute towards the formulation of best practices for creating LOSD, and thus facilitate combining and analyzing Statistical Data from diverse sources on the Web.
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DG.O - Theory and practice of linked open Statistical Data
Proceedings of the 19th Annual International Conference on Digital Government Research: Governance in the Data Age, 2018Co-Authors: Efthimios Tambouris, Marijn Janssen, Evangelos Kalampokis, Paul Hermans, Ricardo Matheus, Tarmo KalvetAbstract:The number of Open Statistical Data available for reuse is rapidly increasing. Linked open Data technology enables easy reuse and linking of Data residing in different locations in a simple and straightforward manner. Yet, many people are not familiar with the technology standards and tools for making use of open Statistical Data. In this tutorial, we will introduce Linked Open Statistical Data (LOSD) and demonstrate the use of LOSD technologies and tools to visualize open Data obtained from various European Countries. We will also give the participants the opportunity to use these tools thus obtaining a personal experience on their capabilities.
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Open Statistical Data: Potential and Challenges
2016Co-Authors: Efthimios Tambouris, Marijn Janssen, Evangelos Kalampokis, Bill Roberts, Paul Hermans, T. Alcorn, Konstantinos TarabanisAbstract:Opening up Data is a political priority worldwide. Linked open Data is considered as the most mature technology for publishing and reusing open Data. A large number of open Data is numerical and actually concerns statistics. In the literature, Statistical Data have been heavily studied using the Data cube model. Recently, ICT tools have emerged aiming to exploit linked open Data technologies for providing advanced visualizations and analytics of open Statistical Data residing in geographically dispersed open Data portals. The aim of this panel is to discuss the potential and challenges of open Statistical Data.
Marco A. Casanova - One of the best experts on this subject based on the ideXlab platform.
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PUBLISHING Statistical Data ON THE WEB
International Journal of Semantic Computing, 2012Co-Authors: Percy E. Rivera Salas, Michael Martin, Fernando Maia Da Mota, Karin Breitman, Marco A. Casanova, Sören AuerAbstract:Statistical Data is one of the most important sources of information, relevant for large numbers of stakeholders in the governmental, scientific and business domains alike. In this article, we over...
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ICSC - Publishing Statistical Data on the Web
2012 IEEE Sixth International Conference on Semantic Computing, 2012Co-Authors: Percy E. Rivera Salas, Michael Martin, Fernando Maia Da Mota, Sören Auer, Karin Breitman, Marco A. CasanovaAbstract:Statistical Data is one of the most important sources of information, relevant for large numbers of stakeholders in the governmental, scientific and business domains alike. In this article, we overview how Statistical Data can be managed on the Web. With OLAP2 Data Cube and CSV2 Data Cube we present two complementary approaches on how to extract and publish Statistical Data. We also discuss the linking, repair and the visualization of Statistical Data. As a comprehensive use case, we report on the extraction and publishing on the Web of Statistical Data describing 10 years of life in Brazil.
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TOPI@ICSE - OLAP2DataCube: an ontowiki plug-in for Statistical Data publishing
2012 Second International Workshop on Developing Tools as Plug-Ins (TOPI), 2012Co-Authors: Percy E. Rivera Salas, Michael Martin, Fernando Maia Da Mota, Sören Auer, Karin Breitman, Marco A. CasanovaAbstract:Statistical Data is one of the most important sources of information, relevant for large numbers of stakeholders in the governmental, scientific and business domains alike. In this article, we introduce an Ontowiki plugin that extracts and publishes Statistical Data in RDF. We illustrate the plugin with a comprehensive use case reporting on the extraction and publishing on the Web of Statistical Data about 10 years of Brazilian government.
Sören Auer - One of the best experts on this subject based on the ideXlab platform.
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Semantic Similarity and Correlation of Linked Statistical Data Analysis
2014Co-Authors: Sarven Capadisli, Sören Auer, A. Merono, Reinhard RiedlAbstract:Statistical Data is increasingly made available in the form of Linked Data on the Web. As more and more Statistical Datasets become available, a fundamental question on Statistical Data comparability arises: To what extent can arbitrary Statistical Datasets be faithfully compared? Besides a purely Statistical comparability, we are interested in the role that semantics plays in the Data to be compared. Our hypothesis is that semantic relationships between different components of Statistical Datasets might have a relationship with their Statistical correlation. Our research focuses in studying whether these Statistical and semantic relationships influence each other, by comparing the correlation of Statistical Data with their semantic similarity. The ongoing research problem is, hence, to investigate why machines have a difficulty in revealing meaningful correlations or establishing non-coincidental connection between variables in Statistical Datasets. We describe a fully reproducible pipeline to compare Statistical correlation with semantic similarity in arbitrary Linked Statistical Data. We present a use case using World Bank Data expressed as RDF Data Cube, and we highlight whether Dataset titles can help predict strong correlations.
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PUBLISHING Statistical Data ON THE WEB
International Journal of Semantic Computing, 2012Co-Authors: Percy E. Rivera Salas, Michael Martin, Fernando Maia Da Mota, Karin Breitman, Marco A. Casanova, Sören AuerAbstract:Statistical Data is one of the most important sources of information, relevant for large numbers of stakeholders in the governmental, scientific and business domains alike. In this article, we over...
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ICSC - Publishing Statistical Data on the Web
2012 IEEE Sixth International Conference on Semantic Computing, 2012Co-Authors: Percy E. Rivera Salas, Michael Martin, Fernando Maia Da Mota, Sören Auer, Karin Breitman, Marco A. CasanovaAbstract:Statistical Data is one of the most important sources of information, relevant for large numbers of stakeholders in the governmental, scientific and business domains alike. In this article, we overview how Statistical Data can be managed on the Web. With OLAP2 Data Cube and CSV2 Data Cube we present two complementary approaches on how to extract and publish Statistical Data. We also discuss the linking, repair and the visualization of Statistical Data. As a comprehensive use case, we report on the extraction and publishing on the Web of Statistical Data describing 10 years of life in Brazil.
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TOPI@ICSE - OLAP2DataCube: an ontowiki plug-in for Statistical Data publishing
2012 Second International Workshop on Developing Tools as Plug-Ins (TOPI), 2012Co-Authors: Percy E. Rivera Salas, Michael Martin, Fernando Maia Da Mota, Sören Auer, Karin Breitman, Marco A. CasanovaAbstract:Statistical Data is one of the most important sources of information, relevant for large numbers of stakeholders in the governmental, scientific and business domains alike. In this article, we introduce an Ontowiki plugin that extracts and publishes Statistical Data in RDF. We illustrate the plugin with a comprehensive use case reporting on the extraction and publishing on the Web of Statistical Data about 10 years of Brazilian government.
