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Exploring linked statistical data using linked widgets

Published: 04 December 2014 Publication History

Abstract

The Open Data movement has gained momentum among governments, in the business world, and in the public sector in recent years. This movement has resulted in a growing number of open and accessible datasets that have established a solid basis for enhanced service offerings and improved experiences for citizens and businesses. Statistical data, which embodies a big portion of Open Data, comprises a wide range of domains including finance, demographics, transportation, employment, etc. Statistical data plays an important role in public policy formation and as a facilitator for informed decision-making in the private sector. Linked Statistical Data is an evolving concept that combines the richness of Linked Data (a set of best practices for publishing and connecting structured data on the Web) with the descriptiveness of statistical data to integrate data from multiple sources and put it in a semantic context. In this short paper, Linked Statistical Data limitations and challenges are explored before introducing Linked Widgets as an innovative approach.

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Tuan-Dat Trinh, Ba-Lam Do, Peter Wetz, Amin Anjomshoaa, A Min Tjoa. 2013. Linked widgets an approach to exploit open government data. In International Conference on Information Integration and Web-based Application & Services (IIWAS)
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Ba-Lam Do, Tuan-Dat Trinh, Peter Wetz, Amin Anjomshoaa, Elmar Kiesling, A Min Tjoa. 2014. Widget-based Exploration of Linked Statistical Data Spaces. In 3rd International Conference on Data Management Technologies and Applications (DATA).
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  • (2016)Experiences about opening data in private sector: A systematic literature review2016 SAI Computing Conference (SAI)10.1109/SAI.2016.7556060(715-724)Online publication date: Jul-2016

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cover image ACM Other conferences
SoICT '14: Proceedings of the 5th Symposium on Information and Communication Technology
December 2014
304 pages
ISBN:9781450329309
DOI:10.1145/2676585
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

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Published: 04 December 2014

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  • (2016)Experiences about opening data in private sector: A systematic literature review2016 SAI Computing Conference (SAI)10.1109/SAI.2016.7556060(715-724)Online publication date: Jul-2016

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