Using the Linked Data Approach in European e-Government Systems

Author:

Janev Valentina1,Mijović Vuk2,Vraneš Sanja1

Affiliation:

1. The Mihajlo Pupin Institute, University of Belgrade, Belgrade, Serbia

2. The Mihajlo Pupin Institute, University of Belgrade, Belgrade, Serbia

Abstract

This article describes the Linked Data approach, based on principles defined back in 2006, which can play an important role in the domain of semantic interoperabiity of government services. Therefore, this article explores the technical aspects and challenges of implementation of the revised European Directive on the Public Sector Information (2013/37/EU) that provides a common legal framework for a European market for government-held data (public sector information). It examines how the Linked Data approach facilitates the PSI Directive implementation, and in particular, the maturity of standards and tools for statistical Linked Data processing. The statistical domain has been selected due to its relevance for policy prediction, planning and adjustments, and well as its significant impact on the society, from citizens to businesses to governments. The main contributions are related to the delivered state-of-the-art open-source tools for the managing statistical Linked Data and metadata—quality assessment, exploration—and the recommendations that have been integrated in the EU SHARE-PSI Best Practices collection.

Publisher

IGI Global

Subject

Computer Networks and Communications,Information Systems

Reference32 articles.

1. Aracri, R., De Francisci, S., Pagano, A., Scannapieco, M., Tosco, L., & Valentino, L. (2014). Publishing the 15th Italian Population and Housing Census as Linked Open Data. In Capadisli, S. et al. (Eds.), Proceedings of the 2nd International Workshop on International Workshop on Semantic Statistics, RWTH Aachen University.

2. Linked Open Data -- Creating Knowledge Out of Interlinked Data

3. Making the web a data washing machine – Creating knowledge out of interlinked data.;S.Auer;Semantic Web Journal,2010

4. Bargiotti, L., De Keyzer, M., Goedertier, S., & Loutas, N. (2014, July). Value-based prioritisation of open government data investments. Paper presented at the 1st SHARE-PSI Workshop, Samos, Greece, June 30-July 1. Retrieved August 10, 2017, from https://www.w3.org/2013/share-psi/wiki/images/c/c0/Paper_Publishing_high-value_datasets_as_a_priority.pdf

5. Berners-Lee, T. (2006). Design issues: Linked data. Retrieved August 10, 2017, from http://www.w3.org/DesignIssues/LinkedData.html

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Goal Modeling for Linked Data Exploitation of Municipalities Data Access in South Africa;Software Engineering Application in Systems Design;2023

2. Data-Driven Construction Safety Information Sharing System Based on Linked Data, Ontologies, and Knowledge Graph Technologies;International Journal of Environmental Research and Public Health;2022-01-11

3. Arabic linked drug dataset consolidating and publishing;Computer Science and Information Systems;2021

4. Semantic Intelligence in Big Data Applications;Smart Connected World;2021

5. The Effect of Gender, Age, and Education on the Adoption of Mobile Government Services;International Journal on Semantic Web and Information Systems;2020-07

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3