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Access control and quality attributes of open data: Applications and techniques

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conference contribution
posted on 05.07.2018 by E. Karafili, Konstantina Spanaki, Emil Lupu
Open Datasets provide one of the most popular ways to acquire insight and information about individuals, organizations and multiple streams of knowledge. Exploring Open Datasets by applying comprehensive and rigorous techniques for data processing can provide the ground for innovation and value for everyone if the data are handled in a legal and controlled way. In our study, we propose an argumentation and abductive reasoning approach for data processing which is based on the data quality background. Explicitly, we draw on the literature of data management and quality for the attributes of the data, and we extend this background through the development of our techniques. Our aim is to provide herein a brief overview of the data quality aspects, as well as indicative applications and examples of our approach. Our overall objective is to bring serious intent and propose a structured way for access control and processing of open data with a focus on the data quality aspects.

Funding

Erisa Karafili was supported by the European Union’s H2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 746667

History

School

  • Business and Economics

Department

  • Business

Published in

21st International Conference on Business Information Systems (BIS 2018) - Workshop on Quality of Open Data (QOD 2018)

Citation

KARAFILI, E., SPANAKI, K. and LUPU, E., 2018. Access control and quality attributes of open data: Applications and techniques. IN: Abramowicz W. and Paschke A. (eds) Business Information Systems Workshops. BIS 2018. Chaim, Switzerland: Springer, pp. 603-614.

Publisher

Springer

Version

AM (Accepted Manuscript)

Publisher statement

The final authenticated version is available online at https://doi.org/10.1007/978-3-030-04849-5_52.

Acceptance date

20/06/2018

Publication date

2019-01-03

Notes

This paper was presented at the 21st International Conference on Business Information Systems (BIS 2018) - Workshop on Quality of Open Data (QOD 2018), Berlin, Germany, 18-20th July.

ISBN

9783030048488;9783030048495

ISSN

1865-1348;1865-1356

Book series

Lecture Notes in Business Information Processing; 339

Language

en

Location

Berlin, Germany

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