Access Control and Quality Attributes of Open Data: Applications and Techniques
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Accepted version
Supporting information
Author(s)
Karafili, E
Spanaki, Konstantina
Lupu, Emil
Type
Conference Paper
Abstract
Open Datasets provide one of the most popular ways to ac- quire 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.
Date Issued
2019-01-03
Date Acceptance
2018-06-29
Citation
Lecture Notes in Business Information Processing, 2019, 339, pp.603-614
ISSN
1865-1348
Publisher
Springer Verlag (Germany)
Start Page
603
End Page
614
Journal / Book Title
Lecture Notes in Business Information Processing
Volume
339
Copyright Statement
© Springer Nature Switzerland AG 2019. The final publication is available at Springer via https://link.springer.com/chapter/10.1007/978-3-030-04849-5_52
Sponsor
Commission of the European Communities
Grant Number
746667
Source
Workshop on Quality of Open Data
Publication Status
Published
Start Date
2018-07-18
Coverage Spatial
Berlin, Germany