Access Control and Quality Attributes of Open Data: Applications and Techniques

Abstract

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.

AI applications of data sharing in agriculture 4.0: A framework for role-based data access control

“…The DSAs are heterogeneous, and therefore, they present various conflicts, especially between legal and business or user requirements. Thus, the DSAs require expressive language to represent the agreements (Karafili & Lupu, 2017;Karafili, Spanaki, & Lupu, 2018a;Karafili et al, 2018b). The studies of DSAs propose a policy language based on logic programming that represents complex agreements and an analysis process for capturing the conflicts and the associated solutions.…”

“…The studies of DSAs propose a policy language based on logic programming that represents complex agreements and an analysis process for capturing the conflicts and the associated solutions. The main structure of DSAs, as presented in Table 1, requires already defined (a) actors and roles, as well as (b) the variations of the data categories (data management aspects), so as rules and conditions can be formed for the DSAs (Karafili & Lupu, 2017;Karafili et al, 2018aKarafili et al, , 2018b.…”

“…The first step is to agree on the terms of the DSAs, where some DSAs terms, usually legal ones, are irrefutable. The DSA rules are represented using a policy analysis language that is an enhanced version of the language presented in (Karafili & Lupu, 2017;Karafili et al, 2018aKarafili et al, , 2018b. For the sake of simplicity, in this paper, we do not present the DSAs rules with the policy language, but we use a semi-natural language.…”

Importance of the Open Data Assessment: An Insight Into the (Meta) Data Quality Dimensions

“…Quality assessment through standalone dimensions. Karafili et al (2019) defined quality attributes of OD, which are part of one dimension. Sáez Martín et al ( 2015) developed a quality index consisting of several descriptions.…”