2 research outputs found
Privacy-aware Linked Widgets
The European General Data Protection Regulation (GDPR) brings
new challenges for companies, who must demonstrate that their
systems and business processes comply with usage constraints
specified by data subjects. However, due to the lack of standards,
tools, and best practices, many organizations struggle to adapt their
infrastructure and processes to ensure and demonstrate that all
data processing is in compliance with users' given consent. The
SPECIAL EU H2020 project has developed vocabularies that can
formally describe data subjects' given consent as well as methods
that use this description to automatically determine whether
processing of the data according to a given policy is compliant
with the given consent. Whereas this makes it possible to determine
whether processing was compliant or not, integration of the
approach into existing line of business applications and ex-ante
compliance checking remains an open challenge. In this short paper,
we demonstrate how the SPECIAL consent and compliance framework
can be integrated into Linked Widgets, a mashup platform, in
order to support privacy-aware ad-hoc integration of personal data.
The resulting environment makes it possible to create data integration
and processing workflows out of components that inherently
respect usage policies of the data that is being processed and are
able to demonstrate compliance. We provide an overview of the
necessary meta data and orchestration towards a privacy-aware
linked data mashup platform that automatically respects subjects'
given consents. The evaluation results show the potential of our
approach for ex-ante usage policy compliance checking within the
Linked Widgets Platforms and beyond
The CitySPIN Platform: A CPSS Environment for City-Wide Infrastructures
Cyber-physical Social System (CPSS) are complex systems that span
the boundaries of the cyber, physical and social spheres. They play
an important role in a variety of domains ranging from industry
to smart city applications. As such, these systems necessarily need
to take into account, combine and make sense of heterogeneous
data sources from legacy systems, from the physical layer and also
the social groups that are part of/use the system. The collection,
cleansing and integration of these data sources represents a major
effort not only during the operation of the system, but also during
its engineering and design. Indeed, while ongoing efforts are
concerned primarily with the operation of such systems, limited
focus has been put on supporting the engineering phase of CPSS.
To address this shortcoming, within the CitySPIN project we aim to
create a platform that supports stakeholders involved in the design
of these systems especially in terms of support for data management.
To that end, we develop methods and techniques based on
Semantic Web and Linked Data technologies for the acquisition
and integration of heterogeneous data from disparate structured,
semi-structured and unstructured sources, including open data and
social data. In this paper we present the overall system
architecturewith a core focus on data acquisition and integration.We
demon-strate our approach through a prototypical implementation
of an adaptive planning use case for public transportation
scheduling