Addressing exploitability of Smart City data

Abstract

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An Incremental Learning Method to Support the Annotation of Workflows with Data-to-Data Relations

“…We showed through applying this approach on a set of workflows from the My Experiments repository that it can effectively reduce the effort required to achieve this task for data managers and workflow publishers. We plan to integrate the presented approach with the methodology described in [4] in order to support Data Hub managers in the annotation of the data manipulation processes required to compute the propagation of policies associated with the data involved. We have enough confidence to believe that the characteristics of scientific workflows as data intensive workflows [16] are equivalent, because they can be reduced to data centric representations, as demonstrated in Section 3.1.…”

“…Instead on characterizing the activities of a workflow (like in [10]), Datanode can be applied to describe it in terms of relations between the input and the output of processors 12 . The resulting network of data objects can be used to reason upon the propagation of policies, for example in the context of a Smart City data hub [6,4].…”

“…Recently, a data-centric approach for the representation of data relying systems has been proposed with the aim to simulate the impact of process executions on the data involved, particularly to perform reasoning on the propagation of data policies [6,4]. This approach puts the data objects as first class citizens, aiming to represent the possible semantic relations among the data involved.…”

“…The users, all members of the research team of the authors, have skills that we consider similar to the ones of a data manager, for example in the context of a large data processing infrastructure like the one of [4]. In this experiment, users were asked to annotate each one of the IO port pairs with a semantic relation from a fixed vocabulary (the Datanode ontology), by exploiting the workflow documentation, the associated feature set and the recommendations provided.…”

Propagating Data Policies

“…Current research aims to understand how to govern the life cycle of data in City Data Hubs [8]. The diversity of data sources, owners and licences associated with the data opens a new challenge, namely the problem of data exploitability, defined as the assessment of the policies associated with the data resulting from the computation of diverse datasets implemented within a City Data Hub [4]. Indeed, assessing how the policies associated with the sensed data will be propagated to the results of a data processing pipeline is an important problem.…”