Using a Model-driven Approach in Building a Provenance Framework for Tracking Policy-making Processes in Smart Cities
Abstract
The significance of provenance in various settings has emphasised its potential in the policy-making process for analytics in Smart Cities. At present, there exists no framework that can capture the provenance in a policy-making setting. This research therefore aims at defining a novel framework, namely, the Policy Cycle Provenance (PCP) Framework, to capture the provenance of the policy-making process. However, it is not straightforward to design the provenance framework due to a number of associated policy design challenges. The design challenges revealed the need for an adaptive system for tracking policies therefore a model-driven approach has been considered in designing the PCP framework. Also, suitability of a networking approach is proposed for designing workflows for tracking the policy-making process.
Cite
@article{arxiv.1803.06839,
title = {Using a Model-driven Approach in Building a Provenance Framework for Tracking Policy-making Processes in Smart Cities},
author = {Barkha Javed and Zaheer Khan and Richard McClatchey},
journal= {arXiv preprint arXiv:1803.06839},
year = {2018}
}
Comments
15 pages, 5 figures, 2 tables, Proc of the 21st International Database Engineering & Applications Symposium (IDEAS 2017)