Using a Model-driven Approach in Building a Provenance Framework for Tracking Policy-making Processes in Smart Cities

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 policymaking 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.

[1]  David Ríos Insua,et al.  Policy analysis and policy analytics , 2016, Ann. Oper. Res..

[2]  James Cheney,et al.  Provenance as Dependency Analysis , 2007, DBPL.

[3]  J. Gareth Polhill,et al.  eSocial Science and Evidence-Based Policy Assessment : Challenges and Solutions , 2022 .

[4]  Karoliina Jarenko,et al.  New Approaches to Urban Planning - Insights from Participatory Communities , 2013 .

[5]  Farhana Sajjad,et al.  An analytical framework for workflow technology adoption in local government authorities , 2014 .

[6]  Sudha Ram,et al.  A New Perspective on Semantics of Data Provenance , 2009, SWPM.

[7]  Kawa Nazemi,et al.  The FUPOL Policy Lifecycle , 2014 .

[8]  E. Ostrom.  Institutional Rational Choice , 2019, Theories of the Policy Process.

[9]  Ann Macintosh,et al.  E-participation and Governance: Widening the net , 2005 .

[10]  Georgios K. Ouzounis,et al.  Smart cities of the future , 2012, The European Physical Journal Special Topics.

[11]  Alexis Tsoukiàs,et al.  From evidence-based policy making to policy analytics , 2016, Ann. Oper. Res..

[12]  David Ludlow,et al.  ICT enabled participatory urban planning and policy development: The UrbanAPI project , 2014 .

[13]  Chris Mellish,et al.  e-Social Science and Evidence-Based Policy Assessment , 2009 .

[14]  Daniel W. Margo,et al.  Using Provenance to Extract Semantic File Attributes , 2010, TaPP.

[15]  Ronald E. Weber,et al.  The "Politics" of Redistribution , 1975 .

[16]  Vishanth Weerakkody,et al.  Supporting Public Policy Making Processes with Workflow Technology: Lessons Learned From Cases in Four European Countries , 2012, Int. J. Electron. Gov. Res..

[17]  Zheng Liu,et al.  A Method to Build and Analyze Scientific Workflows from Provenance through Process Mining , 2011, TaPP.

[18]  Sarvapali D. Ramchurn,et al.  Interpretation of Crowdsourced Activities Using Provenance Network Analysis , 2013, HCOMP.

[19]  Ortwin Renn,et al.  Public participation in decision making: A three-step procedure , 1993, Policy Sciences.

[20]  Merilee S. Grindle,et al.  After the decision: Implementing policy reforms in developing countries , 1990 .

[21]  A. Tsoukiàs,et al.  Policy analytics: an agenda for research and practice , 2013 .

[22]  Maria Wimmer,et al.  Evidence Based and Conceptual Model Driven Approach for Agent-Based Policy Modelling , 2015, J. Artif. Soc. Soc. Simul..

[23]  Wil M.P. van der Aalst.  Process Mining: Overview and Opportunities , 2012, TMIS.

[24]  James Frew,et al.  Lineage retrieval for scientific data processing: a survey , 2005, CSUR.

[25]  Daniel A. Mazmanian,et al.  A Multivariate Model of Public Policy-Making , 1980 .

[26]  Bernhard Rumpe,et al.  Model-driven Development of Complex Software : A Research Roadmap , 2007 .