A Provenance Framework for Policy Analytics in Smart Cities

Barkha Javed, Richard McClatchey, Zaheer Khan, Jetendr Shamdasani

Abstract

Sustainable urban environments require appropriate policy management. However, such policies are established as a result of underlying, potentially complex and long-term policy making processes. Consequently, better policies require improved and verifiable planning processes. In order to assess and evaluate the planning process, transparency of the system is pivotal which can be achieved by tracking the provenance of policy making process. However, at present no system is available that can track the complete cycle of urban planning and decision making. We propose to capture the complete process of policy making and to investigate the role of Internet of Things (IoT) provenance to support design-making for policy analytics and implementation. The environment in which this research will be demonstrated is that of Smart Cities whose requirements will drive the research process.

References

  1. Bakici, T. et al., (2013). A Smart City Initiative: The Case of Barcelona. Journal of the Knowledge Economy. pp.135-148.
  2. Batty, M. et al., (2012). Smart cities of the future. European Physical Journal Special Topics, pp. 481- 518.
  3. Bristol Is Open project. Available at: www.bristolisopen.com [Accessed 4 March, 2016].
  4. British Standard Institute, (2014). PAS 181: 2014 Smart city framework - Guide to establishing strategies for smart cities and communities. United Kingdom. Available at: http://www.bsigroup.com/en-GB/smartcities/Smart- Cities-Standards-and-Publication/PAS181-smart-cities-framework/
  5. Carata, L. et al., (2014). A Primer on Provenance. Commun. ACM.
  6. Ceolin, D. et al., (2013). Reliability Analyses of Open Government Data. In URSW, pp. 34-39.
  7. Chourabi, H. et al., (2012). Understanding Smart Cities: An Integrative Framework. The 45th Hawaii International Conference on System Sciences, pp. 2289 - 2297.
  8. Coglianese, C. et al., (2008). Transparency and Public Participation in the Rulemaking Process. A Nonpartisan Presidential Transition Task Force Report.
  9. Daniell, K. A. et al., (2015). Policy analysis and policy analytics. Annals of Operations Research., 10.1007/s10479-015-1902-9
  10. d'Aquin, M. et al., (2014). Dealing with Diversity in a Smart-City Datahub. In Fifth Workshop on Semantics for Smarter Cities. pp. 68-82.
  11. De Marchi, G. et al., (2012). From Evidence Based Policy Making to Policy Analytics. Cahier du LAMSADE 319. Université Paris Dauphine, Paris.
  12. Edwards, P. et al., (2009). esocial science and evidencebased policy assessment: challenges and solutions. Social Science Computer Review. vol. 27(4), pp. 553- 568.
  13. Emaldi et al., (2013). To trust, or not to trust: Highlighting the need for data provenance in mobile apps for smart cities. International Workshop on Semantic Sensor Networks (SSN).
  14. FUPOL. Available at: http://www.fupol.eu/en [Accessed 4 March, 2016]
  15. Geiger, C. P and Lucke, J. V., (2011). Open Government Data. In CeDEM11. Conference for E-Democracy and Open Government. pp. 183-194.
  16. Horelli, L. and Wallin, S., (2013). New Approaches to Urban Planning Insights from Participatory Communities. Aalto University Publication series Aalto-ST 10/2013, pp.11-16.
  17. Huynh, T. D., et al., (2013). Interpretation of crowdsourced activities using provenance network analysis. In: First AAAI Conference on Human Computation and Crowdsourcing.
  18. Jeannine, E. R. and Sabharwal, M., (2009). Perceptions of Transparency of Government Policymaking: A CrossNational Study. Government Information Quarterly 26(1): pp.148-157.
  19. Kaschesky, M. et al., (2011). Opinion mining in social media: modeling, simulating, and visualizing political opinion formation in the web. In: International Conference on Digital Government Research.
  20. Khan, Z. et al., (2014). ICT enabled participatory urban planning and policy development: The UrbanAPI project. Transforming Government: People, Process and Policy, 8 (2). pp. 205-229. ISSN 1750-6166.
  21. Liu, Q. et al., (2013). Data Provenance and Data Management Systems. In Data Provenance and Data Management in eScience, Springer Berlin Heidelberg.
  22. Lopez-de-Opina, D. et al., (2013). Citizen-centric Linked Data Apps for Smart Cities. Lecture Notes in Computer Science, Springer Publishers. pp. 70-77.
  23. Lotzmann, U. and Wimmer, M., (2012). Provenance and Traceability in Agent-based Policy Simulation. In Proceedings of 26th European Simulation and Modelling Conference - ESM'2012.
  24. Luzeaux, D. and Ruault, J. R., (2010). Systems of Systems. ISTE Ltd and John Wiley & Sons Inc.
  25. Margo, D and Smogor, R., (2010) Using provenance to extract semantic file attributes. In: Proceedings of the 2nd conference on Theory and practice of provenance.
  26. McClatchey, R. et al., (2014). Provenance Support for Medical Research. In 5th International Provenance and Annotation Workshop (IPAW2014).
  27. Packer, H. et al., (2014). Semantics and Provenance for Accountable Smart City Applications. Semantic Web - Interoperability, Usability, Applicability an IOS Press Journal.
  28. Ram, S. and Liu, J., (2009). A new perspective on Semantics of Data Provenance. First International Workshop on the role of Semantic Web in Provenance Management (SWPM).
  29. Scherer, S. et al. (2015). Evidence Based and Conceptual Model Driven Approach for Agent-Based Policy Modelling. Journal of Artificial Societies and Social Simulation.
  30. Shamdasani, J. et al. (2014). CRISTAL-ISE : Provenance Applied in Industry. Proceedings of the 16th International Conference on Enterprise Information Systems (ICEIS).
  31. Simmhan, Y. L. et al., (2005). A Survey of Data Provenance Techniques. In Technical Report TR-618: Computer Science Department, Indiana University.
  32. Smarticipate, (2016). Smart services for calculated impact assessment in open governance. EC H2020 Project start February 2016.
  33. Tsoukiàs, A. et al., (2013). Policy analytics: An agenda for research and practice. EURO Journal on Decision Processes, 1, 115-134.
  34. Urban API, (2014). Interactive Analysis, Simulation and Visualisation Tools for Urban Agile Policy Implementation. Available at: http://www.urbanapi.eu/ [Accessed 5 March, 2016]
  35. World Health Organization, (2016). Climate change and human health. Available at: http://www.who.int/ globalchange/ecosystems/urbanization/en/ [Accessed 5 March, 2016].
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Paper Citation


in Harvard Style

Javed B., McClatchey R., Khan Z. and Shamdasani J. (2016). A Provenance Framework for Policy Analytics in Smart Cities . In Proceedings of the International Conference on Internet of Things and Big Data - Volume 1: IoTBD, ISBN 978-989-758-183-0, pages 429-434. DOI: 10.5220/0005931504290434


in Bibtex Style

@conference{iotbd16,
author={Barkha Javed and Richard McClatchey and Zaheer Khan and Jetendr Shamdasani},
title={A Provenance Framework for Policy Analytics in Smart Cities},
booktitle={Proceedings of the International Conference on Internet of Things and Big Data - Volume 1: IoTBD,},
year={2016},
pages={429-434},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005931504290434},
isbn={978-989-758-183-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Internet of Things and Big Data - Volume 1: IoTBD,
TI - A Provenance Framework for Policy Analytics in Smart Cities
SN - 978-989-758-183-0
AU - Javed B.
AU - McClatchey R.
AU - Khan Z.
AU - Shamdasani J.
PY - 2016
SP - 429
EP - 434
DO - 10.5220/0005931504290434