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2017 ITU Kaleidoscope Academic Conference

[6] Independent Expert Advisory Group on a Data Emerging Impacts in Open Data in in Argentina,
Revolution for Sustainable Development, “A World Chile and Uruguay. 2014, pp. 1–48.
that Counts: Mobilising the Data Revolution for [25] United Nations Development Group, “Common
Sustainable Development,” 2014. Country Assessment,” 2002.
[7] “Metrics & Indicators - Business for 2030.” [Online]. [26] L. F. Gómez and R. Heeks, “Measuring the Barriers to
Available: http://www.businessfor2030.org/metrics- Big Data for Development: Design-Reality Gap
indicators/. [Accessed: 31-Jan-2017]. Analysis in Colombia’s Public Sector,” 2016.
[8] High-Level Panel of Eminent Persons on the Post- [27] Committee for the Coordination of Statistical
2015 Development Agenda, “A New Global Activities and Statistical Office of the European
Partnership: Eradicate Poverty and Transform Communities, “Revised International Statistical
Economies through Sustainable Development,” 2013. Processes Assessment Checklist,” 2009.
[9] United Nations, “Fundamental Principles of Official [28] Organisation for Economic Co-operation and
Statistics,” 2014. Development, “OECD Glossary of Statistical Terms -
[10] Sustainable Development Solutions Network, Statistical standard Definition.” [Online]. Available:
“Leaving No One Behind : Disaggregating Indicators http://stats.oecd.org/glossary/detail.asp?ID=4920.
for the SDGs,” 2015. [Accessed: 26-Jun-2017].
[11] H. Robinson and D. Obuwa, “Quality assurance of [29] M. Giacalone and S. Scippacercola, “Big Data: Issues
new methods in National Accounts,” Econ. Trends, and an Overview in Some Strategic Sectors,” J. Appl.
vol. April, no. 629, pp. 14–19, 2006. Quant. Methods, vol. 11, no. 3, pp. 1–18, 2016.
[12] Office for National Statistics United Kingdom, [30] Office for National Statistics United Kingdom,
“Framework for National Statistics,” 2000. “National Statistics Code of Practice: Statement of
[13] European Central Bank, “ECB Statistics Quality Principles,” 2002.
Framework (SQF),” 2008. [31] UNDESA Statistics Division, “Generic Statistical
[14] “Monitoring and evaluation | Sustainable Development Information Model (GSIM): Statistical Classifications
Goals Fund.” [Online]. Available: Model,” 2015.
http://www.sdgfund.org/monitoring-and-evaluation. [32] UNECE Secretariat, “Generic Statistical Business
[Accessed: 02-Mar-2017]. Process Model: GSBPM,” 2013.
[15] G. Brancato, F. D’Assisi Barbalace, M. Signore, and [33] “Modernisation Maturity Model (MMM) - Roadmap
G. Simeoni, “Introducing a framework for process for Implementing Modernstats Standards - UNECE
quality in National Statistical Institutes,” Stat. J. IAOS, Statistics Wikis.” [Online]. Available:
vol. 33, no. 2, pp. 441–446, 2017. http://www1.unece.org/stat/platform/pages/viewpage.a
[16] S. Portillo and K. Moore, “A systematic approach to ction?pageId=129172266. [Accessed: 28-Feb-2017].
quality: the development and implementation of a [34] M. C. Paulk, B. Curtis, M. B. Chrissis, and C. V.
quality management framework in the Central Weber, “Capability Maturity Model for Software,
Statistics Office, Ireland,” in European Conference on Version 1.1,” 1993.
Quality in Official Statistics, 2016, pp. 1–12. [35] K. Jugdev and J. Thomas, “Project Management
[17] OECD, “Quality Framework and Guidelines for Maturity Models: The Silver Bullets of Competitive
OECD Statistical Activities,” 2012. Advantage?,” Proj. Manag. J., vol. 33, no. 4, pp. 4–
[18] International Monetary Fund Statistics Department, 14, 2002.
“IMF’s Data Quality Assessment Framework,” in [36] T. De Bruin, R. Freeze, U. Kaulkarni, and M.
Conference on Data Quality for International Rosemann, “Understanding the Main Phases of
Organizations, 2010, pp. 1–11. Developing a Maturity Assessment Model,” in
[19] S. M. Dahlgaard-Park, “Total Quality Management Australasian Conference on Information Systems
(TQM),” SAGE Encycl. Qual. Serv. Econ., pp. 808– (ACIS), 2005, pp. 8–19.
812, 2015. [37] “Quality Assessment of Big Data with GIS,” in AGILE
[20] J. Dygaszewicz and B. Szafranski, “Introducing EA 2017, 2017, pp. 1–6.
Framework in Statistics Poland,” Comput. Sci. Math. [38] “Sustainable Development Goals Beliefs and
Model., vol. 3, pp. 23–32, 2016. Principles | Agora Portal.” [Online]. Available:
[21] Eurostat, “ESS EA Reference Framework,” 2015. https://www.agora-parl.org/resources/aoe/sustainable-
[22] T. Lalor and A. Gregory, “Common Statistical development-goals-beliefs-and-principles. [Accessed:
Production Architecture,” in 5th Annual European 05-Jun-2017].
DDI User Conference, 2015, pp. 1–50. [39] M. Thinyane, “Investigating an Architectural
[23] T. Koskimäki and V. Koskinen, “Governmental and Framework for Small Data Platforms,” in 17th
Statistical Enterprise Architectures as Tools for European Conference on Digital Government, 2017,
Modernizing the National Statistical System,” in pp. 220–227.
European Conference on Quality in Official Statistics, [40] M. Best, “Small Data and Sustainable Development,”
2016, pp. 1–10. in Int. Conf. on Communication/Culture and SDGs:
[24] S. Elena, N. Aquilino, and A. Pichón Riviére, Challenges for a new generation., 2015, pp. 1–6.

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