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Process and economic evaluation of the ODI R&D programme: Final report (2021)
Report
Ritchie, F., Tava, F., Whittard, D., Green, E., Beata Kreft, M., & Alves, K. (2021). Process and economic evaluation of the ODI R&D programme: Final report. London: Open Data Institute

The Open Data Institute was funded by Innovate UK to undertake a major programme of Research and Development on "Data Innovation for the UK", which was re-scoped and funded on a yearly basis for a total of 4 years (called, for short, "The R&D program... Read More about Process and economic evaluation of the ODI R&D programme: Final report.

Measuring the value of improving data governance and access in Gates Foundation programme: A case study of the Supporting Soil Health Interventions in Ethiopia projects (2021)
Report
Ritchie, F., Whittard, D., & Nyengani, J. (in press). Measuring the value of improving data governance and access in Gates Foundation programme: A case study of the Supporting Soil Health Interventions in Ethiopia projects. Wallingford: Centre for Agriculture and Bioscience International

The Centre for Agriculture and Bioscience International (CABI) and the Open Data Institute (ODI) commissioned a team of economists to measure the value of improving data governance and access in the Supporting Soil Health Interventions in Ethiopia (S... Read More about Measuring the value of improving data governance and access in Gates Foundation programme: A case study of the Supporting Soil Health Interventions in Ethiopia projects.

Understanding a pandemic: The power of administrative data (2021)
Book Chapter
Waind, E., Ritchie, F., Bailey, N., Caskie, P., Morrison-Rees, S., Lowe, S., & Webster, N. (2021). Understanding a pandemic: The power of administrative data. In Productivity and the Pandemic. Edward Elgar Publishing

This chapter is taken from the book Productivity and the Pandemic. It suggests how administrative data is essential to understanding what is happening now, and what happpens next.

Microdata access and privacy: What have we learned over twenty years? (2021)
Journal Article
Ritchie, F. (2021). Microdata access and privacy: What have we learned over twenty years?. Journal of Privacy and Confidentiality, 11(1), 1-8. https://doi.org/10.29012/jpc.766

Felix Ritchie reflects on lessons learned in twenty years of microdata access in the UK and Canada. Based on his contribution to the panel on "Privacy And Microdata Access: Two Worlds Colliding?" at the October 2020 Canadian Research Data Centre Netw... Read More about Microdata access and privacy: What have we learned over twenty years?.

Financial resilience, income dependence and organisational survival in UK charities (2021)
Journal Article
Green, E., Ritchie, F., Bradley, P., & Parry, G. (in press). Financial resilience, income dependence and organisational survival in UK charities. Voluntas: International Journal of Voluntary and Nonprofit Organizations, https://doi.org/10.1007/s11266-020-00311-9

The financial well-being of the charity sector has important social implications. Numerous studies have analysed whether the concentration of income in a few sources increases financial vulnerability. However, few studies have systematically consider... Read More about Financial resilience, income dependence and organisational survival in UK charities.

Using ASHE to examine trends in low pay: Initial exploration of the data (2020)
Report
Bryson, A., Phan, V., Stokes, L., Ritchie, F., Forth, J., McKenzie, A., & Whittard, D. (in press). Using ASHE to examine trends in low pay: Initial exploration of the data. Bristol: Low Pay Commission

Using the Annual Survey of Hours and Earnings (ASHE) 2004-2019 we report consistent time-series estimates of the percentage of jobs on and around the minimum wage; low paid jobs above the minimum; and ‘high paid’ jobs. In doing so we report on some i... Read More about Using ASHE to examine trends in low pay: Initial exploration of the data.

Runners, repeaters, strangers and aliens: Operationalising efficient output disclosure control (2020)
Journal Article
Alves, K., & Ritchie, F. (2020). Runners, repeaters, strangers and aliens: Operationalising efficient output disclosure control. Statistical Journal of the IAOS, 36(4), 1281-1293. https://doi.org/10.3233/SJI-200661

Statistical agencies and other government bodies increasingly use secure remote research facilities to provide access to sensitive data for research and analysis by internal staff and third parties. Such facilities depend on human intervention to ens... Read More about Runners, repeaters, strangers and aliens: Operationalising efficient output disclosure control.

Frameworks, principles and accreditation in modern data management (2020)
Working Paper
Ritchie, F., & Green, E. Frameworks, principles and accreditation in modern data management

The Five Safes framework is increasingly widely used for data governance. Since its conception in 2003, it has influenced data management in many ways, particularly in the public sector. As it has become established, both the advantages and limitatio... Read More about Frameworks, principles and accreditation in modern data management.

User-focused threat identification for anonymised microdata (2019)
Journal Article
Ritchie, F., Hafner, H., & Lenz, R. (2019). User-focused threat identification for anonymised microdata. Statistical Journal of the IAOS, 35(4), 703-713. https://doi.org/10.3233/SJI-190506

© 2019 - IOS Press and the authors. When producing anonymised microdata for research, national statistics institutes (NSIs) identify a number of 'risk scenarios' of how intruders might seek to attack a confidential dataset. This approach has been cri... Read More about User-focused threat identification for anonymised microdata.

The five safes of risk-based anonymization (2019)
Journal Article
Arbuckle, L., & Ritchie, F. (2019). The five safes of risk-based anonymization. IEEE Security and Privacy Magazine, 17(5), 84-89. https://doi.org/10.1109/MSEC.2019.2929282

The sharing of data for the purposes of data analysis and research can have many benefits. At the same time, concerns and controversies about data ownership and data privacy elicit significant debate. So how do we utilize data in a way that protects... Read More about The five safes of risk-based anonymization.

Analyzing the disclosure risk of regression coefficients (2019)
Journal Article
Ritchie, F. (2019). Analyzing the disclosure risk of regression coefficients. Transactions on data privacy, 12(2), 145-173

A major growth area in social science research this century has been access to highly sensitive confidential microdata, often via restricted-access remote facilities. These allow researchers highly unlimited access to manipulate the data but with che... Read More about Analyzing the disclosure risk of regression coefficients.

Confidentiality and linked data (2018)
Book Chapter
Ritchie, F., & Smith, J. Confidentiality and linked data. In G. Roarson (Ed.), Privacy and Data Confidentiality Methods – a National Statistician’s Quality Review, 1-34. Office for National Statistics

This chapter considers the confidentiality issues around linked data. It notes that the use and availability of secondary (adminstrative or social media) data, allied to powerful processing and machine learning techniques, in theory means that re-ide... Read More about Confidentiality and linked data.

Spontaneous recognition: An unneccessary control on data access? (2017)
Book Chapter
Ritchie, F. (2017). Spontaneous recognition: An unneccessary control on data access?. In G. Sandor, Z. Vereczkei, J. Poggi, P. Nymand-Andersen, A. Manninen, M. Karlberg, …C. Boldsen (Eds.), Selected papers from the 2016 Conference of European Statistics Stakeholders, 148-158. Publications Office of the European Union. https://doi.org/10.2785/091435

Social scientists increasingly expect to have access to detailed source microdata for research purposes. As the level of detail increases, data owners worry about ‘spontaneous recognition’, the likelihood that a microdata user believes that he or she... Read More about Spontaneous recognition: An unneccessary control on data access?.

Open data: Who needs it? (2017)
Presentation / Conference
Ritchie, F. (2017, September). Open data: Who needs it?. Presented at UNECE/Eurostat work session on statistical data confidentiality - 2017

This presentation, to introduce and stimulate a panel discussion, argued that we have 50 years worth of experience in knowing how to use data safely for researcher; as such we should be concentrating on practical management problems not theory: "how-... Read More about Open data: Who needs it?.

Lessons learned in training ‘safe users’ of confidential data (2017)
Presentation / Conference
Ritchie, F., Green, E., Newman, J., & Parker, T. (2017, September). Lessons learned in training ‘safe users’ of confidential data. Paper presented at UNECE/Eurostat work session on statistical data confidentiality - 2017

Many statistical organisations require researchers using detailed sensitive data to undergo ‘safe researcher’ training. Such training has traditionally reflected the ‘policing’ model of data protection. This mirrors the defensive stance often adopted... Read More about Lessons learned in training ‘safe users’ of confidential data.

The "Five Safes": A framework for planning, designing and evaluating data access solutions (2017)
Presentation / Conference
Ritchie, F. (2017, September). The "Five Safes": A framework for planning, designing and evaluating data access solutions. Paper presented at Data for Policy 2017, London, UK

The ‘Five Safes’ is a popular way to structure thinking about data access solutions. Originally used mainly by statistical agencies and social science academics , in recent years it has been adopted more widely across government, health organisations... Read More about The "Five Safes": A framework for planning, designing and evaluating data access solutions.

Spontaneous recognition: An unnecessary control on data access? (2017)
Journal Article
Ritchie, F. (2017). Spontaneous recognition: An unnecessary control on data access?. https://doi.org/10.2866/430525

Social scientists increasingly expect to have access to detailed data for research purposes. As the level of detail increases, data providers worry about “spontaneous recognition”, the likelihood that a microdata user believes that he or she has acci... Read More about Spontaneous recognition: An unnecessary control on data access?.

Ensuring the confidentiality of statistical outputs from the ADRN (2017)
Report
from the ADRN

This technical report discusses potential risks to confidentiality from publication of statistical results based on confidential data, and what we can do to minimise that risk while still ensuring that useful research gets published.

Measuring compliance with minimum wages (2017)
Journal Article
Ritchie, F., Veliziotis, M., Drew, H., & Whittard, D. (2017). Measuring compliance with minimum wages. Journal of Economic and Social Measurement, 42(3-4), 249-270. https://doi.org/10.3233/JEM-180448

© 2017 - IOS Press and the authors. All rights reserved. Identifying genuine underpayment of minimum wages is not straightforward. Some well-known statistical issues affect the measurement of compliance rates, but factors such as processing or behavi... Read More about Measuring compliance with minimum wages.

Improving data quality: The value of the user as data detective (2016)
Presentation / Conference
Ritchie, F. (2016, October). Improving data quality: The value of the user as data detective. Presented at Conference of European Statistics Stakeholders

In this presentation, we explore how users can contribute to a better understanding of data quality. We illustrate, with reference to minimum wage compliance, how users identify the sort of data problems missed by NSIs