All Outputs (77)

Exploring the workplace location problem in the Annual Survey of Hours and Earnings (2022)
Working Paper
Whittard, D., Ritchie, F., Phan, V., Forth, J., Bryson, A., Stokes, L., …McKenzie, A. Exploring the workplace location problem in the Annual Survey of Hours and Earnings

The Annual Survey of Hours and Earnings (ASHE) is an important source of longitudinal linked employer-employee payroll earnings data for Britain. It provides accurate information on employees’ hours and earnings and information on the location of em... Read More about Exploring the workplace location problem in the Annual Survey of Hours and Earnings.

Statistical disclosure control for HESA: Part 1: Review of SDC theory (2021)
Report
Green, E., & Ritchie, F. (2021). Statistical disclosure control for HESA: Part 1: Review of SDC theory. Higher Education Statistics Agency (HESA)

This report for the Higher Education Statistics Agency (HESA) is a summary of statistical disclosure control (SDC) methods for tabular outputs.

Automatic Checking of Research Outputs (ACRO): A tool for dynamic disclosure checks (2021)
Journal Article
Green, E., Ritchie, F., & Smith, J. (2021). Automatic Checking of Research Outputs (ACRO): A tool for dynamic disclosure checks. ESS Statistical Working Papers, 2021 Edition, https://doi.org/10.2785/75954

This paper discusses the issues surrounding the creation of an automatic tool to reduce the burden of output checking in research environments. It describes ACRO (Automatic Checking of Research Outputs), a Stata tool written as a proof-of-concept, an... Read More about Automatic Checking of Research Outputs (ACRO): A tool for dynamic disclosure checks.

Statistical disclosure controls for machine learning models (2021)
Conference Proceeding
Krueger, S., Mansouri-Benssassi, E., Ritchie, F., & Smith, J. (2021). Statistical disclosure controls for machine learning models

Artificial Intelligence (AI) models are trained on large datasets. Where the training data is sensitive, the data holders need to consider risks posed by access to the training data and risks posed by the models that are released. The first problem c... Read More about Statistical disclosure controls for machine learning models.

The present and future of confidential microdata access: Post-workshop report (2021)
Presentation / Conference
Green, E., Ritchie, F., Tava, F., Ashford, W., & Ferrer Breda, P. (2021, July). The present and future of confidential microdata access: Post-workshop report. Presented at The Present and Future of Microdata Access

In the summer of 2021, the University of the West of England, in collaboration with UN Economic Commission for Europe, Eurostat, INXEDA and statistical organisations across the world, hosted a workshop to review lessons learnt in microdata access ove... Read More about The present and future of confidential microdata access: Post-workshop report.

The present and future of confidential microdata access [draft] (2021)
Presentation / Conference
Green, E., & Ritchie, F. (2021, July). The present and future of confidential microdata access [draft]. Presented at The Present and Future of Microdata Access

This briefing document was prepared for the DRAGoN conference 'The Present and Future of Microdata Access', 5th-9th July 2021. It provides an introduction to the topics to be covered in the conference.

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)
Journal Article
Whittard, D., Ritchie, F., & Nyengani, J. (2021). 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. Gates Open Research, 5, Article 97. https://doi.org/10.21955/gatesopenres.1116786.1

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.

Sequential mixed methods research: Non-compliance in apprentice pay with owls (2021)
Presentation / Conference
Drew, H., & Ritchie, F. (2021, June). Sequential mixed methods research: Non-compliance in apprentice pay with owls. Paper presented at 20th European Conference on Research Methodology for Business and Management Studies, University of Aveiro, Portugal

Within mixed methods literature, the relationship between qualitative and quantitative data collection is ubiquitously presented as sequential. Thus, the most followed approach is for the first stage of data collection to follow the second, or to run... Read More about Sequential mixed methods research: Non-compliance in apprentice pay with owls.

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

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. (2021). Financial resilience, income dependence and organisational survival in UK charities. Voluntas: International Journal of Voluntary and Nonprofit Organizations, 32, 992–1008. 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.

Understanding output checking (2020)
Report
Green, E., Ritchie, F., & Smith, J. (2020). Understanding output checking. Luxembourg: European Commission (Eurostat - Methodology Directorate)

This report for Eurostat (Methodology) considers the conceptual and practical issues that need to be addressed in designing and implementing automatic disclosure control checking for statistical research outputs. The report covers - The basic theo... Read More about Understanding output checking.

10 is the safest number that there’s ever been (2019)
Presentation / Conference
Ritchie, F. (2019, October). 10 is the safest number that there’s ever been. Paper presented at Workshop on statistical data confidentiality 2019, The Hague

When checking frequency and magnitude tables for disclosure risk, the cell threshold (the minimum number of observations in each cell) is the crucial statistic. In rules-based environments, this is a hard limit on what can or can’t be published. In p... Read More about 10 is the safest number that there’s ever been.

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.