Data Ethics and Ownership
- Video: Data Ethics Video
- Data Ethics Video
Data science is revolutionising how health, social and care services are delivered. However, the use of service user data in health and social care is not free from ethical challenges. Different ethical issues might emerge depending on how data are collected, analysed, stored, shared and used and depending on who gets to make these decisions. Understanding how to identify ethical challenges and knowing how to make ethical decisions is key in any health and care setting. Given the increasing and continued role of data science in these contexts, as well as the high stakes involved in data use, it is extremely important that those working in data science are able to recognize and resolve ethical dilemmas and that they can embed ethical approaches within their own data practices.
Through a combination of independent learning, online activities, guest seminars and written assessments, this course will introduce you to some of the key principles, concepts and debates relating to data ethics in health social and care contexts. You will be supported in developing the skills to identify different ethical issues, to engage in ethical debates and to reach ethically defensible judgements. We will consider different rights and responsibilities emerging out of data use. Together we will reflect on some of the key debates and controversies that exist around data use and we will draw on different case studies and examples from across health, social and care settings. We will explore some of the concrete ways that we can translate ethical principles such as fairness or transparency into practice as well as how to include publics in decisions about data. The course will prompt active self-reflection and appraisal and provide students with an opportunity to give and receive constructive feedback. Students taking this course do not need to have any prior exposure to data ethics.
Further information can be found in the University's course catalogue:
Anyone working in health or social care or with computational roles who are interested in starting a career in data science or graduates who are seeking to develop data science skills that can be applied in health, social and care services
This is an introductory Masters-level course (SCQF Level 11). It provides foundational skills and/or an overview of the subject – no prior knowledge is needed. Masters-level courses are relatively intensive and require independent learning, critical thinking, analysis and reflection.
Entry Requirements
As this course is designed mainly for health and care professionals, we expect our students to have qualifications or work experience in such environments (e.g. NHS National Services, Acute/Community/Public health), third sector organisations, social services, nursing homes, pharmaceutical companies, diagnostic laboratories, etc.).
You should be educated to a degree level as this course is catering for those seeking postgraduate academic credit. However, professionals who are involved with managing services and caseloads and have 5 years of work experience may also apply even if they do not hold a degree qualification.
Check whether your international qualifications meet our general entry requirements:
English Language Requirements
You must be comfortable studying and learning in English if it is not your first language.
On completion of this course, the student will be able to:
- Demonstrate a critical understanding of ethical challenges and data ownership issues associated with the use of service user data in the health, social and care service context.
- Apply logical, analytical and problem-solving skills to identify and assess current ethical challenges and data ownership issues to make informed decisions when addressing these within the health, social and care services sectors.
- Apply professional critical judgement and demonstrate the ability to effectively communicate about data ethics issues.
| Start Date: |
17 January 2022 |
| Course Duration: | 5 weeks |
| Total Hours: | 100 ( Lecture Hours 5, Seminar/Tutorial Hours 1, Online Activities 35, Feedback/Feedforward Hours 5, Formative Assessment Hours 5, Revision Session Hours 1, Programme Level Learning and Teaching Hours 2, Directed Learning and Independent Learning Hours 46 ) |
| Method of Assessment: | Coursework 100% |
| Level: |
This is an intermediate Masters-level course (SCQF Level 11). It develops your skills and/or provides a broad understanding of the subject in some detail - some foundational knowledge is required. Please see the entry requirements for further details. Masters-level courses are relatively intensive and require independent learning, critical thinking, analysis and reflection. |
Course fees for 21/22 are £960, but funded places are available for people employed, unemployed or furloughed in Scotland who meet Scottish Funding Council elgibility criteria.
Funding
Through the Scottish Funding Council (SFC) Upskilling Fund and National Transition Training Fund, a number of fully-funded places are available at The University of Edinburgh on short, standalone courses from the Data Skills Workforce Development Training portfolio.
Eligibility
Funded places are available to those who meet Scottish Funding Council (SFC) fee waiver criteria. Note that course places are limited and priority will be given to those who meet the criteria for SFC-funded places.
Determining eligibility for a funded place for upskilling takes a number of things into account, including fee status, but also location of employer. SFC provide guidance specifically for upskilling courses:
“Courses/provision is open to all Scottish-domiciled/’home fee’ students, which is consistent with SFC’s policy for core funded student places. Students from the rest of the UK (rUK) are not normally considered eligible for SFC funding. If however a university is working with a Scottish/UK employer which has a physical presence or operating in Scotland, rUK employees of that employer would be eligible.”
Organisations like UKCISA, and the University, provide guidance on how to determine your fee status:
- Information on current fee status regulations for studying in Scotland is available here: https://ukcisa.org.uk/Information--Advice/Fees-and-Money/Scotland-fee-status-for-students-starting-from-August-2021.
- You can check your likely fee status here: https://www.ed.ac.uk/tuition-fees/fee-status/work-out
If your fee status is Scotland Fee Rate, RUK Fee Rate, or EU-EEA Pre/Settled Scotland Fee rate, you may be eligible for a funded upskilling place. To determine this we will look at your fee status, residency information and, where relevant, details of your employer, to confirm whether the employer is based in, or has a significant presence, in Scotland.
Funding eligibility will be assessed at the point of each application for each course; you may be asked to provide further information if you do not meet the general residence conditions. Please email us at bayes-training@ed.ac.uk if you would like to discuss your funding eligibility before applying.
Please note that full-time students (including full-time PhD students) are not eligible for funding.
Funding eligibility criteria for the National Transitition Training Fund in the 2021/22 session is still to be confirmed.
How to Apply
Courses are now being updated for the 2021/22 academic year.
Each course will have a distinct start date which will be updated on the Schedule of Courses webpage and each Course page.
Application links will be available in each individual course webpage, which can be accessed from the Courses summary page. Details about entry requirements and any supporting documentation required can also be found on each page.
You can register your interest by joining our mailing list where courses do not have a live application form for this session.
If you have questions about the application process please contact:
You may find additional information in the FAQ section helpful as well:
Useful Links:
Learners who successfully complete and pass the assessed elements of the course will receive a certificate of completion and gain 10 academic credits at SCQF Level 11, from one of the top 20 universities in the world. All students who actively engage with learning (but may have chosen not to complete the assessments) will be entitled to receive a certificate of participation.
Applications for January 2022 are now closed. Please subscribe to our mailing list to be kept informed about course start dates and new courses.
This course is offered as part of Data Science for Health and Social Care, an innovative online programme looking to equip students with the data science skills, capabilities and competencies to realise the value of data in a healthcare setting. You can use credits achieved on this course towards postgraduate study on this programme (MSc, PG Diploma or PG Certificate), subject to approval by the Programme Director.
You may also be able to use credits achieved on this course towards other University of Edinburgh postgraduate programmes, subject to the approval of the relevant Programme Director:
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