FAIR data etc. Flashcards
What does the FAIR principle stand for, and why is it important in medical data sharing?
FAIR stands for Findable, Accessible, Interoperable, and Reusable. It ensures that medical and genetic data can be efficiently stored, retrieved, and analyzed by researchers while maintaining ethical and legal standards.
How does FAIR apply to patient data?
It ensures that patient data can be structured in a way that allows efficient searching (Findable), secure and controlled access (Accessible), compatibility with different data formats and systems (Interoperable), and long-term usability in research (Reusable).
What are the two levels at which genetic data is collected in Big Data studies?
1) Population-level data – Aggregated information such as SNP statistics, genetic variations across ethnic groups, and general human genome sequencing.
2) Person-level data – More specific data such as BRCA1/2 mutation status, full DNA sequences, or individualized genomic information.
What are some major ethical concerns in Big Data sharing?
Data leaks – Risk of unauthorized access or exposure of sensitive genetic information.
Privacy violations – Patients may not always be aware of how their data is used.
Informed consent – Changes in research goals may require re-consent from patients.
Legal uncertainties – Different countries have different regulations on genomic data.
What determines the suitability of Big Data approaches in biomedical research?
- Biological/medical question – The research goal influences which dataset is most relevant.
- Data type – Whether the data consists of genetic sequences, proteomics, clinical records, or population-level trends.
- Analytical tools – The availability of AI-driven analytics, machine learning, and bioinformatics pipelines.
What are the three main regulatory approaches to protecting medical data?
Human Rights – Ensuring dignity and privacy protection.
Privacy Protection – Laws that limit how personal medical data is collected and used.
Data Protection – Mechanisms such as encryption, anonymization, and GDPR laws to prevent misuse.
Why are Randomized Clinical Trials (RCTs) not always representative?
Selection bias – Participants in RCTs may not reflect the general population.
Geographical bias – Trials are often conducted where they are cheapest, which may exclude marginalized communities.
Lack of real-world data – RCTs are conducted under controlled conditions, which may not reflect actual patient experiences.
How can Real World Data (RWD) and Real World Evidence (RWE) improve representation?
RWD gathers information from electronic health records (EHRs), insurance claims, and wearable devices.
RWE helps track long-term effectiveness, side effects, and patient adherence beyond controlled clinical trials.
What is the General Data Protection Regulation (GDPR)?
GDPR is a European Union law (EU 2016/679) that regulates how personal data is collected, stored, and shared, ensuring strong privacy protections for individuals.
What are the key principles of data protection under GDPR Article 5?
1) Lawfulness, fairness, and transparency – Data must be processed legally, ethically, and with clear communication.
2) Purpose limitation – Data should only be used for specific, declared reasons.
3) Data minimization – Only necessary data should be collected and retained.
4) Accuracy – Data should be up-to-date and correct.
5) Storage limitation – Data should not be kept longer than necessary.
6) Integrity & confidentiality – Strong security measures should be in place.
Under Article 6 of the GDPR, what are the six lawful bases for processing personal data?
1) Informed Consent – The individual has given explicit permission after being informed.
2) Contract necessity – Required to fulfill a contract.
3) Legal obligation – Compliance with a legal requirement.
4) Vital interests – Necessary to protect someone’s life.
5) Public interest – Data use benefits society, such as public health research.
6) Legitimate interest – The data controller has a justified reason that does not override individual rights.
What does the GDPR’s “Right to be Forgotten” (Article 17) entail?
Individuals can request deletion of their personal data when:
- The data is no longer needed.
- Consent is withdrawn.
- The processing is unlawful.
What is the difference between privacy and confidentiality in data governance?
Privacy is about an individual’s right to control their data.
Confidentiality is about how the data is handled and protected once shared.
What are the arguments for and against treating medical data as property?
✅ For:
Individuals have ownership rights over their DNA and health records.
Patients should have control over how their data is used.
❌ Against:
Treating data as property may limit scientific collaboration.
Medical data is often interconnected (e.g., one person’s genetic data can reveal information about relatives).
How can a public interest approach solve privacy vs. utility conflicts in medical data use?
- Uses ethics-based regulation rather than absolute privacy laws.
- Focuses on minimizing harm while maximizing societal benefit.
- Encourages data altruism – individuals sharing data for medical advancement.
What ethical theories influence public interest data policies?
Utilitarianism – Maximizing overall benefit.
Rawls’ Veil of Ignorance – Ensuring fair treatment regardless of personal circumstances.
Kant’s Categorical Imperative – Acting in ways that respect human dignity universally.
What is the biggest challenge in balancing Big Data analytics with personal privacy?
Protecting individual rights while ensuring data is useful for biomedical research and public health applications.
Why are traditional anonymization techniques no longer sufficient for data privacy?
Advanced AI and cross-referencing techniques can re-identify individuals even in anonymized datasets.
How does GDPR regulate secondary use of medical data?
It requires explicit consent unless the data is processed for scientific, historical, or statistical research in the public interest.
Why is informed consent a complex issue in Big Data research?
Patients may not fully understand how their data will be used in future studies, raising ethical concerns.
