Ethics and Privacy in Open
Data Usage
Navigating the opportunities and challenges of open data
responsibly. Emphasizing ethical considerations and privacy
protection in data utilization.
by Gde Adi Widya Utama
Defining Open Data vs. Personal Data
Open Data
Freely available for anyone to use and redistribute
without restrictions. Examples: NYC Open Data portal,
World Bank Open Data.
Personal Data
Information relating to an identified or identifiable
natural person. Protected by privacy regulations like
GDPR.
Key Differences: Anonymity, consent, purpose limitation. Open data should ideally be anonymized.
Risks of Open Data Misuse
1 Re-identification
Combining open datasets to identify individuals, even if data is
anonymized.
2 Discrimination
Using open data to unfairly target or exclude certain groups.
3 Surveillance
Tracking individuals' behavior using aggregated open data.
4 Data Bias Amplification
Open data reflecting existing biases can lead to skewed or unfair
outcomes.
Ethical Principles for Data
Management
Transparency
Clearly
communicate how
data is collected,
used, and shared.
Fairness
Ensure data usage
does not
discriminate or
create unjust
outcomes.
Accountability
Take responsibility
for data practices
and address any
harm caused.
Privacy by Design: Incorporate privacy safeguards into data
projects from the outset. Collect and use only the data that is
necessary. Strive to do good and avoid harm.
Relevant Regulations: GDPR
and Data Protection Laws
GDPR
EU law regulating the processing
of personal data. Applies to any
organization processing data of
EU citizens.
CCPA
US state law granting California
residents rights over their
personal data.
National Laws
Brazil's LGPD, India's proposed Data Protection Bill. Focus on data
localization and consent.
Awareness of these regulations is critical to ensure no violations occur
through re-identification or combination with personal data.
Case Study: Ethical Data
Breach Example
Cambridge Analytica
Misuse of Facebook user data obtained through a
personality quiz. Affected 87 million users.
Lessons Learned
Importance of data governance, user consent, and
third-party oversight.
Strava Fitness Tracking
Revealing sensitive military base locations due to
aggregated user activity data.
Managing Open Data Ethically
1
Anonymization Techniques
Implement robust techniques to protect privacy.
2 Data Governance Policies
Establish clear guidelines for data access, usage, and sharing.
3
Regular Audits
Ensure compliance with ethical principles and regulations.
4 Training and Awareness
Educate employees and stakeholders about data ethics and privacy.
Evaluate the potential ethical and privacy implications of data projects before implementation.
Conclusion: Responsible
Data Stewardship
Open data offers significant benefits, but requires careful ethical
consideration. By embracing ethical principles and adhering to
regulations, we can unlock the power of open data while
protecting privacy and fostering trust.
Emphasizing transparency, accountability, and a commitment to
responsible data management.

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Ethics-and-Privacy-in-Open-Data-Usage.pptx

  • 1. Ethics and Privacy in Open Data Usage Navigating the opportunities and challenges of open data responsibly. Emphasizing ethical considerations and privacy protection in data utilization. by Gde Adi Widya Utama
  • 2. Defining Open Data vs. Personal Data Open Data Freely available for anyone to use and redistribute without restrictions. Examples: NYC Open Data portal, World Bank Open Data. Personal Data Information relating to an identified or identifiable natural person. Protected by privacy regulations like GDPR. Key Differences: Anonymity, consent, purpose limitation. Open data should ideally be anonymized.
  • 3. Risks of Open Data Misuse 1 Re-identification Combining open datasets to identify individuals, even if data is anonymized. 2 Discrimination Using open data to unfairly target or exclude certain groups. 3 Surveillance Tracking individuals' behavior using aggregated open data. 4 Data Bias Amplification Open data reflecting existing biases can lead to skewed or unfair outcomes.
  • 4. Ethical Principles for Data Management Transparency Clearly communicate how data is collected, used, and shared. Fairness Ensure data usage does not discriminate or create unjust outcomes. Accountability Take responsibility for data practices and address any harm caused. Privacy by Design: Incorporate privacy safeguards into data projects from the outset. Collect and use only the data that is necessary. Strive to do good and avoid harm.
  • 5. Relevant Regulations: GDPR and Data Protection Laws GDPR EU law regulating the processing of personal data. Applies to any organization processing data of EU citizens. CCPA US state law granting California residents rights over their personal data. National Laws Brazil's LGPD, India's proposed Data Protection Bill. Focus on data localization and consent. Awareness of these regulations is critical to ensure no violations occur through re-identification or combination with personal data.
  • 6. Case Study: Ethical Data Breach Example Cambridge Analytica Misuse of Facebook user data obtained through a personality quiz. Affected 87 million users. Lessons Learned Importance of data governance, user consent, and third-party oversight. Strava Fitness Tracking Revealing sensitive military base locations due to aggregated user activity data.
  • 7. Managing Open Data Ethically 1 Anonymization Techniques Implement robust techniques to protect privacy. 2 Data Governance Policies Establish clear guidelines for data access, usage, and sharing. 3 Regular Audits Ensure compliance with ethical principles and regulations. 4 Training and Awareness Educate employees and stakeholders about data ethics and privacy. Evaluate the potential ethical and privacy implications of data projects before implementation.
  • 8. Conclusion: Responsible Data Stewardship Open data offers significant benefits, but requires careful ethical consideration. By embracing ethical principles and adhering to regulations, we can unlock the power of open data while protecting privacy and fostering trust. Emphasizing transparency, accountability, and a commitment to responsible data management.