CONCERNS ON THE NATIONAL DATA SHARING POLICY

The National Data Sharing Policy may raise several concerns related to privacy, security, and ethical implications. These issues need to be adequately addressed to ensure cooperation and participation from all parties. Among the 7 most significant issues that I've identified are :

1) Privacy Risks - Sharing national data can compromise individual privacy if not handled securely. Sensitive information might be exposed, leading to potential misuse or unauthorized access.

Implementing data sharing is like opening the floodgates to a wide range of potential threats, such as hacking or malware. The more people who have access to the data, the more opportunities there are for unauthorized parties to access it. (Castordoc)

2) Security Breaches - Data sharing introduces the risk of security breaches. If not adequately protected, shared data can fall into the wrong hands, leading to identity theft, fraud, or other malicious activities.

These are all common types of security breach or incidents. For example, a lost laptop, mobile phone, or external hard drive that is unlocked can easily direct to data being stolen if it ends up in the wrong hands. Also, a locked device could be hacked into by a sophisticated attacker (Knowledge Hut)

3) Ethical Considerations - There are ethical dilemmas regarding consent, transparency, and the fair use of shared data. Ensuring data is used responsibly and ethically can be challenging.

Data protection is an ethical issue. It involves respect for individuals and their rights regarding privacy and the use of information about them. External funders, particularly the EU, are seeking increasing levels of assurance with regard to data protection and ethics. (University of Edinburg)

4) Data Accuracy and Quality - Shared data might not always be accurate or up-to-date. This can lead to decisions based on flawed information, impacting policy-making and public services.

There are six main dimensions of data quality: accuracy, completeness, consistency, validity, uniqueness, and timeliness. (Heavy AI)

5) Regulatory Compliance - Complying with various regional or international data protection regulations adds complexity. Different jurisdictions might have conflicting requirements, making it challenging to streamline data sharing processes.

Regulatory data protection (RDP) is an intellectual property right available for a limited duration which protects an innovator's proprietary safety and efficacy data for its innovative product (Merck)

6) Data Monetization and Control - There's a concern about how shared data might be monetized or used for commercial purposes without proper consent or benefit sharing for the individuals whose data is being shared.

With data monetization, personal information is often collected without explicit permission from users. This raises ethical questions about who owns the data and whether individuals have control over how it is used. Another drawback is the risk of data breaches or misuse (The Cable)

7) Public Trust and Perception - Mishandling of data can erode public trust in government institutions or organizations responsible for data sharing, leading to reluctance in participating in future data-sharing initiatives.

Findings suggested that public's trust may not meet the needs of of the policy. There is a majority of the public having lack of trust on the organizations having information and share it on multiple platforms. This requires a new module to gain public trust via knowledge, attitudes, and beliefs to inform policies and practices for data sharing.

Addressing the abovementioned concerns requires robust data protection frameworks, strong encryption, clear policies for consent and usage, regular audits, and a commitment to transparency to maintain trust and safeguard individual rights.