Libraries, privacy, and the right to be forgotten

On May 25th, 2018, the EU General Data Protection Regulation (GDPR) came into force. Recognised as a comprehensive regulation for improving privacy and data protection, a substantial impact on data processing disciplines such as Serious Games (SG) research was expected.By conducting a scoping review, this paper explores the effects of GDPR on reporting of ethics approval, informed consent, ethics guidelines and data protection in SG studies. Five scientific databases were searched for research between 2016 and 2020 addressing Serious Games, Exergames and Applied Games. A total of 2146 full-text studies split into equal collections before and after GDPR were included. Lexicometric and keyword-in-context analysis were conducted and comparatively evaluated regarding ethics reporting and trends.Results unexpectedly show that GDPR so far hardly left a mark. While a slight increase of 12% in general ethics reporting can be observed, less than 6% of the studies after GDPR coming-into-force report on data protection. Ethics procedures remained consistent with most researchers reporting the approval from their home university committee and stating the Declaration of Helsinki as followed guidelines. Overall, the verifiable impact of GDPR was found negligibly small, with only 0.5% of studies referring to the regulation in the two years after introduction. Conclusively, further research is suggested to focus on integrating ethics and data protection guided on GDPR from an early conceptual stage to the reporting of the findings.

Compensation for Breach of the General Data Protection Regulation

The General Data Protection Regulation (GDPR), enacted in the European Union in 2018, has significantly transformed the landscape of personal data management and protection. This article provides an overview of GDPR's impact, focusing on its applicability, fundamental principles and influence on data management practices, particularly within the European Society of Thoracic Surgeons (ESTS) database. GDPR's reach extends to all entities collecting and processing personal data of European Union residents, regardless of their location. It encompasses various data types, emphasizing meticulous handling and protection of identifiable information. Special categories of data, such as health and sensitive attributes, require even more stringent protection. The regulation sets legal, fair and transparent data processing principles, emphasizing accuracy, purpose limitation and data minimization. It also stresses accountability, leading to the appointment of Data Protection Officers and significant penalties for non-compliance. The ESTS database, designed to enhance thoracic surgical research and care, collects data on European procedures. It follows GDPR principles by pseudonymizing data, ensuring secure data transmission and providing clear instructions for data submission. The database contributes to research, policymaking and practice improvement in thoracic surgery by offering a comprehensive dataset for analysis. Here, we aim to shed light on the complexities of GDPR implementation and emphasize the need for comprehensive data management strategies to ensure compliance and enhance privacy protection with the contribution to the ESTS database. GDPR compliance comes with challenges, including potential human dignity and privacy rights violations. Data breaches can result in unauthorized disclosures, and non-compliance can lead to substantial fines and reputational damage. The implementation of GDPR encourages organizations to prioritize ethical data practices, security measures and transparent data handling. In conclusion, GDPR has revolutionized personal data protection by emphasizing accountability, transparency and individual rights. It has impacted organizations globally, promoting responsible data management practices. Adhering to GDPR ensures privacy protection, trust-building and overall enhancement of data management in today's data-driven environment.

EU General Data Protection Regulation: Changes and implications for personal data collecting companies

Regulating Privacy Online: The Early Impact of the GDPR on European Web Traffic & E-Commerce Outcomes

The Interplay Between the NIS Directive and the GDPR in a Cybersecurity Threat Landscape

In recent years, along with the blooming of Machine Learning (ML)-based applications and services, ensuring data privacy and security have become a critical obligation. ML-based service providers not only confront with difficulties in collecting and managing data across heterogeneous sources but also challenges of complying with rigorous data protection regulations such as EU/UK General Data Protection Regulation (GDPR). Furthermore, conventional centralised ML approaches have always come with long-standing privacy risks to personal data leakage, misuse, and abuse. Federated learning (FL) has emerged as a prospective solution that facilitates distributed collaborative learning without disclosing original training data. Unfortunately, retaining data and computation on-device as in FL are not sufficient for privacy-guarantee because model parameters exchanged among participants conceal sensitive information that can be exploited in privacy attacks. Consequently, FL-based systems are not naturally compliant with the GDPR. This article is dedicated to surveying of state-of-the-art privacy-preservation techniques in FL in relations with GDPR requirements. Furthermore, insights into the existing challenges are examined along with the prospective approaches following the GDPR regulatory guidelines that FL-based systems shall implement to fully comply with the GDPR.

BackgroundIrish Health Research Regulations (HRRs) were introduced following the commencement of the General Data Protection Regulation (GDPR) in 2018. The HRRs set out supplementary regulatory requirements for research. A legal analysis presented under the auspices of the Irish Academy of Medical Sciences (IAMS) on April 8 and November 25, 2019 at the Royal College of Surgeons in Ireland welcomed the introduction of GDPR and the HRRs. The analysis found the GDPR “explicit consent” introduced by the HRRs is problematic. A call was made to regulate informed consent in line with the common law as an achievable alternative safeguard, bringing Ireland in line with other EU Member States.AimsThis article aims to review academic papers, legal opinion, EU opinion and advice and data protection law in relation to research and explicit consent, in order to examine the legal burden of GDPR and the HRRs on health research in Ireland and to determine whether the analysis presented at the IAMS meetings is reflected more widely in legal text.MethodsLegal literature review of academic papers, legal opinion, EU opinion and advice and data protection legislation.ResultsThe legal literature review overwhelmingly supports the concerns raised.ConclusionsOur results confirm the GDPR explicit consent requirement of the HRRs is having had a significantly negative and far-reaching impact on the conduct of health research in Ireland. Urgent review of the HRRs and meaningful engagement between the health research community and legislators in healthcare is required.

The Platform Work Directive (PWD) was adopted at the end of 2024. It contains a chapter on algorithmic management, covering topics which were already regulated by the General Data Protection Regulation (GDPR). However, the GDPR is said to lack practical effectiveness when applied in the employment context, which made it necessary that new, more specific legislation was adopted. In this paper, I consider the question to what extent the PWD is better positioned than the GDPR to address employment issues in light of the worker’s right to data protection. I study the four topics which are regulated or touched upon in the algorithmic management chapter of the PWD, namely limits to data processing, automated decision-making, transparency, and Data Protection Impact Assessments (DPIAs). For each topic, I describe how both the GDPR and the PWD regulate them, and what level of protection for the worker’s right to data protection they offer. I conclude that the PWD generally constitutes an improvement for the worker’s right to data protection, as it complements and clarifies multiple issues raised by the GDPR in the context of employment. On the other hand, some issues and unclarities remain to exist, mostly looking at the legal ground for data processing requirement and transparency.

Purpose This article aims to examine the tension between freedom of expression and personal data protection, focusing on criminal conviction and offence data under the General Data Protection Regulation (GDPR). It analyses how legal frameworks, particularly Article 85 of the GDPR, attempt to reconcile public access to information with individual data privacy rights harmoniously. Design/methodology/approach Using a legal doctrinal approach primarily, this study examines GDPR provisions, especially Article 85, alongside relevant case law. The principle of proportionality serves as a key analytical tool to assess the necessity and justification of legal restrictions on data processing. Findings The research underscores the delicate balance between freedom of expression and data protection concerning criminal records. Article 85 plays a crucial role in establishing journalistic exemptions while ensuring data privacy. The principle of proportionality is vital in preventing disproportionate restrictions, requiring case-by-case evaluations. The study highlights the evolving nature of privacy-publicity conflicts, with the right to be forgotten serving as a safeguard against undue harm from outdated or minor convictions. Research limitations/implications This study has limitations, including its reliance on case-specific analyses, which overlook the broader impacts of the evolving digital media landscape, particularly social media and user-generated content. The focus on European legal frameworks (e.g. GDPR) restricts generalisability to non-EU jurisdictions with differing standards. Additionally, the analysis emphasises journalistic exemptions, neglecting other forms of expression – such as academic, artistic and literary – that also require balancing against personal data protection rights. Practical implications The research provides practical guidance for balancing data protection and freedom of expression, particularly under GDPR Article 85. It underscores the need for case-by-case assessments, ensuring proportionality and necessity when handling criminal conviction data. Policymakers and legal practitioners can use these insights to refine journalistic exemptions and prevent data misuse, especially in digital media contexts. Organisations, including media platforms, are encouraged to adopt responsible data-handling practices to safeguard privacy while enabling public interest reporting. Finally, the findings stress the importance of dynamic frameworks that adapt to evolving societal and technological contexts, supporting fair outcomes for both data protection and expression rights. Social implications This research highlights the delicate balance between individual data protection rights and freedom of expression, particularly regarding criminal conviction data. Its implications extend to societal concerns over data privacy, the potential misuse of personal information and the long-term impact on individuals, especially those with minor or outdated offences. As digital media evolves, these issues become more pressing, with the rise of social media and user-generated content complicating the legal landscape. Ensuring that privacy is upheld without stifling public access to essential information is crucial for maintaining both rights and societal transparency in an increasingly interconnected world. Originality/value This study enriches the debate on data protection and freedom of expression in crime-related data processing. By addressing journalistic exemptions and the evolving media landscape, it provides a nuanced perspective on safeguarding privacy while maintaining transparency in an era of digital accessibility.

IT providers offering services based on genetic data face serious challenges in managing health data in compliance with the General Data Protection Regulation (GDPR). Based on a literature research and our experiences, an overview of GDPR compliant processing of sensitive data is given. The GDPR requirements for processing sensitive data were specified for a use case concerning a service provider of a pharmacogenomic decision support system. Start-ups who want to enter into the health market also have to comply with the Medical Device Regulation (MDR). The associated efforts for legal compliance constitute an impediment for many start-ups. We created a comprehensive overview, which aligned the requirements of the GDPR with the life-cycle of a medical device. This overview shall help start-ups to grasp and overcome the regulatory hurdles faster.

This chapter presents a critical analysis of the efficacy of the General Data Protection Regulation (GDPR) as a framework for the protection of genetic privacy in biobanking. In this regard, it outlines twenty-three problems concerning the standard of protection offered by the GDPR, assessing the degree to which each problem casts doubt on the efficacy of the GDPR. The chapter considers whether there are factors evident which are likely to mitigate the severity of the impact of each problem, as well as whether each problem is subject to resolution——either through the GDPR's internal interpretation and adaptation mechanisms or through external legislation operating in tandem with the GDPR. The analysis demonstrates that the great majority of problems are not as severe as they initially seem and, as a result, do not call into question the efficacy of the GDPR as a framework for the protection of genetic privacy in biobanking. It also shows that all problems which either require a solution, or would benefit from a solution, can be resolved via the GDPR's internal mechanisms or via external law operating in parallel with the GDPR, or both.

The European Union's general data protection regulation (GDPR) came into effect in May 2018. It is intended to prevent the unwanted sharing of private data and it has significant implications for healthcare research. A well-established research methodology that GDPR is likely to affect is the retrospective reviewing of patients' data. This has been used widely in healthcare research and commonly involves examining patients' medical records. To examine GDPR and its potential effects on the use of patients' data in healthcare research. Previous misuse of patients' data has affected public confidence in healthcare research. GDPR is intended to improve the public's confidence in the handling of their data, but it may negatively impact healthcare research. Researchers who want to review patients' data will need to consider consent issues carefully. GDPR does include exceptions to the rules of consent, but there is uncertainty about this process. If GDPR results in stricter requirements to achieve patients' consent in research, the validity of some studies may be affected. Nurse researchers and organisations may need to consider innovative ways of engaging patients in research. Research using patients' data has played an important role in shaping nursing and healthcare policy and practice. Imminent Europe-wide changes prompted by GDPR could affect how patients' data are used in research.

After the European Union's new General Data Protection Regulation (GDPR) became applicable in May 2018, concerns about the legal compliance of public blockchain systems with rights guaranteed by GDPR have emerged, e.g., on the right to be forgotten. In order to better understand how the blockchain sector sees the challenges raised by GDPR and how such their communications could influence their users, this paper reports our data-driven analysis of GDPR-related public online communications of blockchain developers and service providers. Our analysis covers 314 public blockchain systems, and two different online communication channels: legal documents in-cluding privacy policies, T&C (Terms and Conditions) documents and other similar legal documents published on systems' official websites and public tweets of their official Twitter accounts. Our analysis revealed that only a minority (86/314 ≈ 27.5%) of the investigated blockchain systems had covered GDPR at least once using one or both communication channels. Among the 86 systems, only 27 systems (8.6%) had at least one legal document that actually talks about GDPR for the corresponding blockchain system. We noticed a systematic lack of detail about why and how the GDPR compliance issue was addressed, and most systems made questionable statements about GDPR compliance. The results are surprising considering that the GDPR was enacted in 2016 and has been in effect since May 2018.

The General Data Protection Regulation (GDPR) harmonizes data privacy laws and regulations across Europe. Through the GDPR, individuals are able to better control their personal data in the face of new technological developments. While the GDPR is highly advantageous to individuals, complying with it poses major challenges for organizations that control or process personal data. Since no automated solution with broad industrial applicability currently exists for GDPR compliance checking, organizations have no choice but to perform costly manual audits to ensure compliance. In this paper, we share our experience building a UML representation of the GDPR as a first step towards the development of future automated methods for assessing compliance with the GDPR. Given that a concrete implementation of the GDPR is affected by the national laws of the EU member states, GDPR's expanding body of case law and other contextual information, we propose a two-tiered representation of the GDPR: a generic tier and a specialized tier. The generic tier captures the concepts and principles of the GDPR that apply to all contexts, whereas the specialized tier describes a specific tailoring of the generic tier to a given context, including the contextual variations that may impact the interpretation and application of the GDPR. We further present the challenges we faced in our modeling endeavor, the lessons we learned from it, and future directions for research.