Types Of Personal Data Research Articles

Young adults’ acceptance of data-driven personalized advertising: Privacy and Trust Equilibrium (PATE) model

Purpose This study aims to examine young social media users’ differential acceptance of data-driven ad personalization depending on the types of personal data used, and to propose and test the Privacy and Trust Equilibrium (PATE) model, a new conceptual model developed to explain the intertwined nature of the competing influences of platform-related factors (privacy concern, trust, and privacy fatigue) on acceptance of ad personalization. Design/methodology/approach A survey of 440 Instagram users aged 18–24 in Australia was conducted to examine the relationships between the three factors of the PATE model and acceptance of ad personalization utilizing overt vs covert data collection methods. Findings This study shows the highest level of acceptance for personalization using overtly collected data and the lowest for covert data. The results also support the PATE model, revealing the competing dynamics of how the platform-related factors shape consumers’ acceptance of data-driven ad personalization. Privacy concern discourages Instagram users from accepting personalized ads, while trust encourages them. When the pushing influence of privacy concern and the pulling influence of trust form equilibrium, generating cognitive dissonance, privacy fatigue seems to play a significant role in resolving the dissonance, leading to increased acceptance. Originality/value This study advances the understanding of how concurrent push–pull-resigning factors affect young consumers’ acceptance of data-driven ad personalization practices, expanding the scope of research on data-driven personalized advertising and privacy.

Are Certain Types of Microtargeting More Acceptable? Comparing US, German, and Dutch Citizens’ Attitudes

Much of the research on political microtargeting has focused on growing public concerns about its use in elections, fuelling calls for greater regulation or even a ban on the practice. We contend that a more nuanced understanding of public attitudes toward microtargeting is required before further regulation is considered. Drawing on advertising psychology research and the results of academic analyses into microtargeting, we argue that individual concern, and by corollary, acceptance of microtargeting will vary based on socio-demographic characteristics and political orientations, and the type of personal data used. We hypothesise that microtargeting that relies on observable or publicly accessible personal information will be more accepted by voters than that which uses unobserved and inferred traits. We test these expectations and the expected variance of public acceptance by individual characteristics using comparative survey data from the US, Germany, and the Netherlands. We find that across countries and socio-demographic groups, not all microtargeting is considered equally problematic. For example, whereas the use of age and gender is generally deemed acceptable, the use of sexual orientation is not, and right-leaning individuals are more accepting than those who lean left. Additionally, overall, the US is more accepting of microtargeting than Germany or the Netherlands. Thus, we find that not all microtargeting is considered equally problematic across countries and socio-demographic groups. We conclude by calling for a more contextualised debate about the benefits and costs of political microtargeting and its use of “sensitive” data before the expansion of current regulation.

Проблемы правовой защиты персональных данных по законодательству России и Китая

In the context of the functioning of the digital environment, information assets are becoming increasingly important, while the need to ensure the protection of personal non-property rights remains an unshakable constitutional guarantee. Artificial intelligence technologies used in many spheres of life gain access to various kinds of personal information, which in itself affects national, economic and political security, encroaches on social stability. The legislation of many countries, including Russia and China, contains provisions ensuring the legal protection of personal data. However, many problems remain unresolved, which requires further improvement of the legal regulation of the collection and processing of personal data, ensuring their legal protection by providing different legal regimes for certain types of personal data, and developing a modern model of information security control. The article contains a comparative legal analysis of the legislation on personal data of Russia and China, identifies problems of legal protection of personal data, and draws conclusions about the need for further improvement of legislation on personal data, which should contain guarantees of information security during automatic processing of personal data.

Threats and Legal Protection of Personal Data Combined in E-Commerce Transactions Based on Personal Data Protection Law in Indonesia

The dynamics of Indonesian trade are becoming more complex as time goes on, and one form of this development is digitalization. Although it has a positive impact, trade digitization also has a negative impact on different points of view, one of which is the threat in terms of combined personal data. Combined personal data is one type of personal data that is protected by the state through legal protection, so that the state guarantees people’s personal data. This scientific research uses one part of the grand method, namely Library Research which is based on literature or literature. The results of the research show that there are three forms of threats to people’s personal data combined in e-commerce transactions, especially in the use of IP Address, namely threats to geographic location tracking, unauthorized use and opening of personal data, and Distributed Denial of Service (DDoS) attacks. In the legal space in Indonesia, the three threats themselves do not yet have further rules related to the form and mechanism of protection and have different arrangements as a form of protection. Law Number 27 of 2023 concerning Personal Data Protection, Law Number 19 of 2016 amending Law Number 11 of 2008 concerning Electronic Information and Transactions, and Government Regulation of the Republic of Indonesia Number 71 of 2019 concerning the Implementation of Electronic Systems and Transactions. Based on this research, it is necessary to provide legal rules related to the form and mechanism of protecting a person’s IP Address as one type of personal data in Indonesia.

Handling of Personal Data by Smart Home Equipment: an Exploratory Analysis in the Context of LGPD

This paper presents an exploratory research that analyzed the Privacy and Security Policies and the Instruction Manuals of 59 home automation equipment for Smart Home in order to verify which personal data was handled and how these documents were providing information about processes performed in personal data. The analysis was conducted with a quantitative approach followed by a qualitative analysis, using content analysis. The surveys identified the following types of personal data: Identification, Financial, Devices and Location. The results presented greater interest in identification data, although financial and location are also used in specific cases. We also concluded that the Privacy and Security Policies present several information that meets the LGPD’s guidelines, especially regarding the purpose of using the data and which personal data is used. However, there is a visible lack of information about the benefits provided to data subjects and about sharing data with third parties, such as recipient data and the legal basis for sharing data.

Tell me something new: data subject rights applied to inferred data and profiles

The EU General Data Protection Regulation (GDPR) contains several data subject rights, but for many of these rights it is not entirely clear how they should work in practice, especially in digital environments. Most data subject rights apply to personal data obtained directly or indirectly from the data subject. This is often personal data that data subjects already are familiar with, i.e., things they already know about themselves. Unclear, however, is to what extent ascribed personal data, such as inferred data and categories or profiles in which data subjects are placed by data controllers, are within the scope of these rights. Such ascribed personal data often concerns novel information, generated by data controllers, and includes insights into how controllers view and assess them, which may have practical and legal impact on data subjects. Given these characteristics, the ascribed personal data may be much more interesting to data subjects, so it appears beneficial, from the policy perspective, to have this novel information included in the scope of data subject rights. If data subject rights do not apply to inferred data and profiles, invoking these rights is unlikely to be informative and provide meaningful information for data subjects, particularly in complex, digital environments. However, if data subject rights do apply to inferred data and profiles, the scope of these rights may be hard to delineate and they may quickly interfere with rights and freedoms of others, including trade secrets of data controllers and privacy rights of other data subjects. In this article, we investigate the implications of applying data subject rights to inferred data and profiles. For each data subject right in the GDPR, we assess which types of personal data could and perhaps should be in scope, based on grammatical and teleological legal analyses as well as practical considerations. While the area of data subject rights received significant academic attention in the past years, our article contributes to the discussion by providing a systematic, holistic framework to consider the scope of the rights in relation to ascribed data.

Harmonization of health protection legislation and personal data legislation as a basis for the development of personalized medicine

The article analyzes the health protection legislation and personal data legislation in terms of their impact on the implementation of personalized medicine in practice. It is concluded that since the development of personalized medicine is associated with the study of a person’s individual data, and first of all, his genetic data, the harmonization of legal provisions on medical activities and genetic information as a type of personal data takes on special significance. In relation to personalized medicine, the «head» law proposes to consolidate general provisions regarding the use of an individualized method, and in special laws to identify groups of norms that establish the specifics of using this method in carrying out a specific type (direction) of medical activity. As a final conclusion, the idea of the need to harmonize health protection legislation and legislation on genetic information as a type of personal data is substantiated, primarily in terms of the regime of genetic health information, as well as the features of their use in personalized medicine.

“Not Private at All:” Comparative Perspectives on Privacy of Genomic Data, Family History Data, Health-Related Data, and Other Personal Data

People choose how and if to generate and disclose not just personal genomic data, but also multiple other types of personal health and non-health related data. To contextualize choices about genetic testing and genetic data disclosure, we explored perspectives of genomic data privacy and disclosure compared to other types of data. We conducted a qualitative focus group study with adult members of an integrated U.S. health system, using administrative data to stratify our sample by age and by race/ethnicity. Discussion topics included qualities, rights, benefits and harms of disclosure of genomic, health, family history and non-health related data. We conducted thematic template analysis using verbatim transcripts. The sample (n = 24) was 67% female, mean age 54.1 years (range 23-88), and 37% people of color; 71% reported college degree. Participants considered genetic data, but not other data types, as a permanent, core part of the individual self and as protected health information under current laws. Participants did not feel that individuals had a right to family medical history disclosure from their relatives. Participants assumed high levels of privacy protections of genetic and other health-related data, but no perceived privacy or protection around other personal data. Participants weighed benefits and risks of generation and disclosure of all data types; harms were more far-reaching for non-health data, possibly related to the perceived lack of protections around these data. People make privacy-related choices about genetic testing in the context of related considerations for multiple types of data and rely on perceived privacy protections under current U.S. health privacy laws. Genetic research and screening programs should consider providing clear guidance on privacy protections afforded to genetic information in U.S. clinical settings. Future research should examine connections between privacy-related views on genetic and multiple other types of personal data.

IoT forensics: What kind of personal data can be found on discarded, recycled, or re-sold IoT devices

With the advancement in science and technology, the demand for electronic Internet of Things (IoT) devices has increased to store and process digital data. With the advancement in IoT technology, we are more reliant on IoT devices to perform our regular tasks. IoT Forensics deals with the investigation of IoT devices such as smartphones, tablets, smart watches, or any device which is connected to the Internet. The data on these devices can still be retrieved via IoT forensics even if they are destroyed, resold, or misplaced. Before discarding any IoT device, we must consider how to secure the data stored on them. We are then going to discuss the several types of personal data that could be retrieved from discarded IoT devices. Finally, we are going to discuss the protection measures for the safe disposal of IoT devices.

Mining the Data: Exploring Rural Patients’ Attitudes about the Use of Their Personal Information in Research

Background This study examines rural patients’ perceived importance of knowing or being consulted about researchers’ access and use of their personal data (identifiable and de-identified health information, and identifiable and de-identified non-health information) across five scenarios. This study also examines their views on stewardship or governance of their personal information by researchers in their healthcare systems. Methods We conducted a survey by mail. Data were analyzed using descriptive statistics. Multivariable regression analyses were conducted across each scenario and type of personal data with the same variables included in each model. Results The majority of participants said it was “very important/absolutely essential” to know the purpose of the study, to be asked every time, and to know the policies governing researcher access and use of their identifiable health information. Just over two-thirds of respondents thought it “very important/absolutely essential” to know who serves on the data governance committee and to have a community member serve. Distrust in healthcare organizations was positively correlated with the scenarios while willingness to give permission to donate leftover biological specimens was negatively correlated. Conclusion Our study findings indicate that the type of personal information being accessed and used generally matters to 1,407 patients living in rural Pennsylvania. We also demonstrate that knowing their healthcare organizations’ governance policies and practices for managing their personal data is important to many rural Pennsylvania patients. Biomedical researchers need to recognize and attend to those differences as much as possible in order to expand opportunities for and participation in research by residents of these rural communities. Supplemental data for this article is available online at

Comparative study of personal data protection regulations in Indonesia, Hong Kong and Malaysia

PurposeThe purpose of this paper is two-fold: to explore the legal issue of the importance of personal data protection in the digital economy sector and to propose a legal framework for personal data protection as a consumer protection strategy and accelerate the digital economy.Design/methodology/approachThis study is legal research. The research approach used was the comparative approach and statute approach. The legal materials used are all regulations regarding personal data protection that apply in Indonesia, Hong Kong and Malaysia. The technique of collecting legal materials is done by using library research techniques.FindingsThe value of Indonesia’s digital economy is the biggest in the Southeast Asia region, but data breach is still a big challenge to face. The Indonesian Consumers Foundation (Yayasan Lembaga Konsumen Indonesia) recorded 54 cases of a data breach in e-commerce, 27 cases in peer-to-peer lending and 5 cases in electronic money. Based on the results of a comparative study with Hong Kong and Malaysia, Indonesia has yet no specific Act that comprehensively regulates personal data protection. Indonesia also does not have a personal data protection commission. Criminal sanctions and civil claims related to data breaches have not yet been regulated.Research limitations/implicationsThis study examines the data breach problem in the Indonesian digital economy sector. However, the legal construction of personal data protection regulations is built on the results of a comparative study with Hong Kong and Malaysia.Practical implicationsThe results of this study can be useful for constructing the ideal regulation regarding the protection of personal data in the digital economy sector.Social implicationsThe results of the recommendations in this study are expected to develop and strengthen the protection of personal data in the Indonesian digital economy sector. Besides aiming to prevent the misuse of personal data, the regulation aims to protect consumers and accelerate the growth of the digital economy.Originality/valueIndonesia needs to create a personal data protection act. The act should at least cover such issues: personal data protection principles; types of personal data; management of personal data; mechanism of personal data protection and security; commission of personal data protection; transfers of personal data; resolution mechanism of personal data dispute and criminal sanctions and civil claims.

A Big Data and Artificial Intelligence Framework for Smart and Personalized Air Pollution Monitoring and Health Management in Hong Kong

All people in the world are entitled to enjoy a clean environment and a good quality of life. With big data and artificial intelligence technologies, it is possible to estimate personalized air pollution exposure and synchronize it with activity, health, quality of life and behavioural data, and provide real-time, personalized and interactive alert and advice to improve the health and well-being of individual citizens. In this paper, we propose an overarching framework outlining five major challenges to personalized air pollution monitoring and health management, and respective methodologies in an integrated interdisciplinary manner. First, urban air quality data is sparse, rendering it difficult to provide timely personalized alert and advice. Second, collected data, especially those involving human inputs such as health perception, are often missing and erroneous. Third, the data collected are heterogeneous, and highly complex, not easily comprehensible to facilitate individual and collective decision-making. Fourth, the causal relationships between personal air pollutants exposure (specifically, PM2.5 and PM1.0 and NO2) and personal health conditions, and health-related quality of life perception, of young asthmatics and young healthy citizens in Hong Kong (HK), are yet to be established. Fifth, whether personalized and smart information and advice provided can induce behavioural change and improve health and quality of life are yet to be determined. To overcome these challenges, our first novelty is to develop an AI and big data framework to estimate and forecast air quality in high temporal-spatial resolution and real-time. Our second novelty includes the deployment of mobile pollution sensor platforms to substantially improve the accuracy of estimated and forecasted air quality data, and the collection of activity, health condition and perception data. Our third novelty is the development of visualization tools and comprehensible indexes, by correlating personal exposure with four types of personal data, to provide timely, personalized pollution, health and travel alerts and advice. Our fourth novelty is determining causal relationship, if any, between personal pollutants, PM1.0 and PM2.5, NO2 exposure and personal health condition, and personal health perception, based on a clinical experiment of 150 young asthmatics and 150 young healthy citizens in HK. Our fifth novelty is an intervention study to determine if smart information, presented via our proposed visualized platform, will induce personal behavioural change. Our novel big data AI-driven approach, when integrated with other analytical approaches, provides an integrated interdisciplinary framework for personalized air pollution monitoring and health management, easily transferrable to and applicable in other domains and countries.

Give or buy contexts and internet experience as a factor differentiating of readiness to provide different types of personal data in m-commerce

Studies show that privacy concerns are an important factor in m-commerce and m-buyers are often not ready to disclose private data to m-shops. An e-questionnaire survey was used to gather opinions in three groups – ca. 160 Poles, ca.160 Ukrainians and ca.130 Romanians, to study decisions of potential consumers concerning disclosure of personal data when downloading paid or free mobile applications in 3 different contexts: downloading an attractive app to their smartphone as a gift, as a promo purchase, or from a well-known brand. The study showed that different kinds of personal data have different fragility levels. The e-mail had the lowest level of concern, postal address a medium level, and ID and credit card numbers the highest. Context was also shown to change the kind of data respondents are willing to exchange for an attractive app. When the measure of internet experience was subjective to the length of internet use, people with higher internet experience were not found to be more unlikely to download an attractive app to their smartphone, if a condition of downloading it was providing personal identification data, in comparison with persons with low internet experience. When internet experience was measured by social norms (living in a country with a higher e-readiness index), persons with higher experience levels were less likely to download apps requiring the provision of personal data. The text ends with recommendations and suggestions for further research.

Anticipatory Governance in Biobanking: Security and Risk Management in Digital Health

Although big-data research has met with multiple controversies in diverse fields, political and security implications of big data in life sciences have received less attention. This paper explores how threats and risks are anticipated and acted on in biobanking, which builds research repositories for biomedical samples and data. Focusing on the biggest harmonisation cluster of biomedical research in Europe, BBMRI-ERIC, the paper analyses different logics of risk in the anticipatory discourse on biobanking. Based on document analysis, interviews with ELSI experts, and field research, three types of framing of risk are reconstructed: data security, privacy, and data misuse. The paper finds that these logics downplay the broader social and political context and reflects on the limits of the practices of anticipatory governance in biobanking. It argues that this regime of governance can make it difficult for biobanks to address possible future challenges, such as access to biomedical data by authorities, pressures for integrating biobank data with other type of personal data, or their use for profiling beyond medical purposes. To address potential controversies and societal implications related to the use of big data in health research and medicine, the paper suggests to expand the vocabulary and practices of anticipatory governance, in the biobanking community and beyond.

Acquisition and Interpretation of Digital Information in Forensic Assessments

Despite the now ubiquitous presence of technology in everyday life, there is little written on the subject of personal digital data as it pertains to forensic mental health evaluations. Ethical concerns and limited consensus guidance on this issue have previously made it challenging to use this information in a responsible way. This Perspectives article elaborates on the different types of personal data that exist and the practical aspects of acquiring such information, including data location and legal considerations. Incorporation of personal digital information into the forensic assessment as a form of collateral information is discussed, along with the current state of the literature on technology use and its relationship to psychopathology and risk. Given the important role of technology in the life of the modern individual, deeper research into this topic will be necessary in the immediate future to establish practice standards for the safe and ethical use of digital information in both forensic and non-forensic mental health assessments.

That’s Private! Understanding Travelers’ Privacy Concerns and Online Data Disclosure

Against the backdrop of advancements in technology and its deployment by companies and governments to collect sensitive personal information, information privacy has become an issue of great interest for academics, practitioners, and the general public. The travel and tourism industry has been pioneering the collection and use of biometric data for identity verification. Yet, privacy research focusing on the travel context is scarce. This study developed a valid measurement of Travelers’ Online Privacy Concerns (TOPC) through a series of empirical studies: pilot ( n=277) and cross-validation ( n=287). TOPC was then assessed for its predictive validity in its relationships with trust, risk, and intention to disclose four types of personal data: biometric, identifiers, biographic, and behavioral data ( n=685). Results highlight the role of trust in mitigating the relationship between travelers’ privacy concerns and data disclosure. This study provides valuable contribution to research and practice on data privacy in travel.

Web Analytics and Online Retail

Currently, all major e-retailers and even the start-ups have incorporated web analytics services on their websites to monitor customer behaviour while extracting personal data. However, the web analytics data collection methods and the applications of such collected data have raised a lot of concerns regarding the ethical use of this data. The present work identifies some important ethical challenges and unethical practices that have cropped up with the usage of these techniques. The research also suggests the measures to reduce the volume and type of personal data that can be monitored by the websites/applications at the user level. It also elaborates on measures and requirements that need to be undertaken by the online retailers at the policy level to meet the country and industry standards, while keeping their practices ethical.

Preface to the special issue on harnessing personal tracking data for personalization and sense-making

Increasingly, people are making use of diverse digital services that create many types of personal data. The most recent addition to such services are self-tracking devices that are capable of creating very detailed personal activity records. The focus of this special issue is to explore how such activity records can be exploited to provide user-centric personalization services.

Personal data usage and privacy considerations in the COVID-19 global pandemic.

Data has become increasingly important and valuable for both scientists and health authorities searching for answers to the COVID-19 crisis. Due to difficulties in diagnosing this infection in populations around the world, initiatives supported by digital technologies are being developed by governments and private companies to enable the tracking of the public's symptoms, contacts and movements. Considering the current scenario, initiatives designed to support infection surveillance and monitoring are essential and necessary. Nonetheless, ethical, legal and technical questions abound regarding the amount and types of personal data being collected, processed, shared and used in the name of public health, as well as the concomitant or posterior use of this data. These challenges demonstrate the need for new models of responsible and transparent data and technology governance in efforts to control SARS-COV2, as well as in future public health emergencies.

Legal Challenges in the Realm of InsurTech

The paper addresses the topic of digital innovation in the insurance field and the challenges it poses for both companies and regulators. The paper starts with showing how data-driven technologies represent a priceless resource for insurers, allowing new and revolutionary methods to classify policyholders in different merit categories according to risk. The paper then turns to the analysis of new tools at the centre of the recent technological development (i.e. Blockchain and smart contracts) and focuses on the role of Big Data in the insurance sector. The paper thus concludes with some considerations on why access to more types of personal data should be allowed to insurers by regulators, presenting potential advantages not only for the companies themselves, but also for customers and the financial system in general. FinTech, InsurTech, Innovation, BigData, Blockchain, Technology, Personal Data, Insurance, Credit Scoring, Risk.