Thus, we aim to fill this gap in the literature by posing the following question (RQ): What is the current research and development status on personal data stores regarding architectures, capabilities, and challenges? However, no previous research study has offered a comprehensive review of current PDS platforms within the academic literature. Ĭurrently, most of the research related to the PDS model has focused on the development of PDS platforms that enforce user privacy preferences, and provide capabilities to store and share personal data. In addition, these PDS platforms allow individuals to create value for their data by providing tools for data trading based on their privacy preferences and permissions.
PDS platforms are designed to achieve this by allowing individuals to aggregate scattered data from different online systems (e.g., social media, banks, hospitals, airlines, etc.) and provide the tools needed to manage and share their data. This means they have the right to collect, self-manage, and exchange their data.
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In the user-centric model, individuals have full control and ownership over their data. With the emergence of the Personal Data Store (PDS) and the introduction of the General Data Protection Regulation (GDPR), the focus has shifted from a service provider-centric model to a user-centric model as a potential solution for the challenges mentioned above. Besides, individuals will not be able to use their data as a valuable asset to create profit. Furthermore, with this centralised structure, personal data are vulnerable to data security and privacy issues (e.g., data breaches by Facebook) and unlawful usage of the data. In the current centralised Internet infrastructure, individuals have little or no control over the storage and usage of their data. While control of personal data refers to the ability to collect, organise, protect, and store the data, ownership refers to having the right and ability to create economic and social value. However, despite the tremendous benefits of using these technologies, there are growing concerns and challenges regarding the control and ownership of personal data. In addition to that, with the pervasiveness of IoT technologies, billions of smart objects (e.g., sensors, home appliances, cameras, etc.) are designed to generate and collect a wealth of personal data. Other online web services (e.g., search engines, emails, digital file storage, etc.) also generate massive amounts of data. Social media platforms alone are responsible for creating a big part of this data since more than 4.2 billion people are daily using these platforms. The technological advancement in the daily lives of individuals has increased the creation, exchange, and use of personal data to levels we have never seen before. Subsequently, we summarise the major challenges and issues facing PDS platforms’ development and widespread adoption.
Further, we compare and analyse existing PDS platforms in terms of their capabilities and core components. In particular, we provide a comprehensive review of related concepts and the expected benefits of PDS platforms. This paper surveys the current literature on Personal Data Stores (PDS) that enable individuals to collect, control, store, and manage their data.
However, Personal Data Stores (PDS) have been proposed as an alternative architecture where personal data will be stored within households, giving us complete control (self-sovereignty) over our data. Current systems architectures aim to collect, store, and process our personal data in the cloud with very limited control when it comes to giving back to citizens. We increasingly see that Internet of Things (IoT) devices are also being adopted by consumers, making it possible for companies to capture personal data (including very sensitive data) with much less effort and autonomously at a very low cost. Due to the widespread use of social media, more and more personal data has been collected by different online services. In the beginning, the personal data collection was uncoordinated and was limited to a few selected data types such as names, ages, birthdays, etc. Internet services have collected our personal data since their inception.
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