Problem Summary

Users often lack the tools and understanding necessary to manage and comprehend their disclosed personal data effectively. Despite regulations like the GDPR that grant users rights to access and control their data, many users face significant challenges in understanding the scope and implications of their data disclosures, particularly when exercising their right to receive data that services have about them through data exports. This lack of comprehension leads to feelings of powerlessness, disinterest, and potential misuse of their personal information.

Rationale

The aim is to empower users by enabling them to explore and comprehend their disclosed personal data through effective visualisations. This enhances users' situational awareness, transparency in data transactions, and understanding of how their data is stored, managed, and exported or imported.

Solution

A tool to support the visual and interactive exploration of data exports, enabling users to understand, manage, and control their disclosed personal data effectively.

TransparencyVis aims to enhance situational awareness by supporting perception (exploring one's data distribution based on type, time, and storage service), comprehension (identifying potentially sensitive information), and projection (raising awareness about current and future online behaviours) [1]. It does not utilise a server-based method; instead, it conducts all analysis on the client side, utilising TypeScript and JavaScript libraries. Such client-side processing ensure user privacy, avoiding unnecessary server (and data sharing) interactions. The service, accessible at https://transparency-vis.vx.igd.fraunhofer.de/, offers data export analysis for various platforms including Google, Facebook, Instagram, Netflix, Twitter, LinkedIn, TikTok, and Discord. While the version presented in this guideline is primarily designed as an independent interface for individuals, there exists an additional potential application for these visualisations within online services, fostering transparency and control by assisting users in visualising their disclosed data within the service [3].

The Data Disclosure Log [2] serves as a service provider-independent and user-side component (a Firefox browser extension) that records personal data disclosures, feeding information into the visualisation tool. Similar to TransparencyVis, the Data Disclosure Log incorporates several views, including a chronological view that allows for a temporal analysis of past personal data disclosures, which allows exploration of patterns and trends. The research in [2] predates GDPR and while user-side logging has its benefits, the GDPR's right to access concerns the data held by the online service, including inferred data. Hence, a visualisation tool aligned with GDPR's right to access should primarily emphasise analysing and presenting server-side data, such as data exports or information stored within the online service.

The Data Track's primary focus, a standalone data track tool, as outlined in Karegar, Pulls e Fischer-Hübner [3], revolves around the data portability right, although the tool is tailored for visualising data exports. This specific version addresses data exported from Google, mainly location-related data, providing a map view for visualising the traced information. The project was part of European PRIME and PrimeLife projects (archived at http://primelife.ercim.eu/) and is no longer maintained (archived at https://github.com/pylls/datatrack).

Platforms: personal computers, mobile devices

Related guidelines: Support the Visualisation and Comprehension of Disclosed Data

Example

The four views of TransparencyVis [1]. (See enlarged)

The chronological view of the Data Disclosure Log [2] (See enlarged)

• The solution received significant approval and interest from the targeted user group, indicating its potential acceptance and relevance among users. The evaluation showed promising results in terms of the tool's impact on privacy attitudes and perceived appropriateness for its intended purposes, indicating initial effectiveness [1].
• Most participants stated that for the purpose of exercising their right to data portability, they would prefer first to export their data, inspect and filter out some information before uploading it to another service provider, and would appreciate using a tool such as the Data Track for helping them to visualise and filter data in this context [3].
• A conducted user test proved the usability and the user acceptance of the solution [2].

• Only support data exports from Google. Users demonstrated difficulty differentiating between locally and remotely stored and controlled data. Additionally, users were concerned about the security of their data when they thought of downloading the data on their own machines and being responsible for its security [3].
• While the treemap in FileView offers advantages in data representation, it may be less intuitive for common users, necessitating optimisation for non-experts to enhance usability. Some functionalities, such as ListView and FileView, were not well understood by participants, indicating a need for further improvements and user comprehension. Enhancements are needed to better communicate the distinctions between files and data elements, addressing the challenge of providing a comprehensive overview to users. Long-term studies have to be applied to improved versions of the interface to examine the significance of the effects [1].
• Dealing with the vast variance in data export formats between online services and users poses a challenge in developing unified parsing schemes, impacting the provision of a comprehensive overview for the user [1].

This guideline is closely related to privacy notices. Privacy notices typically inform users about the collection, use, and sharing of their personal data [4]. Tools that enable individuals to analyse their exported data, especially when exercising their right to data access, align with the principles of transparency and control that privacy notices often aim to provide. Allowing users to examine and analyse their stored data from service providers, these tools help them gain insights into the specific data held, its utilisation, and potential sharing. This can complement the information provided in privacy notices, offering users a more hands-on approach to comprehending the data and verifying whether it matches the details presented in the privacy policy.

If integrated into the service handling personal data, such a tool could facilitate privacy choices by offering controls like data exclusion and consent management.

The guideline aims to provide tools that allow users to visually and interactively explore their data exports, enhancing their understanding and awareness of how their personal data are being used, stored, and managed. This aligns with transparency [5], as it seeks to make data handling practices clear and accessible to users. Other related privacy attributes: