Appropriate Measures for Security: Investigating Legal and Technical Requirements under the GDPR

The General Data Protection Regulation (GDPR) has been in force in the EU since May 2018, but there is still much uncertainty on how to meet its demands in practice. For instance, in its Article 32 the regulation defines that the data controller “shall implement appropriate technical and organisational measures to ensure a level of security appropriate to the risk”. The GDPR gives some indication on the aspects that should drive the decision on appropriate measures, but it admits multiple interpretations. Thus, when reading the regulation’s demands, one question resonates: How to devise and put in practice technical measures suitable to guarantee such technical and legal demands from Article 32? This is the driving question of this project.

If on one side we lack concrete guidelines on how to comply with GDPR’s demands, on the other, information on what is not compliant is already available: approximately 90 fines have been applied on the basis of violation of Article 32. This project foresees the analysis of the decisions issued by the Data Protection Authorities (DPAs) imposing fines for the breach of Article 32 GDPR. In particular, it will look at how the DPAs interpret and apply the factors mentioned in this provision, and it will map findings regarding the security of data processing into tangible and concrete guidelines to help the implementation of suitable security measures. This interdisciplinary project combines topics of information security (Dayana Spagnuelo), and in human rights law (Magdalena Jozwiak).

Academy Assistants

Maria Konstantinou: ‘As a law student, I am working on the legal side of the project. My work includes researching the scholarly literature on the risks resulting from a privacy and data protection infringement and analysing the DPA decisions to detect the non-compliance mistakes and concretise the appropriate organisational measures under Article 32 of the GDPR.’.
Tina Marjanov: As a Computer Science student, I am working on the technical side of the project. This includes researching the state of the art standards and requirements in the field of information security and then analyzing the DPA decisions to extract the common mistakes and formalize technical guidelines for compliance with the GDPR article 32.


Designing Biofeedback VR Technology for Supporting Relaxation

The project aims to integrate a virtual reality environment and respiratory biofeedback to help users relax and manage their stress. The Academy Assistants presented an accessible program that measures users breathing with only their mobile phone and integrates this information in a VR environment. The final goal is to help users visualize their own respiratory pace, and adjust it to foster relaxation. After conducting a successful pilot study, the researchers intend to run further experiments with the system during the next academic year, and publish the results in academic venues. Besides, the system will be made publicly available to boost research on this topic.

Academy Assistants

Elena Maan: My name is Elena Maan and I’m from the communication sciences department. Together with Lars Lische, Miguel Barreda Angeles and Katrin Obendrauf I work on the ‘designing biofeedback in VR technology for supporting relaxation’ project. My position is the position of academic assistant.
Katrin Obendrauf: I am an AI masters student and I am working on the Relaxation in VR Project. My main role in the project is to program the prototype (so the VR environment and the collection and integration of biofeedback into the VR environment). Additionally, I will conduct an experiment with Elena to evaluate our prototype and will then analyze the prototype from a HCI perspective.



Effects of Headline Formulation Features

The aim of the project was twofold: on the one hand, we wanted to verify whether formulations of headlines play a role in news selection decisions of news users, and whether social media algorithms would help reduce the diversity of social media algorithms (that is, do algorithms favor news that is formulated in specific ways?). In order to achieve these goals, we replicated and extended a content analysis of headlines with Click Through Rates (CTR) collected in A/B tests by the Dutch newspaper NRC, and we further developed a tool simulating a news recommender, in order to tap audience preferences for news presented in different formulation styles.

The first stage of the research project investigated formulation features of NRC newspaper headlines that had been modified in so called A/B tests: alternative headlines were probed on identical website pages, where the difference in the number of clicks decided which was the more popular headline. The tests were performed without any presumptions about our research; we obtained the data set of about 8,000 headlines with their views and clicks afterwards. We wanted to verify whether properties like negativity, language intensity, and forward referencing would promote headline selection. In a content analysis these and other features were identified and tested against the CTR. This way we replicated and extended earlier research (Lagerwerf and Govaert, 2021). A manuscript to be submitted to Digital Journalism  is almost completed.

The second stage of the research project consisted of the development of a digital tool (a recommender systems research tool called ‘3bij3’, Loecherbach & Trilling, 2020) to further investigate potential systematic influence of the formulation features negativity and language intensity. First, news items gathered from news website were clustered on the basis of their news topic. Second, from a set of similar news items two headlines were chosen that are opposite in negativity. Likewise, two headlines were chosen that are opposite in language intensity. These headlines are, together with two filler items, presented on a mock news website. Every day, news items are renewed, and the same respondents are asked to pick the news item that interests them the most. Their choices are registered. In our data analysis we are analyzing systematic patterns of news choices motivated by negativity and/or language intensity. The tool has been developed and data collection has started this week.

Lagerwerf, L., & Govaert, C. G. (2021). Raising clickworthiness: Effects of foregrounding news values in online newspaper headlines News Values from an Audience Perspective (pp. 95-119): Springer.
Loecherbach, F. & Trilling, D. (2020). 3bij3 – Developing a framework for researching recommender systems and their effects. Computational Communication Research 2(1), 53-79. doi: 10.5117/CCR2020.1.003.LOEC

Academy Assistants

Supervisors: Luuk Lagerwerf & Wouter Atteveldt
Advisors: Nicolas Mattis and Tim Groot Kormelink

Information Systems Complexity and Sustainability

The rising complexity of software systems presents managers with major challenges regarding the management of their application landscapes; it negatively influences efficiency and business agility. In a similar vein, it hinders software architects in making informed design decisions: they are asked to continuously evolve the software while ensuring its reliability, and technical quality like performance and security.

This project addresses the question: how can we get a grip on the complexity of software landscapes so that we can understand how the decisions made over time influence the related technical and business sustainability?
It will study the software landscape of a large organization, and extract a suite of metrics that will help analyze the relation between complexity and sustainability.

Supervisors: Patricia Lago & Bart Hooff

Mapping Communication Science with Living Literature Reviews

Literature reviews are an invaluable asset in communication science to bring work from different approaches (e.g., linguistics, political science, psychology) together. Such reviews, however, require a lot of work to be compiled and are quickly outdated. Unfortunately, there are no incentives or systems in place to keep them updated, which would also be a very difficult and time-consuming task given the narrative paper format in which they are published.
The concept and technology of nanopublications could help researchers with these problems. Nanopublications are a container format to publish scientific (and other) statements as small pieces of Linked Data. This project investigates whether nanopublications yield us with machine-interpretable, interoperable, and easily updatable literature reviews in communication science. To do so, we will develop a general model for literature reviews in communication science, and then apply it on a concrete case from an existing literature review. We will thereby demonstrate how this allows for literature reviews that are “living” in the sense that they can be kept up-to-date in a manner that is user-friendly, open, and provenance-aware.

Supervisors: Tobias Kuhn & Mickey Steijaert

Protein Transformers: Large Transferable Language Models for Protein Sequences

Recently, deep language models like BERT and GPT-2 have shown a remarkable ability to generalize across domains. Models pre-trained on large amounts of general-domain data yield representations that capture high-level semantics, and can be finetuned for domains where little data is available.

We will adapt deep language models from the natural language domain to the domain of protein sequences. Both domains use sequences of tokens from a finite alphabet, making it straightforward to apply existing language models without much adaptation. If this approach is successful, it will lead to representations of protein sequences which extract high-level semantic concepts from raw data, which may benefit drug-discovery, biomedical analysis, and biomolecular information retrieval.

Supervisors: Maurits Dijkstra & Peter Bloem

Academy Assistants: Henriette Capel & Robin Weiler

The Cycle of News in Chronicles from Eighteenth Century Holland: A Stylometric Approach

Scholars agree that cultural changes in early modern Europe (c. 1500-1800) were both accompanied and precipitated by an information revolution. The use of printed media filtered down into local chronicles. These are hand-written narratives produced usually by middle class authors, that recorded events and phenomena they considered important (local politics, upheavals, climate, prices, crime, deaths). Authors frequently copied excerpts from earlier chronicles, official documents, local announcements and by-laws, and increasingly copied or inserted printed material, like ballads, pamphlets, and newspapers, without being explicit about the fact that they were copying (Pollmann 2016).This project will focus on automatically finding what parts of the chronicles contain the wordings of the chronicler him(/her)self and what parts might be copied. We will apply both close reading and computational stylometry techniques that are often used in authorship verification. Students will work in the framework of the NWO project Chronicling Novelty. New Knowledge in The Netherlands (1500-1850).

Academy Assistants

Lianne Wilhelmus: In the Chronicling Novelty project, I am concerned with close reading of our source, an 18th century chronicle. I try to list all the sources our author has referred to and in this way I try to find out what his ‘information world’ (all the ways he got information: books, newspapers, jaarboeken, etc). Ultimately, by understanding the source and the author completly, I can act as a controller of the test results by stylo that will deal with the possible authors of the copied fragments.