References of "Palmirani, Monica"
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See detailDeontic Sentence Classification Using Tree Kernel Classifiers
Liga, Davide UL; Palmirani, Monica

in Intelligent Systems and Applications (2022, August 31)

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See detailDerogations Analysis of European Legislation Through Hybrid AI Approach
Palmirani, Monica; Liga, Davide UL

in Electronic Government and the Information Systems Perspective: 11th International Conference, EGOVIS 2022 (2022)

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See detailHybrid AI Framework for Legal Analysis of the EU Legislation Corrigenda
Palmirani, Monica; Sovrano, Francesco; Liga, Davide UL et al

in Legal Knowledge and Information Systems (2021)

This paper presents an AI use-case developed in the project “Study on legislation in the era of artificial intelligence and digitization” promoted by the EU Commission Directorate-General for Informatics ... [more ▼]

This paper presents an AI use-case developed in the project “Study on legislation in the era of artificial intelligence and digitization” promoted by the EU Commission Directorate-General for Informatics. We propose a hybrid technical framework where AI techniques, Data Analytics, Semantic Web approaches and LegalXML modelisation produce benefits in legal drafting activity. This paper aims to classify the corrigenda of the EU legislation with the goal to detect some criteria that could prevent errors during the drafting or during the publication process. We use a pipeline of different techniques combining AI, NLP, Data Analytics, Semantic annotation and LegalXML instruments for enriching the non-symbolic AI tools with legal knowledge interpretation to offer to the legal experts. [less ▲]

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See detailInferring the Meaning of Non-personal, Anonymized, and Anonymous Data
Podda, Emanuela UL; Palmirani, Monica

in Rodríguez-Doncel, Victor; Palmirani, Monica; Araszkiewicz, Michał (Eds.) et al AI Approaches to the Complexity of Legal Systems (2021)

On the awareness of the dynamism pertaining to data and its processing, this paper investigates the problem of having two mutually exclusive definitions of personal and non-personal data in the legal ... [more ▼]

On the awareness of the dynamism pertaining to data and its processing, this paper investigates the problem of having two mutually exclusive definitions of personal and non-personal data in the legal framework in force. The taxonomic analysis of key terms and their context of application highlights the risk to crystalize the whole system upon which the digital single market is built, suffocating its future development. With this premise, the paper discusses the extent of the two main data processing tools provided by the GDPR, questioning the ex-ante categorization of data and its outcome, supporting stakeholders in overcoming this issue. [less ▲]

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See detailCan Visual Design Provide Legal Transparency? The Challenges for Successful Implementation of Icons for Data Protection
Rossi, Arianna UL; Palmirani, Monica

in Design Issues (2020), 36(3), 82-96

Design is a key player in the future of data privacy and data protection. The General Data Protection Regulation (GDPR) established by the European Union aims to rebalance the information asymmetry ... [more ▼]

Design is a key player in the future of data privacy and data protection. The General Data Protection Regulation (GDPR) established by the European Union aims to rebalance the information asymmetry between the organizations that process personal data and the individuals to which that data refers. Machine-readable, standardized icons that present a “meaningful overview of the intended processing” are suggested by the law as a tool to enhance the transparency of information addressed to data subjects. However, no specific guidelines have been provided, and studies on privacy iconography are very few. This article describes research conducted on the creation and evaluation of icons representing data protection concepts. First, we introduce the methodology used to design the Data Protection Icon Set (DaPIS): participatory design methods combined with legal ontologies and machine-readable representations. Second, we discuss some of the challenges that have been faced in the development and evaluation of DaPIS and similar icon sets. Third, we provide some tentative responses and indicate a way forward for evaluation of the effectiveness of privacy icons and their widespread adoption. [less ▲]

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See detailWhat's in an Icon? Promises and Pitfalls of Data Protection Iconography
Rossi, Arianna UL; Palmirani, Monica

in Leenes, Ronald; Hallinan, Dara; Gutwirth, Serge (Eds.) et al Data Protection and Privacy: Data Protection and Democracy (2020)

Under the General Data Protection Regulation (GDPR), transparency of information becomes an obligation aimed at creating an ecosystem where data subjects understand and control what happens to their ... [more ▼]

Under the General Data Protection Regulation (GDPR), transparency of information becomes an obligation aimed at creating an ecosystem where data subjects understand and control what happens to their personal data. The definition of transparency stresses its user-centric nature, while design considerations to comply with this obligation assume central importance. This article focuses on the icons established by the GDPR Art. 12.7 to offer “a meaningful overview of the intended processing”. Existing attempts to represent data protection through icons have not met widespread adoption and reasons about the strengths and weaknesses of their creation and evaluation are here discussed. Building on this analysis, we present an empirical research proposing a new icon set that responds to GDPR requirements. The article also discusses the challenges of creating and evaluating such icon set and provides some future directions of research for effective an effective implementation and standardization. [less ▲]

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See detailUncertainty in Argumentation Schemes: Negative Consequences and Basic Slippery Slope
Liga, Davide UL; Palmirani, Monica

in Logic and Argumentation (2020)

This study is an approach to encompass uncertainty in the well-known Argumentation Scheme from Negative Consequences and in the more recent “Basic Slippery Slope Argument” proposed by Douglas Walton. This ... [more ▼]

This study is an approach to encompass uncertainty in the well-known Argumentation Scheme from Negative Consequences and in the more recent “Basic Slippery Slope Argument” proposed by Douglas Walton. This work envisages two new kinds of uncertainty that should be taken into account, one related to time and one related to the material relation between premises and conclusion. Furthermore, it is argued that some modifications to the structure of these Argumentation Schemes or to their Critical Questions could facilitate the process of Knowledge Extraction and modeling from these two argumentative patterns. For example, the study suggests to change the premises of the Basic Slippery Slope related to the Control and the Loss of Control. [less ▲]

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See detailTransfer Learning with Sentence Embeddings for Argumentative Evidence Classification
Liga, Davide UL; Palmirani, Monica

in Proceedings of the 20th Workshop on Computational Models of Natural Argument (2020)

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See detailCombining tree kernels and tree representations to classify argumentative stances
Liga, Davide UL; Palmirani, Monica

in Advances in Semantics and Linked Data: Joint Workshop Proceedings from ISWC 2020 (2020)

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See detailArgumentation Schemes as Templates? Combining Bottom-up and Top-down Knowledge Representation
Liga, Davide UL; Palmirani, Monica

in Proceedings of the 20th Workshop on Computational Models of Natural Argument (2020)

This paper describes a long-term research goal which aims at creating a middleware interface between Argumentation Schemes and natural language. This idea comes from the need to face some challenges ... [more ▼]

This paper describes a long-term research goal which aims at creating a middleware interface between Argumentation Schemes and natural language. This idea comes from the need to face some challenges related to the automatic extraction of Argumentation Schemes from Nat- ural Language: for example the ability to extract Argumentation Schemes at different level of granularity. In the paper we describe how this process can be designed and how the structures of Argumentation Schemes can be modeled to this aim. [less ▲]

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See detailDetecting “slippery slope” and other argumentative stances of opposition using tree kernels in monologic discourse
Liga, Davide UL; Palmirani, Monica

in International Joint Conference on Rules and Reasoning (2019)

The aim of this study is to propose an innovative methodology to classify argumentative stances in a monologic argumentative context. Particularly, the proposed approach shows that Tree Kernels can be ... [more ▼]

The aim of this study is to propose an innovative methodology to classify argumentative stances in a monologic argumentative context. Particularly, the proposed approach shows that Tree Kernels can be used in combination with traditional textual vectorization to discriminate between different stances of opposition without the need of extracting highly engineered features. This can be useful in many Argument Mining sub-tasks. In particular, this work explores the possibility of classifying opposition stances by training multiple classifiers to reach different degrees of granularity. Noticeably, discriminating support and opposition stances can be particularly useful when trying to detect Argument Schemes, one of the most challenging sub-task in the Argument Mining pipeline. In this sense, the approach can be also considered as an attempt to classify stances of opposition that are related to specific Argument Schemes. [less ▲]

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See detailClassifying argumentative stances of opposition using Tree Kernels
Liga, Davide UL; Palmirani, Monica

in ACAI 2019: Proceedings of the 2019 2nd International Conference on Algorithms, Computing and Artificial Intelligence (2019)

The approach proposed in this study aims to classify argumentative oppositions. A major assumption of this work is that discriminating among different argumentative stances of support and opposition can ... [more ▼]

The approach proposed in this study aims to classify argumentative oppositions. A major assumption of this work is that discriminating among different argumentative stances of support and opposition can facilitate the detection of Argument Schemes. While using Tree Kernels for classification problems can be useful in many Argument Mining sub-tasks, this work focuses on the classification of opposition stances. We show that Tree Kernels can be successfully used (alone or in combination with traditional textual vectorizations) to discriminate between different stances of opposition without requiring highly engineered features. Moreover, this study compare the results of Tree Kernels classifiers with the results of classifiers which use traditional features such as TFIDF and n-grams. This comparison shows that Tree Kernel classifiers can outperform TFIDF and n-grams classifiers. [less ▲]

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See detailFormalizing GDPR provisions in reified I/O logic: the DAPRECO knowledge base
Robaldo, Livio UL; Bartolini, Cesare UL; Lenzini, Gabriele UL et al

in Journal of Logic, Language and Information (2019)

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See detailDaPIS: an Ontology-Based Data Protection Icon Set
Rossi, Arianna UL; Palmirani, Monica

in Peruginelli, Ginevra; Faro, Sebastiano (Eds.) Knowledge of the Law in the Big Data Age (2019)

Privacy policies are known to be impenetrable and lengthy texts that are hardly read and poorly understood. This is why the General Data Protection Regulation (GDPR) introduces provisions to enhance ... [more ▼]

Privacy policies are known to be impenetrable and lengthy texts that are hardly read and poorly understood. This is why the General Data Protection Regulation (GDPR) introduces provisions to enhance information transparency including icons as visual means to clarify data practices. However, the research on the creation and evaluation of graphical symbols for the communication of legal concepts, which are generally abstract and unfamiliar to laypeople, is still in its infancy. Moreover, detailed visual representations can support users’ comprehension of the underlying concepts, but at the expense of simplicity and usability. This Chapter describes a methodology for the creation and evaluation of DaPIS, a machine-readable Data Protection Icon Set that was designed following human-centered methods drawn from the emerging discipline of Legal Design. Participatory design methods have ensured that the perspectives of legal experts, designers and other relevant stake- holders are combined in a fruitful dialogue, while user studies have empirically determined strengths and weaknesses of the icon set as communicative means for the legal sphere. Inputs from other disciplines were also fundamental: canonical principles drawn from aesthetics, ergonomics and semiotics were included in the methodology. Moreover, DaPIS is modeled on PrOnto, an ontology of the GDPR, thus offering a comprehensive solution for the Semantic Web. In combination with the description of a privacy policy in the legal standard XML Akoma Ntoso, such an approach makes the icons machine-readable and automatically retrievable. Icons can thus serve as information markers in lengthy privacy statements and support an efficient navigation of the document. In this way, different representations of legal information can be mapped and connected to enhance its comprehensibility: the lawyer-readable, the machine-readable, and the human-readable layers. [less ▲]

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See detailFrom Words to Images Through Legal Visualization
Rossi, Arianna UL; Palmirani, Monica

in Pagallo, Ugo; Palmirani, Monica; Casanovas, Pompeu (Eds.) et al AI Approaches to the Complexity of Legal Systems: AICOL International Workshops 2015–2017: AICOL-VI@ JURIX 2015, AICOL-VII@ EKAW 2016, AICOL-VIII@ JURIX 2016, AICOL-IX@ ICAIL 2017, and AICOL-X@ JURIX 2017, Revised Selected Papers (2018)

One of the common characteristics of legal documents is the absolute preponderance of text and their specific domain language, whose complexity can result in impenetrability for those that have no legal ... [more ▼]

One of the common characteristics of legal documents is the absolute preponderance of text and their specific domain language, whose complexity can result in impenetrability for those that have no legal expertise. In some experiments, visual communication has been introduced in legal documents to make their meaning clearer and more intelligible, whilst visualizations have also been automatically generated from semantically-enriched legal data. As part of an ongoing research that aims to create user-friendly privacy terms by integrating graphical elements and Semantic Web technologies, the process of creation and interpretation of visual legal concepts will be discussed. The analysis of current approaches to this subject represents the point of departure to propose an empirical methodology that is inspired by interaction and human-centered design practices. [less ▲]

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See detailLegal Ontology for Modelling GDPR Concepts and Norms
Palmirani, Monica; Bartolini, Cesare UL; Martoni, Michele et al

in JURIX 2018 proceedings (2018)

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See detailPrOnto: Privacy Ontology for Legal Reasoning
palmirani, monica; Martoni, Michele; Rossi, Arianna UL et al

in International Conference on Electronic Government and the Information Systems Perspective (2018)

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See detailA Methodological Framework to Design a Machine-Readable Privacy Icon Set
Palmirani, Monica; Rossi, Arianna UL; Martoni, Michele et al

in Schweighofer, Erich (Ed.) Data Protection / LegalTech Proceedings of the 21st International Legal Informatics Symposium IRIS 2018 (2018)

The GDPR suggests icons to convey data practices in a more straightforward way. Although vi- sualizations to represent legal terms have many benefits, there is fear that they could be misrep- resented by ... [more ▼]

The GDPR suggests icons to convey data practices in a more straightforward way. Although vi- sualizations to represent legal terms have many benefits, there is fear that they could be misrep- resented by designers and misinterpreted by individuals, thus hindering instead of facilitating the comprehension. In order to solve these issues, we present a methodology to generate legal visual representations that is based on an analysis of legal requirements, on an ontological representation of the legal knowledge, and on an iterative, multi-stakeholder design approach, followed by empirical evaluation. [less ▲]

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See detailLegal Design Patterns for Privacy
Haapio, Helena; Hagan, Margaret; Palmirani, Monica et al

in Data Protection / LegalTech Proceedings of the 21st International Legal Informatics Symposium IRIS 2018 (2018)

Fulfilling the legal requirements of mandated disclosure is a challenge in many contexts. Privacy communication is no exception, especially for those who seek to effectively inform individuals about the ... [more ▼]

Fulfilling the legal requirements of mandated disclosure is a challenge in many contexts. Privacy communication is no exception, especially for those who seek to effectively inform individuals about the use of their data. Lawyers across countries and industries are facing recurring problems when (re)writing privacy notices and terms. Visual and interactive design patterns have been suggested as the solution, yet our analysis shows that they are lacking on most privacy policies. This indicates the need for standardization and an actionable pattern library, which we propose in this paper. [less ▲]

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See detailA Visualization Approach for Adaptive Consent in the European Data Protection Framework
Rossi, Arianna UL; Palmirani, Monica

in Edelmann, Noella; Parycek, Peter (Eds.) Proceedings of the 7th International Conference for E-Democracy and Open Government (2017)

For the first time in the history of European data protection law, the use of visualizations and especially of icons is explicitly suggested as a way to improve the comprehensibility of the information ... [more ▼]

For the first time in the history of European data protection law, the use of visualizations and especially of icons is explicitly suggested as a way to improve the comprehensibility of the information about data handling practices provided to the data subjects, which plays a crucial role to obtain informed consent. Privacy icon sets have already been developed, but they differ in the kinds of information they depict and in the perspectives they embed. Moreover, they have not met widespread adoption, one reasons being that research has shown that possibility of misinterpretation of these symbols exist. Our research relies on legal Semantic Web technologies and on principles drawn from legal design and Human Computer Interaction to propose visualizations of privacy policies and consent forms. The final aim is to enhance the communication of data practices to users and to support their decision about whether to give or withhold consent [less ▲]

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