The Role of Vocabulary Mediation to Discover and Represent Relevant Information in Privacy Policies

To date, the effort made by existing vocabularies to provide a shared representation of the data protection domain is not fully exploited. Different natural language processing (NLP) techniques have been applied to the text of privacy policies without, however, taking advantage of existing vocabularies to provide those documents with a shared semantic superstructure. In this paper we show how a recently released domain-specific vocabulary, i.e. the Data Privacy Vocabulary (DPV), can be used to discover, in privacy policies, the information that is relevant with respect to the concepts modelled in the vocabulary itself. We also provide a machine-readable representation of this information to bridge the unstructured textual information to the formal taxonomy modelled in it. This is the first approach to the automatic processing of privacy policies that relies on the DPV, fuelling further investigation on the applicability of existing semantic resources to promote the reuse of information and the interoperability between systems in the data protection domain

Frequent Use Cases Extraction from Legal Texts in the Data Protection Domain

Because of the recent entry into force of the General Data Protection Regulation (GDPR), a growing of documents issued by the European Union institutions and authorities often mention and discuss various use cases to be handled to comply with GDPR principles. This contribution addresses the problem of extracting recurrent use cases from legal documents belonging to the data protection domain by exploiting existing Ontology Design Patterns (ODPs). An analysis of ODPs that could be looked for inside data protection related documents is provided. Moreover, a first insight on how Natural Language Processing techniques could be exploited to identify recurrent ODPs from legal texts is presented. Thus, the proposed approach aims to identify standard use cases in the data protection field at EU level to promote the reuse of existing formalisations of knowledge

Legal knowledge extraction in the data protection domain based on Ontology Design Patterns

In the European Union, the entry into force of the General Data Protection Regulation (GDPR) has brought the domain of data protection to the fore-front, encouraging the research in knowledge representation and natural language processing (NLP). On the one hand, several ontologies adopted Semantic Web standards to provide a formal representation of the data protection framework set by the GDPR. On the other hand, different NLP techniques have been utilised to implement services addressed to individuals, for helping them in understanding privacy policies, which are notoriously difficult to read. Few efforts have been devoted to the mapping of the information extracted from privacy policies to the conceptual representations provided by the existing ontologies modelling the data protection framework. In the first part of the thesis, I propose and put in the context of the Semantic Web a comparative analysis of existing ontologies that have been developed to model different legal fields. In the second part of the thesis, I focus on the data protection domain and I present a methodology that aims to fill the gap between the multitude of ontologies released to model the data protection framework and the disparate approaches proposed to automatically process the text of privacy policies. The methodology relies on the notion of Ontology Design Pattern (ODP), i.e. a modelling solution to solve a recurrent ontology design problem. Implementing a pipeline that exploits existing vocabularies and different NLP techniques, I show how the information disclosed in privacy policies could be extracted and modelled through some existing ODPs. The benefit of such an approach is the provision of a methodology for processing privacy policies texts that overlooks the different ontological models. Instead, it uses ODPs as a semantic middle-layer of processing that different ontological models could refine and extend according to their own ontological commitments

The potential etiopathogenetic role and diagnostic utility of CD3+ CD56+ regulatory T lymphocytes in Myelodysplastic Syndromes

Serio et al. show a significant reduction of CD3+CD56+ regulatory T cells (TR3-56) in bone marrow (BM) of low-risk myelodysplastic subjects, as compared with the high-risk and the AML group; in addition, the BM frequency of mature granulocytes, a recognised marker of residual effective haematopoiesis, was observed to inversely correlate with TR3-56 in the MDS cohort. Such data are of great interest and confirm and extend, in an independent MDS cohort, the trend-increase of BM TR3-56 from very low/low risk to high/very high risk MDS and the inverse correlation with the cytotoxic T-cell (CTL) activity, likely fostering the escape of leukaemic blasts to immune-surveillance, by us recently described

On the ergodicity of supercooled molecular glass-forming liquids at the dynamical arrest: the o-terphenyl case

The dynamics of supercooled ortho-terphenyl has been studied using photon-correlation spectroscopy (PCS) in the depolarized scattering geometry. The obtained relaxation curves are analyzed according to the mode-coupling theory (MCT) for supercooled liquids. The main results are: i) the observation of the secondary Johari-Goldstein relaxation (β) that has its onset just at the dynamical crossover temperature T[subscript B] (T[subscript M] > T[subscript B] > T[subscript g]); ii) the confirmation, of the suggestion of a recent statistical mechanical study, that such a molecular system remains ergodic also below the calorimetric glass-transition temperature T[subscript g]. Our experimental data give evidence that the time scales of the primary (α) and this secondary relaxations are correlated. Finally a comparison with recent PCS experiments in a colloidal system confirms the primary role of the dynamical crossover in the physics of the dynamical arrest.United States. Dept. of Energy. Office of Basic Energy Sciences (Contract DE-FG02-90ER45429

Taking stock of legal ontologies: a feature-based comparative analysis

International audienceOntologies represent the standard way to model the knowledge about specific domains. This holds also for the legal domain where several ontologies have been put forward to model specific kinds of legal knowledge. Both for standard users and for law scholars, it is often difficult to have an overall view on the existing alternatives, their main features and their interlinking with the other ontologies. To answer this need, in this paper, we address an analysis of the state-of-the-art in legal ontologies and we characterise them along with some distinctive features. This paper aims to guide generic users and law experts in selecting the legal ontology that better fits their needs and in understanding its specificity so that proper extensions to the selected model could be investigated