Legal ontologies over time: A systematic mapping study

Rodrigues, Cleyton Mário de Oliveira; Freitas, Frederico Luiz Gonçalves de; Barreiros, Emanoel; Azevedo, Ryan Ribeiro de; Filho, Adauto Trigueiro de Almeida

doi:10.1016/j.eswa.2019.04.009

Cited by 33 publications

(9 citation statements)

References 33 publications

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“…This provided information about the project's aims and objectives, and its future goals and directions. The authors have also been participating themselves in the relevant European and nationallyfunded projects, such as H2020 smashHit 14 , FFG CampaNeo 15 , FFG DALICC 16 , and therefore had an insider view on the consent representation and modeling issues, and also found and analysed the information about the related projects on the websites of the funding agencies (European Commission, national funding agencies). Finally, relevant works at standardisation bodies have been overviewed.…”

Section: Methodsmentioning

confidence: 99%

“…The research by Rodrigues et al [16] categorises legal ontologies along dimensions of (i) organisation and structuring of information, (ii) reasoning and problem solving, (iii) semantic indexing and search, (iv) semantic integration and interoperability and (v) understanding of a domain. The research in [16] shows that there are various approaches of legal domain and compliance that are addressed by ontologies and that they also assist in other knowledge and data driven processes.…”

Section: Introductionmentioning

confidence: 99%

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Consent through the lens of semantics: State of the art survey and best practices

Kurteva

Chhetri

Pandit

et al. 2024

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The acceptance of the GDPR legislation in 2018 started a new technological shift towards achieving transparency. GDPR put focus on the concept of informed consent applicable for data processing, which led to an increase of the responsibilities regarding data sharing for both end users and companies. This paper presents a literature survey of existing solutions that use semantic technology for implementing consent. The main focus is on ontologies, how they are used for consent representation and for consent management in combination with other technologies such as blockchain. We also focus on visualisation solutions aimed at improving individuals’ consent comprehension. Finally, based on the overviewed state of the art we propose best practices for consent implementation.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Consent through the lens of semantics: State of the art survey and best practices

Kurteva

Chhetri

Pandit

et al. 2024

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“…It can provide crucial, although shallow, semantic information for tasks such as question answering (Abujabal et al, 2018;Blanco-Fernández et al, 2020), topic disambiguation (Fernández, N. et al 2012) or detection (Krasnashchok et al, 2018;Lo et al, 2017, Al-Nabki et al, 2019 and revealment of elements relationships (Sarica et al, 2020;Amal et al, 2019). Furthermore, NER has proved to be effective in broader applications, such as user profiling (Nicoletti et al, 2013) and ontology development on unconventional domains (Oliva et al, 2019;Rodrigues et al, 2019). Anyway, since NER is a classification task, for using the most advanced approach in terms of accuracy (corpus-based NER uses deep neural networks) (Devlin et al, 2018), a training set is needed, i.e.…”

Section: Named Entity Recognitionmentioning

confidence: 99%

SkillNER: Mining and Mapping Soft Skills from any Text

Fareri,

Melluso,

Chiarello

et al. 2021

Preprint

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In today's digital world there is an increasing focus on soft skills. The reasons are many, however the main ones can be traced down to the increased complexity of labor market dynamics and the shift towards digitalisation. Digitalisation has also increased the focus on soft skills, since such competencies are hardly acquired by Artificial Intelligence Systems. Despite this growing interest, researchers struggle in accurately defining the soft skill concept and in creating a complete and shared list of soft skills. Therefore, the aim of the present paper is the development of an automated tool capable of extracting soft skills from unstructured texts. Starting from an initial seed list of soft skills, we automatically collect a set of possible textual expressions referring to soft skills, thus creating a Soft Skills list. This has been done by applying Named Entity Recognition (NER) on a corpus of scientific papers developing a novel approach and a software application able to perform the automatic extraction of soft skills from text: the SkillNER. We measured the performance of the tools considering different training models and validated our approach comparing our list of soft skills with the skills labelled as transversal in ESCO (European Skills/Competence Qualification and Occupation). Finally we give a first example of how the SkillNer can be used, identifying the relationships among ESCO job profiles based on soft skills shared, and the relationships among soft skills based on job profiles in common. The final map of soft skills-job profiles may help accademia in achieving and sharing a clearer definition of what soft skills are and fuel future quantitative research on the topic.

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“…Along with efforts towards establishing standards and requirements, the analysis of existing work is also important to identify the potential for reuse and essential drawbacks for adoption. To this end, there have been several critical studies that provide an overview of legal ontologies to date (Leone, Di Caro, & Villata, 2019;Rodrigues, Freitas, Barreiros, Azevedo, & de Almeida Filho, 2019) that present the state of legal ontologies and their usage in the community. At the same time, there are efforts to automate the association of legal requirements with applicable standards -specifically those regarding GDPR and ISO (Bartolini, Giurgiu, Lenzini, & Robaldo, 2017).…”

Section: Emerging Effortsmentioning

confidence: 99%

Standardisation, Data Interoperability, and GDPR

Pandit

Debruyne

O’Sullivan

et al. 2020

Shaping the Future Through Standardization

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The General Data Protection Regulation (GDPR) has changed the ecosystem of services involving personal data and information. It emphasises several obligations and rights, amongst which the Right to Data Portability requires providing a copy of the given personal data in a commonly used, structured, and machine-readable format – for interoperability. The GDPR thus explicitly motivates the use and adoption of data interoperability concerning information. This chapter explores the entities and their interactions in the context of the GDPR to provide an information model for the development of interoperable services. The model categorises information and exchanges and explores existing standards and efforts towards use for interoperable interactions. The chapter concludes with an argument for the use and adoption of structured metadata to enable more expressive services through semantic interoperability.

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Legal ontologies over time: A systematic mapping study

Cited by 33 publications

References 33 publications

Consent through the lens of semantics: State of the art survey and best practices

Consent through the lens of semantics: State of the art survey and best practices

SkillNER: Mining and Mapping Soft Skills from any Text

Standardisation, Data Interoperability, and GDPR

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