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POEM Ontology

Authors: Kelsey Rook, Henrique Santos, Deborah L. McGuinness, Manuel S. Sprung, Paulo Pinheiro, and Bruce F. Chorpita

Abstract

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Kelsey Rook, Henrique Santos, Deborah L. McGuinness, Manuel S. Sprung, Paulo Pinheiro, Bruce F. Chorpita. POEM Ontology (Model, Source Code). Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@misc{dagstuhl-artifact-25228,
   title = {{POEM Ontology}}, 
   author = {Rook, Kelsey and Santos, Henrique and McGuinness, Deborah L. and Sprung, Manuel S. and Pinheiro, Paulo and Chorpita, Bruce F.},
   note = {Model (visited on 2025-12-10)},
   url = {https://github.com/tetherless-world/POEM},
   doi = {10.4230/artifacts.25228},
}

Document

Resource

DOI: 10.4230/TGDK.3.3.3

Supporting Psychometric Instrument Usage Through the POEM Ontology

Authors: Kelsey Rook, Henrique Santos, Deborah L. McGuinness, Manuel S. Sprung, Paulo Pinheiro, and Bruce F. Chorpita

Published in: TGDK, Volume 3, Issue 3 (2025). Transactions on Graph Data and Knowledge, Volume 3, Issue 3

Abstract

Psychometrics is the field relating to the measurement of concepts within psychology, particularly the assessment of various social and psychological dimensions in humans. The relationship between psychometric entities is critical to finding an appropriate assessment instrument, especially in the context of clinical psychology and mental healthcare in which providing the best care based on empirical evidence is crucial. We aim to model these entities, which include psychometric questionnaires and their component elements, the subject and respondent, and the latent variables being assessed. The current standard for questionnaire-based assessment relies on text-based distributions of instruments; so, a structured representation is necessary to capture these relationships to enhance accessibility and use of existing measures, encourage reuse of questionnaires and their component elements, and enable sophisticated reasoning over assessment instruments and results by increasing interoperability. We present the design process and architecture of such a domain ontology, the Psychometric Ontology of Experiences and Measures, situating it within the context of related ontologies, and demonstrating its practical utility through evaluation against a series of competency questions concerning the creation, use, and reuse of psychometric questionnaires in clinical, research, and development settings.

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Kelsey Rook, Henrique Santos, Deborah L. McGuinness, Manuel S. Sprung, Paulo Pinheiro, and Bruce F. Chorpita. Supporting Psychometric Instrument Usage Through the POEM Ontology. In Transactions on Graph Data and Knowledge (TGDK), Volume 3, Issue 3, pp. 3:1-3:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@Article{rook_et_al:TGDK.3.3.3,
  author =	{Rook, Kelsey and Santos, Henrique and McGuinness, Deborah L. and Sprung, Manuel S. and Pinheiro, Paulo and Chorpita, Bruce F.},
  title =	{{Supporting Psychometric Instrument Usage Through the POEM Ontology}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{3:1--3:19},
  ISSN =	{2942-7517},
  year =	{2025},
  volume =	{3},
  number =	{3},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.3.3.3},
  URN =		{urn:nbn:de:0030-drops-252148},
  doi =		{10.4230/TGDK.3.3.3},
  annote =	{Keywords: ontology, ontology development, psychometric assessment, psychometric ontology}
}

Document

DOI: 10.4230/OASIcs.SLATE.2024.10

Towards an Intelligent Algorithm for Profile Authentication and Identification

Authors: Nuno Jerónimo, Filipe Portela, and Henrique Santos

Published in: OASIcs, Volume 120, 13th Symposium on Languages, Applications and Technologies (SLATE 2024)

Abstract

In the context digital transformation, the necessity for secure and efficient virtual identity verification has become paramount. Traditional methods often fail to balance security, speed, and usability, leaving gaps in user authentication systems. This paper addresses the critical challenge of creating a virtual ID system that identifies a single profile with improved security, speed, and effectiveness. An innovative face recognition algorithm using dynamic content loading and deep learning techniques is proposed. The utilisation of OpenCV for face recognition and feature extraction, combined with advanced similarity calculation methods, the system achieves superior accuracy in profile authentication tasks. Extensive testing, including identical twin scenarios, demonstrates the robustness of the algorithm and its superiority over existing solutions such as Apple’s Face ID. In 150 of the tests conducted with identical twins, the algorithm consistently achieved 100% recognition accuracy. This breakthrough in facial recognition technology promises to create a triple authentication system, which will solve the problem of false positives in terms of identifying and authenticating people. This paper integrates principles from Computer Intelligence and Chatbots, emphasizing the application of deep learning techniques in enhancing virtual identity verification systems. This research contributes to the broader discourse on improving authentication mechanisms in the digital age.

Cite as

Nuno Jerónimo, Filipe Portela, and Henrique Santos. Towards an Intelligent Algorithm for Profile Authentication and Identification. In 13th Symposium on Languages, Applications and Technologies (SLATE 2024). Open Access Series in Informatics (OASIcs), Volume 120, pp. 10:1-10:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{jeronimo_et_al:OASIcs.SLATE.2024.10,
  author =	{Jer\'{o}nimo, Nuno and Portela, Filipe and Santos, Henrique},
  title =	{{Towards an Intelligent Algorithm for Profile Authentication and Identification}},
  booktitle =	{13th Symposium on Languages, Applications and Technologies (SLATE 2024)},
  pages =	{10:1--10:14},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-321-8},
  ISSN =	{2190-6807},
  year =	{2024},
  volume =	{120},
  editor =	{Rodrigues, M\'{a}rio and Leal, Jos\'{e} Paulo and Portela, Filipe},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.SLATE.2024.10},
  URN =		{urn:nbn:de:0030-drops-220817},
  doi =		{10.4230/OASIcs.SLATE.2024.10},
  annote =	{Keywords: Facial recognition, Biometric analysis, Dynamic content loading, User authentication}
}

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Documents authored by Santos, Henrique

POEM Ontology

Abstract

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Supporting Psychometric Instrument Usage Through the POEM Ontology

Abstract

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Towards an Intelligent Algorithm for Profile Authentication and Identification

Abstract

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