Data

AWARE: Adaptive Human-Centred AI for Relational Ecosystem Assessment — Synthetic and Annotated Pseudocode Repository (Version 1.0)

Flinders University
Pinero de Plaza, Maria Alejandra
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.25451/flinders.30412363.v1&rft.title=AWARE: Adaptive Human-Centred AI for Relational Ecosystem Assessment — Synthetic and Annotated Pseudocode Repository (Version 1.0)&rft.identifier=10.25451/flinders.30412363.v1&rft.publisher=Flinders University&rft.description=This dataset supports a manuscript in progress applying AWARE (Adaptive Human-Centred AI for Relational Ecosystem Assessment), an artificial-intelligence framework that models human–relational dynamics within complex care, sociotechnical, and organisational ecosystems. The repository includes synthetic data and annotated Python pseudocode reproducing the analytic workflow used in AWARE—covering data preprocessing, path estimation, RidgeCV regularisation, and network visualisation. These materials enable conceptual replication and peer review while maintaining the confidentiality of proprietary algorithmic components.Intellectual Property and RightsAWARE was conceived, designed, and developed by Dr Maria Alejandra Piñero de Plaza (https://orcid.org/0000-0001-5421-9604) as an independent intellectual creation. The framework’s analytic architecture and computational logic are protected under Flinders University’s intellectual-property and copyright policies, with author ownership retained where institutional rights are not exercised. This release provides an annotated Python-based pseudocode version of the analytic workflow for transparency and scholarly verification. Proprietary algorithmic syntax, functional sequences, and parameter configurations remain confidential to protect the author’s intellectual property while ensuring methodological reproducibility.Reuse ConditionsReuse, redistribution, or modification of these materials is not permitted without prior written consent from Dr Maria Alejandra Piñero de Plaza. The released pseudocode and synthetic data enable conceptual replication and analytic verification of the AWARE framework’s methodological structure. Requests for full executables, involving access to the complete algorithmic implementation, hyperparameter configurations, or proprietary computational logic, may be considered under a formal Material Transfer Agreement (MTA) or Non-Disclosure Agreement (NDA) approved by the author.Contact📧 [email protected]📧 [email protected]📧 [email protected] CitationPiñero de Plaza, M. A. (2025). AWARE: Adaptive Human-Centred AI for Relational Ecosystem Assessment — Synthetic Dataset and Annotated Pseudocode (Version 1.0). Flinders University. Dataset and code repository. https://doi.org/10.25451/flinders.30412363&rft.creator=Pinero de Plaza, Maria Alejandra &rft.date=2025&rft.edition=1&rft_rights= https://library.unimelb.edu.au/Digital-Scholarship/restrictive-licence-template&rft_subject=Health informatics and information systems&rft_subject=Artificial life and complex adaptive systems&rft_subject=Health care administration&rft_subject=Health services and systems not elsewhere classified&rft_subject=Digital health&rft_subject=Medicine, nursing and health curriculum and pedagogy&rft_subject=Nursing not elsewhere classified&rft_subject=Health management&rft_subject=Fundamentals of Care&rft_subject=Artificial Intelligence&rft_subject=AWARE AI Framework&rft_subject=Relational Intelligence&rft_subject=Machine Learning&rft_subject=Predictive modelling.&rft_subject=Human-Centred Systems&rft_subject=Implementation Science&rft_subject=Complexity sciences&rft_subject=Digital Health&rft_subject=healthcare quality measures&rft_subject=Network Analysis&rft_subject=Reproducible Research&rft_subject=AI Ethics&rft.type=dataset&rft.language=English Access the data
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Full description

This dataset supports a manuscript in progress applying AWARE (Adaptive Human-Centred AI for Relational Ecosystem Assessment), an artificial-intelligence framework that models human–relational dynamics within complex care, sociotechnical, and organisational ecosystems. The repository includes synthetic data and annotated Python pseudocode reproducing the analytic workflow used in AWARE—covering data preprocessing, path estimation, RidgeCV regularisation, and network visualisation. These materials enable conceptual replication and peer review while maintaining the confidentiality of proprietary algorithmic components.

Intellectual Property and Rights

AWARE was conceived, designed, and developed by Dr Maria Alejandra Piñero de Plaza (https://orcid.org/0000-0001-5421-9604) as an independent intellectual creation. The framework’s analytic architecture and computational logic are protected under Flinders University’s intellectual-property and copyright policies, with author ownership retained where institutional rights are not exercised. This release provides an annotated Python-based pseudocode version of the analytic workflow for transparency and scholarly verification. Proprietary algorithmic syntax, functional sequences, and parameter configurations remain confidential to protect the author’s intellectual property while ensuring methodological reproducibility.

Reuse Conditions

Reuse, redistribution, or modification of these materials is not permitted without prior written consent from Dr Maria Alejandra Piñero de Plaza. The released pseudocode and synthetic data enable conceptual replication and analytic verification of the AWARE framework’s methodological structure. Requests for full executables, involving access to the complete algorithmic implementation, hyperparameter configurations, or proprietary computational logic, may be considered under a formal Material Transfer Agreement (MTA) or Non-Disclosure Agreement (NDA) approved by the author.

Contact

📧 [email protected]
📧 [email protected]
📧 [email protected]

Recommended Citation

Piñero de Plaza, M. A. (2025). AWARE: Adaptive Human-Centred AI for Relational Ecosystem Assessment — Synthetic Dataset and Annotated Pseudocode (Version 1.0). Flinders University. Dataset and code repository. https://doi.org/10.25451/flinders.30412363

Issued: 22 10 2025

Created: 22 10 2025

Modified: 22 10 2025

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AI Ethics | AWARE AI Framework | Artificial Intelligence | Artificial life and complex adaptive systems | Complexity sciences | Digital Health | Digital health | Fundamentals of Care | Health care administration | Health informatics and information systems | Health management | Health services and systems not elsewhere classified | Human-Centred Systems | Implementation Science | Machine Learning | Medicine, nursing and health curriculum and pedagogy | Network Analysis | Nursing not elsewhere classified | Predictive modelling. | Relational Intelligence | Reproducible Research | healthcare quality measures |

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