OntoRetention is a task ontology under development, conceived as the prescriptive layer of the OntoHR ecosystem. It extends OntoTurnover (SANTANA; RODRIGUES; FARIAS JUNIOR; SANTOS, 2023), which describes the causes of voluntary turnover, by answering the question the descriptive layer leaves open: given an identified risk profile, what can the employer do, with what evidential support, and under whose authority.
Modeled in OWL 2 DL and grounded in gUFO, the ontology formalizes retention interventions as actions executable by the employer, each with preconditions, viability constraints, the cause it addresses, and the retention factor it strengthens. The cause–intervention mapping is qualified by a level of empirical evidence, to be validated through a systematic literature review, and intervention priority is inferred by automated reasoning when evidence, preconditions, and viability align. A central commitment of the project is to keep separate six things that current approaches conflate: the evidence, the risk assessment, the recommendation, the authorization, the decision, and the executed intervention. Recommendations are defeasible and never obligatory; decision-making authority remains human, with authorization positions grounded in UFO-L and organizational commitments in UFO-S.
In its current state, OntoRetention is at the requirements specification stage: it has defined competency questions (40, organized into eight groups) and an extension architecture designed in five layers, but no implemented OWL artifact yet. The next steps are the systematic review that will anchor the cause × intervention × evidence matrix and the modeling of the constructs in Protégé, with validation via reasoner.
The ultimate goal is to enable talent retention decision support that is traceable, checkable, and contestable: every recommendation verbalized by an LLM must correspond to an auditable inference chain, and the risk label remains attached to a revisable situation, never to the person.
Get to know more about at:
- SANTANA, A. C.; RODRIGUES, C. N. d. O. OntoTurnover. GitHub. Link: https://github.com/alinecsantana/Ontoturnover/
- SANTANA, A. C.; RODRIGUES, C. M. d. O.; FARIAS JUNIOR, I. H. d.; SANTOS, W. B. OntoTurnover: A Lightweight Domain Ontology for Modeling Employee Turnover. 2023 18th Iberian Conference on Information Systems and Technologies (CISTI), Aveiro, Portugal, 2023, pp. 1-4, doi: 10.23919/CISTI58278.2023.10211799. https://ieeexplore.ieee.org/document/10211799
- SANTANA, Aline C.; FARIAS JUNIOR, Ivaldir H. de; SANTOS, Wylliams B.; RODRIGUES, Cleyton M. de O.. OntoTurnover: Uma ontologia de domínio sobre a rotatividade de profissionais. In: WORKSHOP DE TESES E DISSERTAÇÕES EM QUALIDADE DE SOFTWARE - SIMPÓSIO BRASILEIRO DE QUALIDADE DE SOFTWARE (SBQS), 22. , 2023, Brasília/DF. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2023 . p. 13-18. DOI: https://doi.org/10.5753/sbqs_estendido.2023.235887.