María del Mar Roldán-García
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
María del Mar Roldán-García has a total of 32 co-authors. Here are the top co-authors by number of shared publications:
- José Francisco Aldana Montes
Dept. de Lenguajes y Ciencias de la Computación, ITIS Software, Universidad de Málaga, Málaga, 29071, Spain; Biomedical Research Institute of Málaga (IBIMA), Universidad de Málaga, Málaga, Spain
5 shared publications - José García-Nieto
Dept. de Lenguajes y Ciencias de la Computación, ITIS Software, Universidad de Málaga, Málaga, 29071, Spain; Biomedical Research Institute of Málaga (IBIMA), Universidad de Málaga, Málaga, Spain
5 shared publications - Antonio J. Nebro
University of Malaga
4 shared publications - Ismael Navas-Delgado
Universidad de Málaga
4 shared publications - Manuel Paneque
ITIS Software, Departamento de Lenguajes y Ciencias de la Computación, University of Málaga, 29071 Málaga, Spain
3 shared publications - Antonio Benítez-Hidalgo
University of Malaga
2 shared publications
Latest Publications
- Open Access
- 18 August 2025
- Published by Taylor & Francis in Engineering Optimization
- Vol. 58 (7) , 1-18
Leveraging large language models for the automatic implementation of problems in optimization frameworks
- 18 August 2025
- Published by Taylor & Francis in Engineering Optimization
- Vol. 58 (7) , 1-18
Open AccessLeveraging large language models for the automatic implementation of problems in optimization frameworks
- 15 September 2024
- Published by Springer Nature
- p. 161-174
A Study About Meta-optimizing the NSGA-II Multi-objective Evolutionary Algorithm
- 15 September 2024
- Published by Springer Nature
- p. 161-174
A Study About Meta-optimizing the NSGA-II Multi-objective Evolutionary Algorithm
- Open Access
- 23 January 2024
- Published by Elsevier in Information Sciences
- Vol. 661
MOODY: An ontology-driven framework for standardizing multi-objective evolutionary algorithms
- 23 January 2024
- Published by Elsevier in Information Sciences
- Vol. 661
Open AccessMOODY: An ontology-driven framework for standardizing multi-objective evolutionary algorithms
- Open Access
- 27 February 2023
- Published by Springer Nature in BMC Bioinformatics
- Vol. 24 (1) , 1-18
SALON ontology for the formal description of sequence alignments
Background: Information provided by high-throughput sequencing platforms allows the collection of content-rich data about biological sequences and their context. Sequence alignment is a bioinformatics approach to identifying regions of similarity in DNA, RNA, or protein sequences. However, there is no consensus about the specific common terminology and representation for sequence alignments. Thus, automatically linking the wide existing knowledge about the sequences with the alignments is challenging. Results: The Sequence Alignment Ontology (SALON) defines a helpful vocabulary for representing and semantically annotating pairwise and multiple sequence alignments. SALON is an OWL 2 ontology that supports automated reasoning for alignments validation and retrieving complementary information from public databases under the Open Linked Data approach. This will reduce the effort needed by scientists to interpret the sequence alignment results. Conclusions: SALON defines a full range of controlled terminology in the domain of sequence alignments. It can be used as a mediated schema to integrate data from different sources and validate acquired knowledge.
- 27 February 2023
- Published by Springer Nature in BMC Bioinformatics
- Vol. 24 (1) , 1-18
Open AccessSALON ontology for the formal description of sequence alignments
Background: Information provided by high-throughput sequencing platforms allows the collection of content-rich data about biological sequences and their context. Sequence alignment is a bioinformatics approach to identifying regions of similarity in DNA, RNA, or protein sequences. However, there is no consensus about the specific common terminology and representation for sequence alignments. Thus, automatically linking the wide existing knowledge about the sequences with the alignments is challenging. Results: The Sequence Alignment Ontology (SALON) defines a helpful vocabulary for representing and semantically annotating pairwise and multiple sequence alignments. SALON is an OWL 2 ontology that supports automated reasoning for alignments validation and retrieving complementary information from public databases under the Open Linked Data approach. This will reduce the effort needed by scientists to interpret the sequence alignment results. Conclusions: SALON defines a full range of controlled terminology in the domain of sequence alignments. It can be used as a mediated schema to integrate data from different sources and validate acquired knowledge.
- Open Access
- 21 January 2023
- Published by MDPI AG in Applied Sciences
- Vol. 13 (3) , 1447
A Semantic Model for Enhancing Data-Driven Open Banking Services
In current Open Banking services, the European Payment Services Directive (PSD2) allows the secure collection of bank customer information, on their behalf and with their consent, to analyze their financial status and needs. The PSD2 directive has lead to a massive number of daily transactions between Fintech entities which require the automatic management of the data involved, generally coming from multiple and heterogeneous sources and formats. In this context, one of the main challenges lies in defining and implementing common data integration schemes to easily merge them into knowledge-base repositories, hence allowing data reconciliation and sophisticated analysis. In this sense, Semantic Web technologies constitute a suitable framework for the semantic integration of data that makes linking with external sources possible and enhances systematic querying. With this motivation, an ontology approach is proposed in this work to operate as a semantic data mediator in real-world open banking operations. According to semantic reconciliation mechanisms, the underpinning knowledge graph is populated with data involved in PSD2 open banking transactions, which are aligned with information from invoices. A series of semantic rules is defined in this work to show how the financial solvency classification of client entities and transaction concept suggestions can be inferred from the proposed semantic model.
- 21 January 2023
- Published by MDPI AG in Applied Sciences
- Vol. 13 (3) , 1447
Open AccessA Semantic Model for Enhancing Data-Driven Open Banking Services
In current Open Banking services, the European Payment Services Directive (PSD2) allows the secure collection of bank customer information, on their behalf and with their consent, to analyze their financial status and needs. The PSD2 directive has lead to a massive number of daily transactions between Fintech entities which require the automatic management of the data involved, generally coming from multiple and heterogeneous sources and formats. In this context, one of the main challenges lies in defining and implementing common data integration schemes to easily merge them into knowledge-base repositories, hence allowing data reconciliation and sophisticated analysis. In this sense, Semantic Web technologies constitute a suitable framework for the semantic integration of data that makes linking with external sources possible and enhances systematic querying. With this motivation, an ontology approach is proposed in this work to operate as a semantic data mediator in real-world open banking operations. According to semantic reconciliation mechanisms, the underpinning knowledge graph is populated with data involved in PSD2 open banking transactions, which are aligned with information from invoices. A series of semantic rules is defined in this work to show how the financial solvency classification of client entities and transaction concept suggestions can be inferred from the proposed semantic model.
- Open Access
- 27 September 2022
- Published by Elsevier in Expert Systems with Applications
- Vol. 213
e-LION: Data integration semantic model to enhance predictive analytics in e-Learning
- 27 September 2022
- Published by Elsevier in Expert Systems with Applications
- Vol. 213
Open Accesse-LION: Data integration semantic model to enhance predictive analytics in e-Learning
- Open Access
- 1 January 2022
- Published by Elsevier in Expert Systems with Applications
- Vol. 187
Semantic modelling of Earth Observation remote sensing
- 1 January 2022
- Published by Elsevier in Expert Systems with Applications
- Vol. 187
Open AccessSemantic modelling of Earth Observation remote sensing
- Open Access
- 1 November 2021
- Published by Elsevier in Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms
- Vol. 1864 (11-12) , 194766
Formalization of gene regulation knowledge using ontologies and gene ontology causal activity models
- 1 November 2021
- Published by Elsevier in Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms
- Vol. 1864 (11-12) , 194766
Open AccessFormalization of gene regulation knowledge using ontologies and gene ontology causal activity models
- Open Access
- 1 November 2021
- Published by Elsevier in Knowledge-Based Systems
- Vol. 232
TITAN: A knowledge-based platform for Big Data workflow management
- 1 November 2021
- Published by Elsevier in Knowledge-Based Systems
- Vol. 232
Open AccessTITAN: A knowledge-based platform for Big Data workflow management
- Open Access
- 22 January 2020
- Published by MDPI AG in Applied Sciences
- Vol. 10 (3) , 779
An Ontology-Based Framework for Publishing and Exploiting Linked Open Data: A Use Case on Water Resources Management
Nowadays, the increasing demand of water for electricity production, agricultural and industrial uses are directly affecting the reduction of available quality water for human consumption in the world. Efficient and sustainable maintenance of water reservoirs and supply networks implies a holistic strategy that takes into account, as much as possible, information from the stages of water usage. Next,-generation decision-making software tools, for supporting water management, require the integration of multiple and heterogeneous data sources of different knowledge domains. In this regard, Linked Data and Semantic Web technologies enable harmonization of different data sources, as well as the efficient querying for feeding upper-level Business Intelligence processes. This work investigates the design, implementation and usage of a semantic approach driven by ontology to capture, store, integrate and exploit real-world data concerning water supply networks management. As a main contribution, the proposal helps with obtaining semantically enriched linked data, enhancing the analysis of water network performance. For validation purposes, in the use case, a series of data sources from different measures have been considered, in the scope of an actual water management system of the Mediterranean region of Valencia (Spain), throughout several years of activity. The obtained experience shows the benefits of using the proposed approach to identify possible correlations between the measures such as the supplied water, the water leaks or the population.
- 22 January 2020
- Published by MDPI AG in Applied Sciences
- Vol. 10 (3) , 779
Open AccessAn Ontology-Based Framework for Publishing and Exploiting Linked Open Data: A Use Case on Water Resources Management
Nowadays, the increasing demand of water for electricity production, agricultural and industrial uses are directly affecting the reduction of available quality water for human consumption in the world. Efficient and sustainable maintenance of water reservoirs and supply networks implies a holistic strategy that takes into account, as much as possible, information from the stages of water usage. Next,-generation decision-making software tools, for supporting water management, require the integration of multiple and heterogeneous data sources of different knowledge domains. In this regard, Linked Data and Semantic Web technologies enable harmonization of different data sources, as well as the efficient querying for feeding upper-level Business Intelligence processes. This work investigates the design, implementation and usage of a semantic approach driven by ontology to capture, store, integrate and exploit real-world data concerning water supply networks management. As a main contribution, the proposal helps with obtaining semantically enriched linked data, enhancing the analysis of water network performance. For validation purposes, in the use case, a series of data sources from different measures have been considered, in the scope of an actual water management system of the Mediterranean region of Valencia (Spain), throughout several years of activity. The obtained experience shows the benefits of using the proposed approach to identify possible correlations between the measures such as the supplied water, the water leaks or the population.