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[EN] Goal-oriented requirements engineering promotes the use of goals to elicit, elaborate, structure, specify, analyze, negotiate, document, and modify requirements. Thus, goal-oriented specifications are essential for capturing the objectives that the system to be developed should achieve. However, the application of goal oriented specifications into model-driven development (MDD) processes is still handcrafted, not aligned in the automated flow from models to code. In other words, the experience of analysts and designers is necessary to manually transform the input goal-oriented models into system models for code generation (models compilation). Some authors have proposed guidelines to facilitate and partially automate this translation, but there is a lack of techniques to assess the adequacy of goal-oriented models as starting point of MDD processes. In this paper, we present and evaluate a verification approach that guarantees the automatic, correct, and complete transformation of goal-oriented models into design models used by specific MDD solutions. In particular, this approach has been put into practice by adopting a well-known goal-oriented modeling approach, the i* framework, and an industrial MDD solution called Integranova. ; This work has been developed with the support of FONDECYT under the projects AMoDDI 11130583 and TESTMODE 11121395.This work is also supported by EOSSAC project, funded by the Ministry of Economy and Competitiveness of the Spanish government (TIN2013-44641-P). ; Giachetti Herrera, GA.; Marín, B.; López, L.; Franch, X.; Pastor López, O. (2017). Verifying goal-oriented specifications used in model-driven development processes. Information Systems. 64:41-62. https://doi.org/10.1016/j.is.2016.06.011 ; S ; 41 ; 62 ; 64

41 62 64 ; S ; [EN] Goal-oriented requirements engineering promotes the use of goals to elicit, elaborate, structure, specify, analyze, negotiate, document, and modify requirements. Thus, goal-oriented specifications are essential for capturing the objectives that the system to be developed should achieve. However, the application of goal oriented specifications into model-driven development (MDD) processes is still handcrafted, not aligned in the automated flow from models to code. In other words, the experience of analysts and designers is necessary to manually transform the input goal-oriented models into system models for code generation (models compilation). Some authors have proposed guidelines to facilitate and partially automate this translation, but there is a lack of techniques to assess the adequacy of goal-oriented models as starting point of MDD processes. In this paper, we present and evaluate a verification approach that guarantees the automatic, correct, and complete transformation of goal-oriented models into design models used by specific MDD solutions. In particular, this approach has been put into practice by adopting a well-known goal-oriented modeling approach, the i* framework, and an industrial MDD solution called Integranova. This work has been developed with the support of FONDECYT under the projects AMoDDI 11130583 and TESTMODE 11121395.This work is also supported by EOSSAC project, funded by the Ministry of Economy and Competitiveness of the Spanish government (TIN2013-44641-P). Giachetti Herrera, GA.; Marín, B.; López, L.; Franch, X.; Pastor López, O. (2017). Verifying goal-oriented specifications used in model-driven development processes. Information Systems. 64:41-62. https://doi.org/10.1016/j.is.2016.06.011

[EN] Precision medicine has emerged as a disrupting medical model to transform a historically reactive medicine into a proactive one that focuses on delivering individualized treatment. A relevant challenge of precision medicine is to integrate the large amount of omics data that exists. This data has a high degree of heterogeneity, dispersion, and isolation. In addition, there is a lack of a solid ontological commitment regarding domain concepts and definitions, and a unified guideline of how to transform data into knowledge is missing. In this work, we report our experience applying conceptual modeling to deal with these challenges in a specific genomics dimension, i.e., Precision Medicine. To do so, we have applied conceptual modeling techniques. The use of these techniques allows us to create representations of the world (i.e., conceptual schemes) that can be used for the purposes of understanding, communicating, and problem-solving. They also help to establish a common ontological framework to facilitate both communication and knowledge evolution in complex domains. We identify a set of limitations that emerged after working in a precision medicine context, and we describe how we have solved them using conceptual modeling. Thus, the main contribution of this work is to present the subsequent Conceptual Schema that allowed us to overcome these limitations, which provides a better representation of proteomics data and eases its integration. ; This work was supported in part by the Spanish State Research Agency and the Generalitat Valenciana under Project PROMETEO/2018/176, Project PDC2021-121243-I00, and Project INNEST/2021/57; and in part by the European Regional Development Fund (ERDF) and the European Union NextGenerationEU/PRTR. ; García-Simón, A.; León-Palacio, A.; Reyes Román, JF.; Casamayor Rodenas, JC.; Pastor López, O. (2021). A Conceptual Model-Based Approach to Improve the Representation and Management of Omics Data in Precision Medicine. IEEE Access. 9:154071-154085. ...