There are emerging concerns in biomedical science regarding the limited success in reproducing research data and translating them into applications. This scenario is a major problem for academic science as well as for the economy and the society at large which benefit from research findings. Excluding fraud, the reasons for this might be found in the lack of identification and application of standards, poor description and sharing of data, protocols and procedures, and underdevelopment of quality control activities. Driven by stakeholders and scientific networks, several attempts to face the reproducibility crisis have been initiated. In this chapter we discuss the actions implemented into the academic research environment, as well as the difficulties encountered due principally to the limitation of resources. Our aim is to highlight how the identification and adoption of best practice for Quality and Data Management are key issues in this battle, and to propose a roadmap for their implementation, based on the involvement of all the interested actors, such as the academic community, research agencies and government programs.
Towards the definition of common strategies for improving reproducibility, standardisation, management, and overall impact of academic research
Domenica D'EliaMembro del Collaboration Group
;Annamaria Kisslinger;Giovanna L. Liguori
2022
Abstract
There are emerging concerns in biomedical science regarding the limited success in reproducing research data and translating them into applications. This scenario is a major problem for academic science as well as for the economy and the society at large which benefit from research findings. Excluding fraud, the reasons for this might be found in the lack of identification and application of standards, poor description and sharing of data, protocols and procedures, and underdevelopment of quality control activities. Driven by stakeholders and scientific networks, several attempts to face the reproducibility crisis have been initiated. In this chapter we discuss the actions implemented into the academic research environment, as well as the difficulties encountered due principally to the limitation of resources. Our aim is to highlight how the identification and adoption of best practice for Quality and Data Management are key issues in this battle, and to propose a roadmap for their implementation, based on the involvement of all the interested actors, such as the academic community, research agencies and government programs.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


