D4Science is a federated digital infrastructure designed to advance open science practices through enhanced collaboration and data-driven discovery. A key strength of D4Science lies in its translational capability — transforming research outputs into practical solutions that address pressing societal challenges. Our core research agenda focuses on pushing the boundaries of collaborative methodologies, fostering rigorous reproducibility, and facilitating innovative scientific workflows that transcend traditional disciplinary boundaries. We address key research challenges through the following core themes:
- Virtual Research Environments (VREs): Tailored Collaborative Spaces for Research Innovation
- Challenge: Balancing the need for flexible and customisable research environments with the requirement for policy-driven data sharing and access control, ensuring the specific needs of diverse research communities are met.
- D4Science Research Solution: We conduct research on and develop tailored Virtual Research Environments (VREs) as a foundational mechanism for managing policies and authorisations, enabling community-specific governance within collaborative spaces. These web-based, community-oriented workspaces are designed to support cutting-edge research and are equipped with the necessary tools, datasets, and services tailored to their communities' unique research requirements. Our research on VREs focuses on enhancing collaboration, optimising resource utilisation, and streamlining the sharing of research outputs.
- Open Science Enabling Technologies: Researching Transparent and Accessible Science
- Challenge: Fragmented research resources hinder open access and reuse of research outputs, impeding scientific progress.
- D4Science Research Solution: Our research explores and develops technologies that drive the adoption of open science principles, ensuring research outputs are accessible, reusable, and transparent, contributing to a more inclusive and equitable scientific ecosystem. D4Science's research on open and collaborative cyberinfrastructure fosters co-creation and seamless integration of third-party services and applications, ensuring continuous evolution and responsiveness to the dynamic needs of the global research community.
- Innovative Solutions for Research Data Publishing and FAIRness: Researching for Maximized Data Impact
- Challenge: Overcoming challenges in research output visibility and accessibility, ensuring data is findable, accessible, interoperable, and reusable (FAIR).
- D4Science Research Solution: Our research investigates and develops innovative solutions to enhance research data publishing, with a strong emphasis on FAIR principles to maximise the impact and usability of scientific data. Our research on the D4Science Catalogue focuses on improving discoverability, interoperability, and long-term preservation of research outputs through actionable, persistent, and unique identifiers, persistent storage, licensing, and rich, customisable metadata.
- Data Analytics and Processing at Scale: Researching Big Data Insights
- Challenge: Effectively exploiting cutting-edge technologies like distributed computing, parallel processing, and advanced algorithms for large-scale data analysis in research contexts.
- D4Science Research Solution: Our research focuses on designing and developing solutions that facilitate the exploitation of these technologies for research purposes, empowering researchers to uncover meaningful patterns, derive actionable insights, and accelerate decision-making through user-friendly analytical environments and tools, including JupyterLab, RStudio, Galaxy, integrated with the Cloud Computing Platform (CCP).
- AI-based Solutions for Advanced Scientific Challenges: Researching AI for Science
- Challenge: Tackling increasingly complex research problems requiring advanced computational approaches, including AI and Machine learning techniques.
- D4Science Research Solution: Our research explores and develops the application of artificial intelligence to address complex research challenges, from predictive modelling to automated pattern recognition and beyond, contributing to the advancement of scientific knowledge.
- Interoperability and Integration: Researching Seamless Data Exchange
- Challenge: Ensuring interoperability between diverse systems to facilitate smooth data exchange and efficient research workflows, a critical aspect of collaborative research.
- D4Science Research Solution: Our research focuses on developing solutions that champion interoperability by creating mechanisms for seamless integration of diverse systems, using open standards and protocols to ensure different tools and services can interact effectively. Our research on the unified storage infrastructure across all services and VREs further enhances data sharing and workflow integration.
- Infrastructure Reliability and Observability: Researching for Continuous Access to Resources
- Challenges: Minimizing downtime and ensuring uninterrupted access to critical research resources; developing methodologies for providing real-time insights into infrastructure performance for proactive maintenance and optimisation.
- D4Science Research Solution: Our research investigates methods to enhance the reliability and robustness of infrastructure systems, minimising downtime, and developing advanced observability and monitoring tools to provide real-time insights into infrastructure performance.
- Cloud Computing and Resource Management: Researching Scalable and Efficient Resources
- Challenge: Meeting the growing demands of modern research for scalable and efficient resource management solutions.
- D4Science Research Solution: Our research explores and develops cloud computing strategies to deliver these solutions, supporting the dynamic needs of research projects. This research informs the development of the distributed architecture that integrates external systems for data storage and cloud-based computational resources into a unified virtualised space, providing tailored, on-demand services accessible through VREs.
Selected papers
Overall
L. Candela, D. Castelli, P. Pagano (2023) The D4Science Experience on Virtual Research Environment Development. Comput. Sci. Eng. 25(2): 12-19 https://doi.org/10.1109/MCSE.2023.3290433
M. Assante, L. Candela, D. Castelli, R. Cirillo, G. Coro, A. Dell'Amico, L. Frosini, L. Lelii, M. Lettere, F. Mangiacrapa, P. Pagano, G. Panichi, T. Piccioli, F. Sinibaldi (2023) Virtual research environments co-creation: The D4Science experience. Concurr. Comput. Pract. Exp. 35(18) https://doi.org/10.1002/cpe.6925
M. Assante, L. Candela, D. Castelli, R. Cirillo, G. Coro, L. Frosini, L. Lelii, F. Mangiacrapa, P. Pagano, G. Panichi, F. Sinibaldi (2019) Enacting open science by D4Science. Future Gener. Comput. Syst. 101: 555-563 https://doi.org/10.1016/j.future.2019.05.063
Community experiences
M. Assante, A. Boizet, L. Candela, D. Castelli, R. Cirillo, G. Coro, E. Fernández, M. Filter, L. Frosini, T. Georgiev, G. Kakaletris, P. Katsivelis, R. Knapen, L. Lelii, R. M. Lokers, F. Mangiacrapa, N. Manouselis, P. Pagano, G. Panichi, L. Penev, F. Sinibaldi (2021) Realizing virtual research environments for the agri-food community: The AGINFRA PLUS experience. Concurr. Comput. Pract. Exp. 33(19) https://doi.org/10.1002/cpe.6087
L. Candela, M. Stocker, I. Häggström, C.-F. Enell, D. Vitale, D. Papale, B. Grenier, Y. Chen, M. Obst (2020) Case Study: ENVRI Science Demonstrators with D4Science. Towards Interoperable Research Infrastructures for Environmental and Earth Sciences: 307-323 https://doi.org/10.1007/978-3-030-52829-4_17
R. Amaral, R. M. Badia, I. Blanquer, R. Braga-Neto, L. Candela, D. Castelli, C. Flann, R. De Giovanni, W. A. Gray, A. C. Jones, D. Lezzi, P. Pagano, V. Perez Canhos, F. Quevedo, R. Rafanell, V. E. F. Rebello, M. S. Sousa-Baena, E. Torres (2015) Supporting biodiversity studies with the EUBrazilOpenBio Hybrid Data Infrastructure. Concurr. Comput. Pract. Exp. 27(2): 376-394 https://doi.org/10.1002/cpe.3238
Services
L. Candela, D. Castelli, G. Coro, P. Pagano, F. Sinibaldi (2016) Species distribution modeling in the cloud. Concurr. Comput. Pract. Exp. 28(4): 1056-1079 https://doi.org/10.1002/cpe.3030