Overview of Belmont Forum CRA (Collaborative Research Action) “Science-driven e-Infrastructures Innovation” and its Evaluation

1. Aims of the Program

The impact of environmental change research and data it produces can be dramatically increased through a transnational approach to critical technological and procedural barriers within the scientific community. In order to accelerate scientific discoveries and socioeconomic innovation, exponential increases in diversity, volume and throughput of cross-border, multidisciplinary data in environmental sciences demand delivery mechanisms that allow these data to be more easily findable, accessible, interoperable, and reusable for research, and that facilitate their sustainable curation and preservation for the benefit of future generations.

Opportunities to apply computer science and technology as well as large and complex data sets to interdisciplinary and transdisciplinary science are increasing. It is therefore critically important to establish and enable transnational frameworks so that data-driven scientific knowledge can transcend disciplines and geographical borders, ultimately increasing the scientific underpinnings of policy and action. International collaboration within Belmont Forum priority research fields holds the potential to establish international foundations for federated data integration and analysis systems with shared services, bring together best practices from the public and private sectors, foster open data and open science stewardship among the science communities including related areas such as publishing, and encourage data and cloud providers and others to adopt common standards and practices for the benefit of all.

For these reasons, the Belmont Forum is launching a 4-year competitive call for projects as part of its Collaborative Research Action (CRA) on Science-driven e-Infrastructure Innovation (SEI) for the Enhancement of Transnational, Interdisciplinary and Transdisciplinary Data Use in Environmental Change.

2. Target research field

This SEI call targets initiatives that are well-positioned to bring together environmental, social and economic scientists with data scientists, computational scientists, and e-infrastructure and cyber-infrastructure developers and providers to solve one or more of the methodological, technological and/or procedural challenges currently facing inter-disciplinary and transdisciplinary environmental change research that involves working with large, diverse and multi-source transnational data. The SEI call will intimately link research thinking and technological innovation toward accelerating the full-path of discovery-driven data use and open science, and enable a broader scientific community to benefit from the identified new and potentially disruptive demonstrators or pilots toward solutions.

The Key features of this call

• Science-driven. Projects should aim to develop innovative demonstrators and pilots that enable the use of transnational multi-source data and enhance interdisciplinary and/or transdisciplinary environmental change research. They must specifically identify tangible research questions and objectives that will benefit from the proposed solutions.
• Transnational and Collaborative. Projects should clearly demonstrate the added value of the international partnership and outline the role of each partner in the project workplan. Projects should involve mutually dependent collaboration between and among domain scientists and computer and data scientists, as well as possibly e- and cyberinfrastructure developers and providers, linking research thinking and technological innovation to solve well-identified, experience-based methodological and/or technological issues and barriers in transnational data use.
• Interdisciplinary and/or Transdisciplinary. Great premium will be placed on interdisciplinary and transdisciplinary research-driven initiatives with an emphasis on co-design, co-development and sharing within and across disciplines enabling open data and open science all along the full path of data use.
• Problem Solving and Translatable. Projects are expected to deliver and share innovative demonstrators and pilots and open software that smooth the path from theoretical research through proof of concept to usable and effective solutions that are translatable and relevant to the wider scientific community for a sustained impact on research practices. Projects targeting specific segments along the full path of data use in a well-described science-driven context should demonstrate how this will accelerate the rates at which information is gleaned from data and impact the Belmont Forum research challenges.

The SEI call emphasizes ‘going the last mile’ with data: not only uncovering evidence that support scholarly observations, but also distilling and collating the evidence into forms that can be used routinely in research across disciplines so that these data are available in a form useful to help inform decision-making in a transdisciplinary context.

3. Participating countries

State of São Paulo (Brazil), Chinese Taipei, France, Japan and the United States of America

4. Eligibility

The following were eligible to receive support through this call:

• Persons affiliated with a domestic research organisation where they are able to conduct research
• Persons without a history of accounting irregularities which would restrict their eligibility to apply

5. Research Period

4 years

6. Amount of Funding (including indirect costs)

Up to JPY 8 million per project per year

7. Evaluation Process

Evaluation of proposals was conducted by an international Panel of Experts nominated by the Belmont Forum member organizations taking part in this joint call. The participating funding organizations then met to discuss the outcome of that evaluation and jointly decided on the projects to select for funding.

8. Evaluation Criteria

The following criteria were applied in evaluation of each proposal:

I. Quality/ /Intellectual Merit

• Scientific excellence and progress beyond the state-of-the art
• Clarity of the objectives and of the research hypotheses
• Quality and effectiveness of the scientific/technological strategy, the data collection and the associated work plan
• Added value to be expected from the international research collaboration

II. Relevance to Call

• Adequacy of the project regarding call strategy and topics set forth in the call text
• Relevance of the deliverables to the broader scientific community
• Open data policy and strategy toward open science

III. Quality of the Consortium

• Competence, and expertise of the Leading Principal Investigator (LPI)
• Quality of the consortium as a whole (including the level of complementarity)
• Quality of the inter- and/or transdisciplinary research and implementation strategy

IV. Resources and Management

• Appropriate allocation and justification of the resources (budget, staff, equipment)
• Quality and efficiency of the project management structure and procedures
• Quality of the data management plan and data stewardship strategy
• Strength of cooperation between the partners of project