NNF Data Science Research Infrastructure Grant 2021

Description of application

Key bits of information were taken from the full description from the links below:

Key points and takeaways

  • State of the art
  • Computational and database infrastructures
  • Openness, transparency, and FAIR principles
  • Data engineering/infrastructure necessary for research
  • Qualifications of all involved (staff, collaborators) for continued maintenance
  • Funding for highly skilled personnel (e.g. technical, computational skills)
  • Boost research, including in companies that might not be able to invest in this
  • Education and training

Purpose and overall description

The Data Science Research Infrastructure Programme aims to create bottom-up opportunities for open, national data science infrastructures, which are critical for achieving excellent data science driven research in Denmark. Such infrastructure is in this context defined as computational infrastructures, databases and data resources, and data-generating technologies.

The programme also aims to:

  • Strengthen education and training in data science.
  • Ensure that facilities are continuously developed and maintained, also after their implementation.
  • Boost the research environment, including companies (e.g.,small and medium-sized enterprises (SMEs) and incubators), that cannot invest in this to the same extent.

Infrastructure must state-of-the-art and is defined as:

  • Computational infrastructures, including supercomputers, GPUs, storage, software, etc.
  • Databases and data resources, including data collection, cleaning, annotation, integration, management, etc.
  • Includes building and maintenance of existing databases if it promotes collaboration and FAIR (Findable, Accessible, Interoperable, Reusable) principles, as well as secure and ethical use of such data.

Assessment criteria

  1. Scientific need for the infrastructure (locally and nationally). 2. State-of-the-art of the requested equipment and how widespread its use will be.
    1. Short explanation of criteria: For projects mainly concerned with data science methods development, it is important that the applicants clearly show the relevance for potential future application and impact within life science, health science, or biotechnology. Vice versa, projects which have their primary focus on application of data science methods must describe and explain the novelty and impact of their data science approach, be it development of novel methods or novel applications of existing methods.
  2. Scientific and managerial qualifications of the applicant. 4. Scientific qualifications of core collaborators. 5. Feasibility and suitability of the proposed organizational set up for the infrastructure, including expected use and maintenance.
    1. Short explanation of criteria: Feasibility and suitability of the proposed organizational set up for the infrastructure, including expected use and maintenance.
  3. Coordination with and/or relevance for other Danish research groups. 7. Plan for accessibility to the infrastructure for the local and national research community, including internal, external and industrial users, as well as a clear plan for how to grant access in an open and transparent manner for external users.
    1. Short explanation of criteria: The infrastructure should be shared with the national research community. Priority for funding will be given to applications that demonstrate coordination with other Danish research groups.
  4. The applicant’s and/or collaborators’ plan to actively participate in, and direct, educational or training courses in data science in Denmark, leveraging on the proposed infrastructure.

Areas of support

The infrastructure must be linked to ongoing research and be within the scope of the NNF Data Science Initiative:

  1. Development of new … methods and technologies within data science, …, data engineering, …

For projects mainly concerned with data science methods development, it is important that the applicants clearly show the relevance for potential future application and impact within life science, health science, or biotechnology.

Eligibility

  • Infrastructure linked to ongoing research and applicants must document expertise at the highest level.
  • Must be established at a research institution with expertise within the relevant field to ensure that the infrastructure can develop in parallel with the scientific progress in the area, and that there are qualified personnel to operate and maintain the equipment/facility.
  • Infrastructure should be shared with the national research community. Priority for funding will be given to applications that demonstrate coordination with other Danish research groups.
  • Applications to maintain or expand existing infrastructures are eligible.
  • Funding may be requested for skilled technical staff that can offer research-based training, consultation, data processing, data analysis, data management, software/database development, and dissemination of data/tools.

Funding

DKK 1-3 million on average per year over 5 years, for a total of DKK 5-15 million. Can apply for skilled personnel anchored in a specific institution and linked to ongoing research, as well as for personnel that can offer research-based training, consultation, data processing, data analysis, data management, software/database development, and dissemination of data/tools.

Project application details

  • Grant period: Start and end dates

  • Project title: Short title, maximum 150 characters

  • Brief project description: Brief stand-alone summary of project, describing its purpose, target group, and activities. Max 2000 characters, including spaces, line breaks and special characters

  • Project description:

    • Max 30,000 characters, including spaces, line breaks and special characters. Include purpose, background, methods, collaborations, and significance of the project. Plus 4 figures/diagrams.
    • Clearly describe how the infrastructure will support and strengthen data science research and education in Denmark.
    • Describe how the proposal compares to, supplements, and aligns with current national landscape and relevant future national strategies and initiatives, since the evaluation committee will be purely international.
    • Address:
      • The scientific need, including a mapping of similar, existing infrastructures in Denmark, assessment of the timeliness of the infrastructure, and how it differs from those available in Danish research environments.
      • The scientific and technical expertise within the relevant field at the institution where the infrastructure will be established.
      • How the technical expertise will be obtained to ensure qualified operation and maintenance of infrastructure, as well as instruction of new and experienced users.
      • The potential users of the infrastructure, including core collaborators and other relevant users. Should provide an estimate of the distribution of expected use by the applicant, core users, and external users.
      • A clear plan for how the infrastructure will be made available for a wider group of scientists from, e.g., other research institutions, SME’s (companies), or incubators, including communication and outreach activities, access criteria, and possible payment schemes for external users. Priority for funding will be given to applications that demonstrate coordination with other Danish research groups. Open access is encouraged.
      • A clear plan for data management (storage, databases, handling and processing of data using cloud/edge/fog computing, etc.).
      • The organisation of the infrastructure, including a timeline for establishment, running and maintenance of the infrastructure and a description of a steering committee and its responsibilities.
      • A business plan describing how the infrastructure will be embedded, used, maintained, and financed during and after the grant has ended.If possible, please provide relevant key performance indicators.
      • In case of user fees for using the infrastructure, make sure to describe how the income from such sources will be used during and after the grant period. For instance, if the funds will be used to upgrade, maintain, expand, etc.,the infrastructure.
      • A plan for how the main applicant and/or core collaborators plan to actively participate in and direct educational or training courses in data science in Denmark, leveraging the proposed infrastructure.
      • Permits from public authorities needed to establish the infrastructure, if relevant. Abbreviations should be defined at the first use, and preferably a list of abbreviations should be included in the project description.

  • Literature references: Please provide the reference information for the literature cited in the project description (maximum 4,000 characters, including spaces, line breaks and special characters).

  • Lay project description: Please provide a brief summary for non-experts in lay language. If the application is awarded a grant, the text may be used for publication (in English, maximum 1,000 characters, including spaces, line breaks,and special characters).

  • Budget: Applicants may apply for funding for the following types of expenses when directly related to the project:

    • Equipment, i.e., purchase of equipment for the infrastructure. This is not necessarily a single piece of equipment but can be several that cover different aspects of the same field or can be equipment that is often used sequentially. However, the intent is that only larger equipment should be put in the equipment budget category.
    • Infrastructure, i.e.,establishment and installation of the infrastructure. This may include minor modifications strictly necessary for establishing and operating the infrastructure.
    • Operating expenses, e.g.:
      • Materials, consumables, and service contracts directly related to operating and maintaining the infrastructure.
      • Funds for hosting annual networking/outreach events.
      • Specialised software needed for the infrastructure.
    • Salary for technical personnel (i.e. AC TAP or TAP). These can also offer research-based training, consultation, data processing, data analysis, data management, software/database development, and dissemination of data/tools. Salary can be used for personnel with an academic background but not for conducting research.
    • Training for running and maintaining the infrastructure, including travel and accommodations.
    • Data management, e.g. expenses for collecting and storing data.
    • Direct administrative expenses of up to 5% of the total funding:
      • Such as for accounting, payment of salaries, purchasing, hiring, auditing, and financial reporting on the project.
      • Cannot cover administrative expenses not directly related to the project.