GLOBAL LIGHT COMMONS – MICRO-GRANT PROGRAMME
The Global Light Commons is a new open infrastructure and sharing platform for light exposure and visual experience data, developed by the Translational Sensory & Circadian Neuroscience Unit (Max Planck Society / Technical University of Munich / TUMCREATE).
The overarching goal of the Global Light Commons is to bring together heterogeneous light-related datasets in a FAIR manner – Findable, Accessible, Interoperable, and Reusable – with a strong emphasis on harmonised data structures, metadata and metrics to enable cross-study and cross-region analyses.
As part of the Global Light Commons, we are launching a micro-grant programme to support targeted activities that contribute data and expertise to the platform. Funding is offered under two complementary tracks:
EUR 3,000
- Capturing light exposure and/or visual experience data in under-represented regions
- Harmonising newly collected datasets to open, shared standards
- Enabling global reuse of data through structured metadata and documentation
EUR 1,500
- Mapping legacy or proprietary formats to Global Light Commons standards
- Improving metadata quality and interoperability
- Preparing datasets for open sharing and long-term reuse
What We Support
Micro-grants may be used for activities such as:
- Data curation and restructuring
- Metadata development and documentation
- Harmonisation to agreed-upon metrics and schemas
- Preparation of datasets for FAIR sharing
The programme is explicitly designed to lower barriers to participation, recognise the value of data stewardship work, and accelerate the creation of a globally inclusive, interoperable resource for light exposure and visual experience research.
Eligibility Criteria
Applications are welcome from individuals or teams that meet the following criteria:
Applicant profile
- Researchers, data scientists, practitioners, or institutions working with light exposure and/or visual experience data
- Applicants may be based anywhere globally; LMIC-based applicants are particularly encouraged under Track 1
- Early-career researchers and teams with limited access to infrastructure are explicitly eligible
Data relevance
- Proposed activities must involve light exposure and/or visual experience data relevant to human environments (e.g. natural, built, occupational, clinical, or everyday settings)
- Datasets may be newly collected (Track 1) or pre-existing (Track 2)
Commitment to open science
- Applicants must commit to aligning datasets with the FAIR principles
- Resulting datasets must be prepared for open sharing via the Global Light Commons or a compatible open repository, subject to ethical and legal constraints
Ethics and governance
- Applicants are responsible for ensuring appropriate ethical approvals, consent, and compliance with local and international data protection regulations
- Data involving human participants must be shared in a de-identified or appropriately governed form
Evaluation Principles
Proposals will be evaluated according to the following principles, with an emphasis on data value and reusability rather than project scale:
Contribution to the Global Light Commons
- Degree to which the proposed work increases the coverage, diversity, or usability of the shared data resource
- Relevance to under-represented regions, populations, or environments
Data harmonisation & FAIR alignment
- Clarity and feasibility of the proposed harmonisation approach
- Quality and completeness of metadata, documentation, and standards alignment
- Expected interoperability with existing datasets in the Global Light Commons
Technical and methodological soundness
- Appropriateness of data collection methods (Track 1) or curation strategies (Track 2)
- Realistic and well-scoped use of micro-grant funds
Open science & reuse potential
- Likelihood that the resulting dataset will be reusable by a broad research community Transparency of methods, assumptions, and limitations
Capacity building & equity (where applicable)
- Contribution to local capacity building, especially in LMIC contexts
- Evidence that the micro-grant meaningfully lowers barriers to participation in global data sharing efforts
Apply Before 30 April 2026
Submit your application through the appropriate track link below. Applications are reviewed on a rolling basis.
Contact
Community Manager - Erina Tsukimori
e.tsukimori@tum.de
