Research data management is becoming increasingly important in the scientific community. A critical challenge in this field is making research data FAIR (findable, accessible, interoperable and reusable, Wilkinson et al. 2016). Metadata plays a vital role in this challenge as it allows researchers to accurately understand and recreate experiments. To tackle this challenge, various approaches are being taken towards this goal, including the development of domain-overarching and domain-specific standards.
In the plant science community, multiple domain-specific minimal information standards have been developed, such as MIAPPE, MIAME and MINSEQE. These standards are designed to describe specific types of experiments. Recently, a minimal standard for single-cell experiments, minSCe (minimal information about a single-cell experiment), has been introduced (Füllgrabe et al. 2020). However, it is not yet widely used.
While minimal standards are important, they are only part of the solution. The use of controlled vocabularies and ontology terms is also essential. Ontology terms have a persistent identifier, an expressive name and a curated definition. Using these terms enables different researchers to understand and recreate annotated experiments. In this project, we propose to expand biological and technical metadata schema as well as ontologies for single-cell experiments across domains with a focus on transcriptomics. This will facilitate the sharing and reuse of single-cell data and promote collaboration among researchers in different domains. Our goal is to improve data management practices and enhance the reproducibility of single-cell research.
Our project is built on our expertise in the single-cell omics field, which is part of the larger ELIXIR community, as well as on our experiences working with plant-related ontologies. Both topics have previously been worked on during the BioHackathon Germany.
By combining our knowledge and making use of available public datasets such as from the Single-Cell Expression Atlas and the Human Cell Atlas, we expect to be able to reach our primary goals of creating a minSCe ontology and testing the model for different datasets. On site, we would also like to consult the ISA community regarding the conversion from the minSCe MAGE-tab format to ISA, in order to work towards our goal of creating a robust mapping between the two formats.
- required: 5
- maximum: 10
Participant minimum requirements: knowledge about ISA, MAGE-tab, minSCe, ontologies (OWL, OBO), plant sciences
Hannah Dörpholz, Stefania Giacomello, Naveed Ishaque