​

---

Data Working Group

Contact Chairs

---

Chairs: Kedar Narayan and Martyn Winn ​

---

Remit: 
1) Investigate community requirements for data storage, transfer and archiving. 
2) Investigate community requirements for software and data analysis platforms.
3) Promote the development and use of metadata ontologies.
4) Democratise access to data and tools for the whole community.​

Members:
​​Ilya Belevich, Sebastien Besson, Carles Bosch, Rafael Camacho, Lucy Collinson, Michele Darrow,  MC Domart, Ben Giepmans, Sigurður Rúnar Guðmundsson, Matthew Hartley,  Sanja Jasek, Martin Jones, Matúš Kalaš, Bill Katz, Gerard Kleywegt, Bram Koster, Anna Kreshuk, Jurgen Kriel, Ryan Lane, Philip Lewis, Alice Liang, Flavia Moreira-Leite, Constantin Pape, Nadine Randel, Jessica Riesterer, Norman Rzepka, Stephan Saalfeld, Joseph Sall, Yannick Schwab, Martin Schorb, Jason Swedlow, Brock Wester, Simone Weyand, Aubrey Weigel, Michaela Wilsch-Bräuninger, Charlie Wood,           

---

Ongoing projects:
1) We have carried out a community survey on data and software requirements.
2) We are investigating how we can link to and contribute to existing external resources, such as:

• BioImage Informatics Index https://www.biii.eu
• BioImage Model Zoo for AI models  https://bioimage.io
• BIAflows for benchmarking workflows  https://biaflows-sandbox.neubias.org
• AI4LIFE for image data analysis  https://emphasis.plant-phenotyping.eu/european-infrastructures/cluster-projects/ai4life

3) We have an initial ontology for metadata items that should accompany an EMPIAR deposition. We are looking to collate a wide variety of examples to map against this ontology, covering different samples and imaging modalities.

Future projects:
​1) Repository for software tools, workflows, reference datasets, trained machine learning models, etc. The intention is to encourage the sharing of in-house scripts, to improve software engineering, and to reduce the reinvention of wheels.
2) Develop a cloud-based sandbox to enable members of the community to investigate new tools and protocols. This is intended to lower the barrier to the adoption of new techniques and tools, but will not support full data processing.
3) In collaboration with the Training WG, develop training materials for data analysis. Collate and disseminate existing resources. 

---