Phenoscape TraitFest 2023 - Call for Participants - Due November 7
Jennifer C. Girón Duque
Dear all,
We invite you to participate in the Phenoscape / SCATE (Semantics for Comparative Analysis of Trait Evolution) TraitFest 2023 at RENCI in Chapel Hill, North Carolina. Phenoscape uses semantics and structured knowledge to increase trait discovery for comparative trait analyses. The goals of this hackathon are to introduce the Phenoscape knowledge base for trait discovery, develop tools and workflows to enable participation, cultivate collaboration, and brainstorm ways to incorporate machine learning into trait-based analyses. This year, we are specifically seeking those with knowledge in invertebrate traits to expand the scope of Phenoscape. More information about the event’s background, motivation, and goals can be found in the Call for Participants for TraitFest 2023.
If you are interested, please let us know by filling out the TraitFest 2023 Application for Participation by the end of November 7, 2022.
Please share with potentially interested colleagues.
Synopsis of Phenoscape TraitFest 2023:
The Phenoscape Knowledgebase contains morphological traits across fishes and the vertebrate fin-limb transition linked to terms drawn from formal ontologies representing domain knowledge about anatomical elements and their interrelationships in a fully computable form. This event aims to promote innovative applications adopting the capabilities conveyed by the data and corresponding semantics-enabled algorithms, by engaging, in a hands-on way, potential users of and contributors to this data, as well as developers of methods in comparative phylogenetics and other fields who can use such data and algorithms. In particular, the event aims to include users whose research questions and/or datasets stand to benefit from being afforded the same computable semantics-based capabilities, whose taxonomic communities have already developed the necessary baseline infrastructure of supporting data and ontologies, such as the insects, spiders, and plant research communities, and those interested in developing tools or workflows, especially those using machine learning.
Looking forward to hear from you,