/multidim-biodiv-data

Repository for curriculum development for the multidimensional biodiversity data workshop.

Primary LanguageROtherNOASSERTION

Multi-dimensional Biodiversity Data

Biodiversity researchers must work with an array of data types, including community composition and abundance information, trait, phylogenetic and genetic data. Traditionally, studies in ecology and evolution have worked with only one or a few of these data types. To successfully advance the study of biodiversity across different levels of organization, biodiversity scientists are nonetheless finding the need to integrate multiple of these disparate data types into the same analytical workflow. This workshop will promote learning in the use of multidimensional data streams, gathering biodiversity scientists and students from different sub-disciplines to help facilitate integrative, cross-specialization research.

Goals of the Workshop: This two-day workshop will introduce different data types used by biodiversity scientists in an integrative framework. We will cover common approaches for working with abundance, trait, phylogenetic, and genetic data separately, and proceed to methods for working with multiple dimensions of biodiversity data simultaneously. Finally, we will explore motivations and platforms for archiving, sharing, and accessing multidimensional biodiversity datasets as part of the wider scientific community (e.g. GEOME).

Target Audience: We welcome senior undergrads with interest or experience in Ecology and Evolution, graduate students at any stage, and postdocs and PIs with an interest in expanding their skill set towards working with new-to-them data types. Some computational skills may be helpful (e.g. familiarity with R and at least one type of biodiversity data), but we expect that most participants will have little to no familiarity with at least some of the data types we work with. We especially welcome scientists and student-scientists from groups traditionally excluded from the biodiversity and computer sciences, including (but not limited to) women, Latinx, Black, Native American, LGBTQIA+, and scientists with disabilities.

Core Contributers

  • Renata Diaz
  • Connor French
  • Jacob Idec
  • Rilquer Mascarenhas
  • Isaac Overcast
  • Andy Rominger

Funding Support

We gratefully acknowledge funding support from NSF awards DBI-2208901 to Renata Diaz and DBI-2104147 to the RoLE model team