Skills for Biodiversity Science

Providing the Skills for the Next Generation of Biodiversity Scientists

Fran├žois Michonneau / @fmic_ / iDigBio, FLMNH
Deb Paul / @idbdeb / iDigBio, FSU

## It's a challenging time * increasing anthropogenic pressure on biosphere * decreasing funding/anti-science * complex scientific questions
## It's a challenging time * collaboration faster and easier * computing more powerful * larger dataset easier to obtain and analyze
## It's a challenging time * new skills needed * Scientists recognize they lack bioinformatics skills and want to learn them ![](img/embl_poll.png)
## It's a challenging time * new skills needed * self-taught/"born with it" * yet, can greatly accelerate research
## How to address this disconnect? ![](img/frustration1.png)
## How to address this disconnect? ![](img/happy.jpg)

What to learn?

  1. How to collect data and record metadata?
  2. How to obtain, format, combine large and heterogeneous data?
  3. How to document analysis for reproducibility?
  4. How and where to publish data and analysis alongside the manuscript?
## Who should learn? * Students * Collection managers * PIs * IT staff
## Why learning these skills? * Accelerate science * More robust results * Data management skills * Data re-use (citations)
## Why learning these skills? ![](img/automation.png)
## Where to learn these skills? * Field to Database * Data Carpentry * Data sharing, data standards, and demystifying the IPT * Managing Natural History Collections Data for Global Discoverability (upcoming) * Reproducible Science (upcoming)

Field to Database

Good quality data starts in the field ![](img/field.jpg)
How to clean up your data? ![](img/cleanup.jpg)
How to obtain publicly available data? (API) ![](img/api.png)
When it's clean it can be published ![](img/publishing.jpg)

Data Carpentry

How to use spreadsheets efficiently?
Basics of working with data (R or Python)
* Data visualization * or other topics: text mining, HDF5, etc.
* Sister organization of Software Carpentry * No programming knowledge required * Request a workshop at your institution!

Reproducible Science

What is reproducibility? Why do you/we need it?
How to organize your research projects to make them reproducible?
Getting started with litterate programming
How to automate your workflow?
How and where to publish your research artifacts?
## The workshop model * pre- and post-workshop survey + feedback * good planning * competent instructors and helpers * testing of software/material/exercises in advance * teaching material open and easily accessible via GitHub * **CODE OF CONDUCT**
## Get involved