Workshop: Vector spatial data in R [Wednesday February 10]

Next week’s event will be a workshop, not a roundtable. The workshop will be led by Casey O’ Hara at NCEAS. We will have facilities for remote participation for those who’d like and/or if we run out of space at the NCEAS conference room.
Please RSVP to attend and get follow-up emails.
Vector spatial data in R

GIS is a useful tool for viewing spatial data and creating maps, but R can do a lot of the heavy lifting when it comes to analyzing your spatial data.  We will focus on vector spatial data in this workshop (polygons, lines, points) but also touch on raster spatial data, building upon the raster workshop led by Jamie last fall.  Please RSVP by filling out this google form, so we can send you a follow up e-mail with further instructions to set up your laptop.  Newbies and experts are all welcome.

Some things we will look at; if you have specific questions please feel free to send them in advance (e-mail or on the RSVP form):

  • reading and writing vector spatial data (shapefiles and geodatabases)
  • projecting and displaying vector spatial data (incl. mapping in ggplot)
  • understanding the structure of R spatial polygon objects so we can take them apart, analyze them, modify them, and put them back together again.
  • using basic geoprocessing tools in R to manipulate geometry, e.g. intersect, difference, area, buffer, etc.
  • working with polygons and rasters together
  • checking and repairing geometries (beware of orphan holes!)

Please bring a laptop if you can, so we can work through the examples together.  You can find the materials (scripts, data, and workshop notes) here:  Clone or fork the repository (if you’re a GitHub person) or download the zip file (button on right, above the list of files).

We’ll send a followup e-mail to attendees with a to-do list of things to set up ahead of time, including software and R packages you might need to install or update.  Please make sure to RSVP!

Do synthesis centers produce novel, potentially transformative research? Research publication diversity as an indicator of novelty and transformative capacity


a few of the topics that emerged in our analysis

For this Roundtable, I will present a poster that I presented at the recent AAAS meeting in San Jose. The project is an outgrowth of a working group jointly supported by NCEAS and NESCent and led by Ed Hackett and John Parker. Please read the abstract below for a bit of background, and then come prepared to discuss how you think academic publications (including yours!) produced through synthesis center work might be measurably different from other publications in the field. Then we’ll see if your intuitions are supported by the data we have available. Prepare yourselves to either be really proud of your keen intuitions, or to be surprised by our results!


You can access the poster on figshare using this link:

Update: To initiate discussion prior to the meeting, I’ve put a question up on Tricider, and I welcome you to use the link below to add your ideas, comment on others’ ideas, and/or vote on the ideas that have been suggested. The question is the following:

“How would you expect academic publications that report on synthesis research to differ from publications resulting from other research approaches?”
Here is the link:
Synthesis is an emerging synthetic method for producing transformative research, and publications centers to promote synthesis are on the rise in the US and around the world. New analytic tools and techniques are needed to assess the originality and transformative potential of synthesis. We propose that research outputs produced within synthesis centers will exhibit distinctive qualities that distinguish them from other publications in their fields. To explore this possibility, we conducted a topical analysis of titles, abstracts, and keywords for approximately 400,000 articles published in 108 leading journals from the fields of Ecology, Evolutionary Biology, Biodiversity Conservation, Forestry, and Fisheries. We then described each document as a proportional combination of the discovered topics, and used the Rao-Stirling heuristics to estimate, for each document, various measures that illuminate contrasting aspects of diversity (i.e. variety, balance, and disparity). We then compare diversity metrics for the synthesis center documents with those for all other documents in our corpus to evaluate whether and how the measured diversity of synthesis center publications differs from that of other publications in the relevant fields.