Resources for Coral Reef Education – by Judy Lemus

divers_lpittman_pixabay.jpgWe all recognize that communication and education about science concepts and the process of science is more important than ever.  Fortunately, coral reefs are charismatic ecosystems that inspire much curiosity, concern, and interest from many sectors of society.  While there is no shortage of stunning images and videos online, resources that combine these visuals with robust educational content can be more challenging to identify; they do exist and I’ve put together some of my favorites here. The list is not exhaustive, and we welcome your suggestions for great additions.

EDUCATIONAL WEBSITES. These resources provide educational information about coral reefs across multiple levels and concepts, often using multimedia.

Khaled bin Sultan Living Oceans Foundation Coral Reef Ecology Curriculum. The KSLOF has perhaps the most comprehensive website on coral reef ecology. The site is set up as a course with several units and resources with very nice graphics and high quality videos geared specifically for students and teachers. Lessons are aligned with the Next Generation Science Standards, Ocean Literacy Principles, and Common Core State Standards for K-12, but some of the material could easily be used in a college level course. A major downside to this site is that one must register to use it.

Smithsonian Ocean Portal. The Smithsonian’s website for coral and coral reefs is not as media-rich as the KSLOF, but does have a great deal of scientific information about corals.  Only a couple of lesson plans are offered, but the richness of the content lies in the embedded links to additional images and other stories. The science is backed up with oversight by Smithsonian coral reef biologist Nancy Knowlton.

MarineBio Coral Reefs. The MarineBio website is somewhat of a clearinghouse for other marine bio resources, but the educational content on coral reefs is good quality and quite extensive if you follow the links.  Like the Smithsonian site, there are links to both internal and external resources. The short videos featured throughout the site, generally from outside sources, are particularly engaging.

OTHER WEBSITES WITH EXTENSIVE INFORMATION ABOUT CORAL REEFS

National Ocean Service

NOAA Coral Reef Conservation Program

USGS Coral Reef Project

Coral Reef Alliance

Teach Ocean Science

ReefBase

Great Barrier Reef Foundation

Coral Triangle Initiative

Endangered Reefs, Threatened People

Coral Health Atlas

VIDEOS ABOUT CORALS AND CORAL REEFS. There are loads of videos of corals and coral reefs on the web; these excellent examples incorporate educational content.

Catlin Seaview

Chasing Coral (available through Netflix)

Climate Change: Coral Reefs on the Edge

Exploring the Coral Reef: Learn about Oceans for Kids

Corals Under Confocal

Coral bleaching caused by heating water (time-lapse)

Life Noggin – What Happens if All the Coral Dies? (animation)

Coral Bleaching Animation – HHMI BioInteractive Video (animation)

Coral Bleaching on the Great Barrier Reef (animation)

SCIENCE NEWS SITES. These science news websites regularly post stories on coral reefs.

ScienceDaily

LiveScience


Thanks to Dr. Judy Lemus for this cream-of-the-crop list. Judy is a Faculty Specialist in Science Education at the Hawaii Institute of Marine Biology; fortunately for us, she is also the Education Node Leader for CRESCYNT. You can download Judy’s list in pdf format.

Resources for Coral Reef Education – by Judy Lemus

CRESCYNT Toolbox: EarthCube Sci-Tech Matchup – Lightning Talks

Get a fast intro to new Ready-for-Science EarthCube Tools!

We’ve helped arrange a series of lightning talks that will feature tools developed by EarthCube “building block” projects for direct use by scientists. Many EarthCube-built tools are designed to serve as internal components of an EarthCube platform. Other tools were built for scientists as direct end users, and a collection of these are now ripe for adoption. Will some of these help you with your research work?
The current collection will be shown over a span of two online sessions. Find log-in details for Wed., Feb. 15 and Fri., Feb. 17 (no RSVP required – just show up).
Join us!

Wednesday, Feb. 15, 2017
4-5pm EST / 1-2pm PST / 11am-12pm HST – login link HERE
GeoDataspace/GeoTrust, Tanu Malik
ECOGEO Virtual Machine, Elisha Wood-Charlson
LinkedEarth, Julien Emile-Geay
OntoSoft, Yolanda Gil
Flyover Country, Amy Myrbo

Friday, Feb. 17, 2017
4-5:30pm EST / 1-2:30pm PST / 11am-12:30pm HST – login link HERE
CHORDS, Mike Daniels
SuAVE, Ilya Zaslavsky
CINERGI, Ilya Zaslavsky
X-DOMES Ontology Registry, Janet Fredericks
X-DOMES SensorML Registry, Janet Fredericks
iSamplesIGSN, Kerstin Lehnert
GeoDeepDive, Shanan Peters
Digital Crust, Shanan Peters
ECITE, Sara Graves
Earth System Bridge, Scott Peckham

UPDATE: All of the videos from the February talks are now on the EarthCube YouTube channel – here’s the playlist. Slides will be linked at a new EC webpage in late March, and another hour of tools presentations will happen in early April.

CRESCYNT Toolbox: EarthCube Sci-Tech Matchup – Lightning Talks

CRESCYNT Toolbox: R Resources for Graphing and Visualization

In a previous post we offered some solid supportive resources for learning R – a healthy  dinner with lots of great vegetables. Here we offer a dessert cart of rich resources for data visualization and graphing. It’s a powerful motivation for using R.
rgraphgallery

First up is The New R Graph Gallery – extensive, useful, and actually new. “It contains more than 200 data visualizations categorized by type, along with the R code that created them. You can browse the gallery by types of chart (boxplots, maps, histograms, interactive charts, 3-D charts, etc), or search the chart descriptions. Once you’ve found a chart you like, you can admire it in the gallery (and interact with it, if possible), and also find the R code which you can adapt for your own use. Some entries even include mini-tutorials describing how the chart was made.” (Description by Revolutions.)

Sometimes we want (or need) plain vanilla – something clean and elegant rather than extravagant. Check out A Compendium of Clean Graphs in R, including code. Many examples are especially well-suited for the spartan challenge of conveying information in grayscale. The R Graph Catalog is a similar resource.

If you’re just getting started with R, take a look at the Painless Data Visualization section (p. 17 onward) in this downloadable Beginner’s Guide.

In R, ggplot2,  based on the Grammar of Graphics, is perhaps the single most popular R package for data visualization. The R Cookbook‘s section on Graphs using ggplot2 is a helpful precursor to the R Graphics Cookbook. DataCamp’s DataVis with ggplot2 has a free segment of intro lessons.

For more on visualization and other capabilities, check out this recommended list of useful R packages in the R Studio support blog – succinct and terrific.

If you’re already skilled in R and want a new challenge, an indirect method of harnessing some of the power of D3.js for interactive web visualizations is available through plotly for R. Here’s getting started with plotly and ggplot2, plotly and Shiny, and a gallery. The resources offer code and in some cases the chance to open a visualization and modify its data.

Have a favorite resource? Please share as a comment, or email us!

CRESCYNT Toolbox: R Resources for Graphing and Visualization

CRESCYNT Toolbox: Learning to love R more (or R is for reproducible)

caribbean_reef_shark_wikimediacommons_albertkokWe are driven to learn like sharks: constantly take in new flows, or die. In a recent workshop, when coral reef scientists were asked: “How many of you use R?” 60% raised a hand. To: “How many of you are comfortable with and love using R?” only about 15% kept a hand up.

Here’s where to go to learn to love R more.

rlogoYou likely already know of the R Project, free and open source software for statistical computing and graphics. You may already know of the reliability of the Comprehensive R Archive Network or CRAN repository, favored by many over other potential sources of community-generated code because of their metadata and testing requirements; it now hosts over 9,300 packages (sorted by date and name).

You may also know the elegance of RStudio, the excitement of putting your own interactive code online in RStudio’s Shiny, some great cheat sheets, the most popular R packages, and Stack Overflow as a great place to find answers to your R questions.

You may not know of the new R course finder, an online directory you can search and filter to find the best online R course for your next step (note there are often free versions or segments of even the pay courses listed). There are YouTube videos for R learning, like  twotorials (two-minute tutorials) and YaRrr! (because pirates) with book.

A very recent new book is getting rave reviews from both statistics and programming viewpoints: The Book of R by Tilman Davies (preview it here). The author writes:

“The Book of R …represents the introduction to the language that I wish I’d had when I began exploring R, combined with the first-year fundamentals of statistics as a discipline, implemented in R….   Try not to be afraid of R. It will do exactly what you tell it to – nothing more, nothing less. When something doesn’t work as expected or an error occurs, this literal behavior works in your favor….   Especially in your early stages of learning…try to use R for everything, even for very simple tasks or calculations you might usually do elsewhere. This will force your mind to switch to ‘R mode’ more often, and it’ll get you comfortable with the environment quickly.”

Because R is such a  stellar example of free and open source software with a very robust community (e.g., great stuff at r-bloggers), it’s a surprise how lucky we are that it IS open source, as heard in this interview with R founder Hadley Wickham on the DataStori.es podcast.

We’ll soon host a guest blogpost on some exploratory coral symbiont data analyses, visualizations, and comments generated in R Markdown, which is RStudio’s method for preserving code and output in one running web document. The work is beautiful and useful, and highlights the use of an electronic notebook as a way to capture and share data exploration, analysis and visualization, and to tell a data story. (A major advance to that software was announced this week in the form of R Notebook, which will ship within the next couple of months.)

Why is it worth learning to love R more?

R helps make sure your data work is reproducible (such an issue for science), repeatable (valuable for any processing you have to do periodically), and reusable (on other datasets or data versions, or by colleagues or your future self).

A couple of high-level languages, like R and Python, are becoming more popular each year, and are finding their way as general purpose tools into analytical platforms. These will serve as primary sources of flexibility in cyberinfrastructure platforms now available or under development. Our future selves thank us for the learning investment.

2016 Top 10 Tools for Analytics and Data Science - KD Nuggets Software Poll
“R, Python Duel As Top Analytics, Data Science software – KDnuggets 2016 Software Poll Results”  (click graph for article)

Update: speaking of interviews with R makers, here’s an October 2016 interview with JJ Allaire, the creator of RStudio, Shiny, and R Markdown. His advice for people new to R:

I would suggest that they get a copy of the R for Data Science book written by Hadley Wickham and Garrett Grolemund…. Also, when you have questions or run into problems don’t give up. There’s a lot of great activity around R on stackoverflow and other places and there’s an excellent chance you’re going to find the answers to your questions if you look carefully for them.
CRESCYNT Toolbox: Learning to love R more (or R is for reproducible)