Data Discovery Science Competition

 

Come Find the Data You Need!

Grow your skills and your data resources in the Data Discovery Science Competition at DataDiscoveryStudio.org

Data Discovery Studio is built to help scientists find data. It hosts records for over 1.6 million datasets and resources from over 40 repositories, and continues to grow. Individuals, classes, and sci-tech teams can compete in two categories:

(1) Build a shareable Collection of datasets from existing resources, and add links to other datasets and resources in other repositories. We show you how!

(2) Modify existing Jupyter Notebooks or create your own to explore a data type of interest. Guidance provided!

Find details at bit.ly/ddscompete or jump in and start exploring at DataDiscoveryStudio.org – enter by May 1, 2019.

Please share broadly! We built this NSF-funded EarthCube gateway for you, want it to be useful, and eagerly welcome your feedback.

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Note to coral reef scientists: the site already includes over 16,600 records of coral reef datasets and resources – enough to begin a select collection of your own to share with collaborators, and point to more.

More Details:

Both competition categories contribute to science. (1) Collections will gather and tag resources, including datasets, with a focus you choose for research or community use. (2) Jupyter Notebooks will help develop workflows for datasets with a common theme or structure. Both areas will help address real science questions, share results and resources with others, and will help improve the gateway for future users. The competition is suitable for individual, team, or class entry.

DDStudio’s strongest holdings in datasets and resources are in earth, ocean, atmospheric, hydrologic, geologic, planetary, ecological, and other geoscience domains, broadly defined. Try out a favorite search term at datadiscoverystudio.org – if DDStudio doesn’t have what you need, you can contribute a new link, or point us to repositories to add. DDStudio goes beyond search: some datasets can be explored right on site using example Jupyter Notebooks (e.g., sensor data) – or develop and contribute your own Notebooks.

You can’t win if you don’t enter – show up and represent your domain! bit.ly/ddscompete

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On Preserving Coral Reef Imagery and Related Data – by James W Porter

James Porter’s coral photo monitoring project in Discovery Bay

In preparation for an upcoming Data Science for Coral Reefs: Data Rescue workshop, Dr. James W. Porter of the University of Georgia spoke eloquently about his own efforts to preserve historic coral reef imagery captured in Discovery Bay, Jamaica, from as early as 1976. It’s a story from the trenches with a senior scientist’s perspective, outlining the effort and steps needed to accomplish preservation of critical data, in this case characterizing a healthy reef over 40 years ago.

Enjoy this insightful 26-min audio description, recorded on 2018-01-04.

 

Transcript from 2018-01-04 (lightly edited):

This is Dr. Jim Porter from the University of Georgia. I’m talking about the preservation of a data set that is at least 42 years old now and started with a photographic record that I began making in Discovery Bay, Jamaica on the north coast of Jamaica in 1976. I always believed that the information that photographs would reveal would be important specifically because I had tried other techniques of line transecting and those were very ephemeral. They were hard to relocate in exactly the same place. And in addition to that they only captured a line’s worth of data. And yet coral reefs are three dimensional and have a great deal of material on them not well captured in the linear transect. So those data were… I was very consistent about photographing from 1976 to 1986.

But eventually funding ran out and I began focusing on physiological studies. But toward the end of my career I realized that I was sitting on a gold mine. So, the first thing that’s important when considering a dataset and whether it should be preserved or not is the individual’s belief in the material. Now it’s not always necessary for the material to be your own for you to believe in it. For instance, I’m working on Tom Goreau, Sr.’s collection which I have here at the University of Georgia. I neither made it nor in any way contributed to its preservation but I’ve realized that it’s extremely important and therefore I’m going to be spending a lot of time on it. But in both cases, the photographic record from Jamaica, as well as the coral collection itself – those two activities have in common my belief in the importance of the material.

The reason that the belief in the material is so important is that the effort required to capture and preserve it is high, and you’ve got to have a belief in the material in order to take the steps to assure the QA/QC of the data you’re preserving, as well as the many hours required to put it into digital format. And believing in the material then should take another step, which is a very self-effacing review of whether you believe the material to be of real significance to others. There’s nothing wrong with memorabilia. We all keep scrapbooks and photographs that we like – things relating to friends and family, and times that made us who we are as scientists and people. However, the kind of data preservation that we’re talking about here goes beyond that – could have 50 or 100 years’ worth of utility.

Those kinds of data really do require them to be of some kind of value, and the value could either be global, regional, or possibly even local. Many local studies can be of importance in a variety of ways: the specialness of the environment, or the possibility that people will come back to that same special environment in the future. The other thing that then is number two on the list – first is belief in the material – second is you’ve got to understand that the context in which you place your data is much more important to assure its survival and utility than the specificity of the data. Numbers for their own sake are numbers. Numbers in the service of science become science. It is the context in which you place your data that will assure its future utility and preservation.

Resources for Coral Reef Education – by Judy Lemus

We 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

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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.

>>>Go to NSF EarthCube or the CRESCYNT website or the blog Masterpost.<<<

CoralNet: deploying deep learning in the shallow seas – by Oscar Beijbom

Having dedicated my PhD to automating the annotation of coral reef survey images, I have seen my fair share of surveys and talked to my fair share of coral ecologists. In these conversations, I always heard the same story: collecting survey images is quick, fun and exciting. Annotating them is, on the other hand, slow, boring, and excruciating.

When I started CoralNet (coralnet.ucsd.edu) back in 2012 the main goal was to make the manual annotation work less tedious by deploying automated annotators alongside human experts. These automated annotators were trained on previously annotated data using what was then the state-of-the-art in computer vision and machine learning. Experiments indicated that around 50% of the annotation work could be done automatically without sacrificing the quality of the ecological indicators (Beijbom et al. PLoS ONE 2015).

The Alpha version of CoralNet was thus created and started gaining popularity across the community. I think this was partly due to the promise of reduced annotation burden, but also because it offered a convenient online system for keeping track of and managing the annotation work. By the time we started working on the Beta release this summer, the Alpha site had over 300,000 images with over 5 million point annotations – all provided by the global coral community.

There was, however, a second purpose of creating CoralNet Alpha. Even back in 2012 the machine learning methods of the day were data-hungry. Basically, the more data you have, the better the algorithms will perform. Therefore, the second purpose of creating CoralNet was quite simply to let the data come to me rather than me chasing people down to get my hands on their data.

At the same time the CoralNet Alpha site was starting to buckle under increased usage. Long queues started to build up in the computer vision backend as power-users such as NOAA CREP and Catlin Seaview Survey uploaded tens of thousands of images to the site for analysis assistance. Time was ripe for an update.

As it turned out the timing was fortunate. A revolution has happened in the last few years, with the development of so-called deep convolutional neural networks. These immensely powerful, and large nets are capable of learning from vast databases to achieve vastly superior performance compared to methods from the previous generation.

During my postdoc at UC Berkeley last year, I researched ways to adapt this new technology to the coral reef image annotation task in the development of CoralNet Beta. Leaning on the vast database accumulated in CoralNet Alpha, I tuned a net with 14 hidden layers  and 150 million parameters to recognize over 1,000 types of coral substrates. The results, which are in preparation for publication, indicate that the annotation work can be automated to between 80% and 100% depending on the survey. Remarkably: in some situations, the classifier is more consistent with the human annotators than those annotators are with themselves. Indeed, we show that the combination of confident machine predictions with human annotations beat both the human and the machine alone!

Using funding from NOAA CREP and CRCP, I worked together with UCSD alumnus Stephen Chan to develop CoralNet Beta: a major update which includes migration of all hardware to Amazon Web Services, and a brand new, highly parallelizable, computer vision backend. Using the new computer vision backend the 350,000 images on the site were re-annotated in one week! Software updates include improved search, import, export and visualization tools.

With the new release in place we are happy to welcome new users to the site; the more data the merrier!

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– Many thanks to Oscar Beijbom for this guest posting as well as significant technological contributions to the analysis and understanding of coral reefs. You can find Dr. Beijbom on GitHub, or see more of his projects and publications here. You can also find a series of video tutorials on using CoralNet (featuring the original Alpha interface) on CoralNet’s vimeo channel, and technical details about the new Beta version in the release notes.

 

>>>Go to NSF EarthCube or the CRESCYNT website or the blog Masterpost.<<<

3D Mapping of Coral Reefs – How to Get Started – by John Burns

Rapid technological advancements are providing a suite of new tools that can help advance ecological and biological studies of coral reefs. I’ve studied coral health and disease for the last several years. One large gap in our research approach is the ability to connect changes in coral health to large-scale ecological processes. I knew that when corals died from disease it would alter the fundamental habitat of the system, which in turn would impact associated reef organisms. What I didn’t know was how to effectively document and quantify these changes. Sometimes we just need to alter our perspective to find the answers we are looking for. I starting reviewing methods used by terrestrial researchers to measure landscape changes associated with landslides and erosion. In doing so I came across structure-from-motion (SfM) photogrammetry, and it was immediately clear that this technique could improve our understanding of coral reef ecosystems. I spent the next few years developing methods to use this approach underwater, and have since used SfM to detect changes in reef structure associated with disturbances as well as improve our understanding of coral diseases.

 

The first question I am usually asked is, “How easy is it to use this technique and what does it cost?” The best answer I can provide is the logistic constraints depend on your research question. If you are interested in accuracy and controlling the parameters of the 3D reconstruction process, then you should use proprietary software like Agisoft PhotoScan and Pix4D. These programs give you full control, yet require more understanding of photogrammetry and substantial computing power. Autodesk ReCap can process images remotely, which reduces the need for a powerful computer, but also reduces your control over the 3D reconstruction process. At the most simple level, you can download the Autodesk 123D catch app on your phone and create 3D reconstructions in minutes! There are also multiple open-source software options, but they tend to be less powerful and lack a graphical user interface. My advice is to start small. Get started with some simple and free open source tools such as Visual SfM or Bundler. Collect a few sets of images and get some experience with the processing steps to determine if the model outputs are applicable for your research approach.

The second question I receive is, “What is the best way to collect the images?” Unfortunately, the answer is not to use the ‘auto’ setting on your camera and just take a bunch of pictures. Image quality will directly affect the resolution of your model, and is also important for stitching and spatial accuracy. Spend time to understand the principles of underwater photography. A medium aperture (f-stop of 8 to 11) will let in enough light in ambient conditions while not causing blur and distortion associated with depth of field. Since images are taken while moving through a scene, a high enough shutter speed is required that will eliminate blur and dark images. Since conditions can be highly variable, one must adapt to changes in light and underwater visibility while in the field. Cameras with auto-ISO can be helpful for dealing with changing light conditions while surveying. I also recommend DSLR or mirrorless cameras with high-quality fixed lenses, as they will minimize distortion and optimize overall resolution and clarity. For large areas I won’t use strobes because I take images from large distances off the reef, and this will typically create shadows in the images. I take images of the reef from both planar and oblique angles to capture as much of the reef scene as possible in order to eliminate ‘black holes’ in the resulting model. There is no ‘perfect approach,’ but you will need 70-80% overlap for accurate reconstruction. I swim in circular or lawn-mower patterns depending on the scene, and swear by the mantra that more is better (you can always throw out images later if there is too much overlap). It is worth investing time in experimenting with methods to develop a technique that works best for your study are and experimental design. SfM is a very flexible and dynamic tool, so don’t be afraid to create your own methods.

The third question is then, “How do you ground-truth the model for spatial accuracy?” This is a critical step that often gets overlooked. In order to achieve mm-scale accuracy the software must be able to rectify the model to known x,y,z coordinates. I use mailbox reflectors connected by PVC pipe to create ground control points (GCPs) with known distances. The red color and white outline of the reflectors is easily distinguished and identified by the software and saves a lot of time for optimizing the coordinates of the model. Creating functional GCPs is exceptionally important is spatial accuracy is required for your work. I also use several scale bars throughout my reef plots to check accuracy and scaling. This step of the process is critical for accurately measuring 3D habitat characteristics.

Maybe I’ve taken you too far into technical details at this point, but hopefully this helps for anyone looking to venture into the world of SfM. There is no perfect approach, and we must be adaptable as software continues to improve and new tools are constantly being created. We also need to continue to develop new methods for quantifying structure from 3D models. I export my models into geospatial software to extract structural information, but this step of the process can be improved with methods capable of annotating the true 3D surface of the models. As new software becomes available for annotating 3D surfaces we are entering an exciting phase with endless possibilities for collating and visualizing multiple forms of data. Being open-minded and creative with these techniques may provide new insight into how these environments function, and how we can protect them in the face of global stressors.

– Mahalo to John Burns for this in-depth guest posting. You can see more of his work, simultaneously beautiful and useful, at the Coral Health Atlas. Click on the image below for more of John’s remarkable 3D coral reef mapping work:

>>>Go to NSF EarthCube or the CRESCYNT website or the blog Masterpost.<<<

CRESCYNT Toolbox – Stitched Images – 3D Reef Mapping and 360-Degree Imagery

Imagery REALLY feeds our monkey brains. Today: tools for 3D reef mapping. Bonus: some 360-degree images and video to use with virtual reality headsets.

Several exciting talks at the International Coral Reef Symposium featured 3D mapping of coral reefs using SfM, Structure from Motion techniques, to stitch together large numbers of overlapping images. The resulting 3D mapped images were used to help address a surprising range of research questions. The primary tools used to create these were Agisoft’s PhotoScan or the free and open source Bundler (github) by Noah Snavely.  Part of the challenge of this difficult work is organizing the workflows and data processing pipelines: it’s an example of a type of cyberinfrastructure need that eventually EarthCube architecture should be able to help stage. Look for a guest blog soon by John Burns to learn more!

360 Film by Conservation International

BONUS: The process of creating spherical or 360-degree images or video is at root a similar challenge of stitching together images, though more of the work is done inside a camera or on someone else’s platform. There are some recent beautifully-made examples of spherical coral reef images and 360 videos, viewable through virtual reality (VR) headsets; these have great potential for education and outreach. Consider the XL Catlin Seaview Survey gallery of coral reef photo spheres and videos from around the world, (including bleaching and before-and-after images) and Conservation International’s 8-minute video, Valen’s Reef, both exhibited at the current IUCN World Conservation Congress in Honolulu.

Catlin Seaview Survey – equipment

A new project, Google Expeditions, was launched this past week to facilitate synchronized use by multiple people of 360 videos and photo spheres as a design for class use. Google Streetview is being made more accessible as a venue for education and outreach, including creating and publishing one’s own photo spheres. Also find 360-videos of coral reefs on YouTube.

UPDATE: Visually powerful 360 bleaching images that Catlin Seaview debuted at ICRS, viewed by tablet or smartphone, are now accessible in this article on coral bleaching.

>>>Go to the blog Masterpost or the CRESCYNT website or NSF EarthCube.<<<