As a D-Lab instructor, I have designed and taught many workshops on the use of geospatial tools and techniques using both ArcGIS and QGIS software as well R and Python programming environments. Software installation is often a pain point for students and can dissuade new learners from moving forward. I have found this to be especially true for Python where installing software can be quite complex given differences in Python versions, package versions and operating systems.

 

To avoid having installation problems derail a workshop before it even starts we try to use tools and environments that make things a bit easier for our students. For ArcGIS workshops we start with ArcGIS Online rather than the full desktop suite which only runs on MS Windows PCs. For QGIS, we encourage students to install the long term stable release rather than the latest release. Thankfully, R programming workshops tend to run very smoothly with RStudio.

 

Finding a good local work environment for Python workshops has been more challenging and these workshops are often fraught with software installation issues. Cloud based environments like AWS and Google Cloud and Google Cloud Datalab may resolve installation problems for students but given the complexity of setup and deployment they might just move the problem around and lead to additional staff time and operating expenses.

 

Given this landscape, I was recently encouraged when I discovered the joys of Google Collaboratory a cloud-based Jupyter notebook environment for Python programming.  According to the FAQ, Google Collaboratory is “a research tool for machine learning education and research. It’s a Jupyter notebook environment that requires no setup to use.” I repeat - NO SETUP TO USE! FREE! FOR EDUCATION!  These are all great things (while they last) for folks who use Google tools.  

 

Speaking of other Google tools, Google Collaboratory works similarly to Google Docs. Once you go to the Google Collaboratory website and save a notebook to Google Drive you will have a Colab Notebooks folder in your Google Drive. Like a Google Doc, you can share your notebooks with other folks. If you share in View only mode, folks can view and save local copies of your notebook. You can also give folks Edit permission and create notebooks collaboratively, thus the name Google Collaboratory!

 

The primary focus of Google Collaboratory is as a training environment for machine learning. However, it’s also great for learning about geospatial data and mapping in Python. You can give Google Collaboratory a test drive by opening this simple notebook that I wrote which demonstrates geocoding and mapping a small set of named places in San Francisco.  Feel free to send me an email with any feedback.

 

As for workshops, the D-Lab is planning to hold an introductory Python geospatial workshop using Google Collaboratory this semester, so keep your eyes on our calendar as it is updated frequently. In the meantime, the GeoMatters working Group will test run this workshop this week on Thursday November 1, 2018 from 4:00 to 5:30 pm in 371 Barrows Hall. This is a great time to check out both Google Collaboratory and the GeoMatters working group and also provide us with some feedback on how we might use this cloud environment for future D-Lab workshops.

 

 

Author: 

Patty Frontiera

Dr. Patty Frontiera is the D-Lab geospatial topic area lead. As such, she develops the geospatial workshop curriculum, teaches workshops and consults on geospatial topics.  Patty has been with the D-Lab since 2014 and served as the the Academic Coordinator through Spring 2017. Patty received her Ph.D. in Environmental Planning from UC Berkeley where her dissertation explored the application and effectiveness of generalized spatial representations in geographic information retrieval.