Spatial Data Science Bootcamp March 2016

Register now for the March 2016 Spatial Data Science Bootcamp at UC Berkeley!

We live in a world where the importance and availability of spatial data are ever increasing. Today’s marketplace needs trained spatial data analysts who can:

• compile disparate data from multiple sources;
• use easily available and open technology for robust data analysis, sharing, and publication;
• apply core spatial analysis methods;
• and utilize visualization tools to communicate with project managers, the public, and other stakeholders.

To help meet this demand, International and Executive Programs (IEP) and the Geospatial Innovation Facility (GIF) are hosting a 3-day intensive Bootcamp on Spatial Data Science on March 23-25, 2016 at UC Berkeley.

With this Spatial Data Science Bootcamp for professionals, you will learn how to integrate modern Spatial Data Science techniques into your workflow through hands-on exercises that leverage today's latest open source and cloud/web-based technologies. We look forward to seeing you here!

To apply and for more information, please visit the Spatial Data Science Bootcamp website.

Limited space available. Application due on February 19th, 2016.

Hold the date! January 15th for a workshop on Open Tools with ESRI

On January 15th we will hold a full day free workshop on Open Mapping Tools using ESRI. 

Welcome to the Esri GeoDev HackerLab. This is an eight-hour, mentored, hands-on lab for developers (novice or experienced) where you will learn how to build maps and apps for the web, devices, and desktops using ArcGIS and other technologies. 

Here is what we will cover:

1. A brief intro to ArcGIS Online for developers. Get the free dev subscription and we put the tools right into your hands.

2. Data: Search, find, connect to, import, edit, collect, translate, convert, and host datasets and web services. You will also use a variety of cloud-based geoanalytical tools to make better sense of the data and export new datasets for your apps to use.

3. Design: Create web maps tailored to the needs of your end users using layer selection, thematic rendering, popups, and more.

4. Develop: Build customized apps with or without code, using templates, builders, APIs, and SDKs, from Esri and from other popular open source technologies.

The labs are divided into modules that you can do in any order. Choose ones you want to learn, and skip those you already know. You can bring your own data or use tutorial data that we provide. Use web maps of your own or build ones on-site during the lab. If you are a coder, dig into APIs and SDKs from Esri or compatible open source libraries. If you aren’t a coder, you can still build highly customized production-ready apps using templates and builders.

The tutorials are going to be led by developers from Esri, who will either guide you along the way or assist you as you choose your own learning path. 

Stay tuned for sign-up information!

Data science for the 21st century: building a new team of researchers

Berkeley is one out of eight new awards from the National Science Foundation's recently launched NSF Research Traineeship (NRT) program. These programs develop innovative approaches to graduate training used across these projects include industry internships, international experiences, citizen science engagement, interdisciplinary team projects, and training in communication with the media, policy makers, and general public.

Our program at UC Berkeley is called Data Science for the 21st centur: DS421.  Three Grand Challenges motivate our program:

1. Data: data acquisition, assimilation, and analysis, and the resulting challenges and opportunities for the research community and society at large. The data revolution is a potentially disruptive advance that challenges the norms and traditions of scientific research. Data science is an opportunity, entailing a revolution in training and a reorientation of research priorities. Open science— open access to datasets, literature, scripted workflows and the like—is a fundamental transformation that integrates scientific publication with the underlying data, analysis, and reasoning, using metadata and machine-readable research products to facilitate a semantic web of knowledge. These practices will make our research reproducible and transparent, documenting the evidentiary basis for scientific conclusions and their implications for policy.
2. System dynamics: coupled human-natural systems and their responses to rapid environmental change. Social-ecological systems display a complex array of ecological and social processes interconnected across broad spatial, temporal, and socio-political scales. Our current approach to understanding ecological and economic systems is dominated by partial equilibrium models that are poorly suited to the dynamics of rapidly changing systems. Important research avenues include: characterizing the dynamics and feedbacks among and within systems to better plan for cross-scale and nonlinear uncertainties; identifying the proximity of tipping points or other critical transitions; understanding how the spatial structure of interactions affects system dynamics; and detecting and attributing responses to environmental and climatic drivers. Real-time data analytics combined with long-term monitoring and forecasting are critical tools to address to these challenges.
3. Action: evidence-based proposals in public policy, natural resource management, and environmental design to mitigate the impacts of rapid environmental change, and enhance societal resilience and sustainability. Effective decision-making depends on networks of diverse stakeholders, with rapid feedback between individuals and groups to evaluate the impact, efficiency, equity, and efficacy of policy and management actions. This third component is at the core of a practical data science ethic critical for translating science to societal benefit, and makes use of our partnerships with academic, private, governmental, and non-governmental organizations.

Cutting across these challenges, all students, and especially those engaged in interdisciplinary research,
need excellent communication skills and the ability to adjust content and style to reach their audiences. Welcome to the new cohort!

Fall 2013 GIF Workshops Scheduled

The Fall 2013 schedule of workshops has been posted! Check them out at: http://gif.berkeley.edu/support/workshops.html.

Workshops include:

• Intro to Geographic Information Systems (GIS): Environmental Science Focus
• Intro to Geographic Information Systems (GIS): Social Science Focus
• Intro to Global Positioning Systems (GPS): Working with Garmin receivers
• Intro to Remote Sensing: Understanding digital imagery
• Intro to Remote Sensing: Pixel-based analysis
• Intro to Remote Sensing: Land cover change analysis
• Intro to Remote Sensing: Object-based image analysis (OBIA)
• Intro to Open Source GIS: Working with Quantum GIS (QGIS)
• Intro to species distribution modeling
• Creating your own web maps

ANR members are invited to attend. GIF workshops offer hands-on applications oriented training in a variety of geospatial topics. Workshop fees are available at a subsidized rate of $84 for all UC students (graduate and undergraduate), faculty, and staff. Workshop fees are $224 for all non-UC affiliates.