GIS for Journalism: Other Resources

The links below will take you to online resources for GIS and Data Science for Journalists.

Towards Data Science weblogs include case studies about Data and GIS applications in journalism.  The broader page contains information about other topics in Data Science including machine learning, visualization and programming.

Intro to Mapping and GIS for Journalists (online course via the Univ. of Texas)

This resource page features course content from the Knight Center for Journalism in the America's massive open online course (MOOC) titled " Intro to Mapping and GIS for Journalists." The four-week course took place from August 27 to September 23, 2018, and is now available free to anyone else who is interested in geography, map making, data visualization and visual storytelling. No geographic background is required.

A Story Map Journalism Experience ( via GIS Lounge)

"A Story Map allows us to write from “where,” that is, from the location where the news is taking place – on an interactive digital map. It answers the five W’s in journalism, namely: “who,” “what,” “when,” “why,” and “how,” and also use images, videos, and sound to support the narration – which is why Story Maps are a powerful tool for digital journalism."

Proprietary

• ArcGIS -  Arguably the most widely used, proprietary GIS software suite, includes extensive technical and tutorial support.  ArcGIS can be integrated with a  broad range of data sources.  Limit access at Morgan.
• Maptitude -  Maptitude has the advantage of easy to use interfaces and expansive built-in data that facilitates streamlined visualizations and analyses.  Limited access at Morgan.

Open Source

• ESRI Story Maps  - An exceptional platform for  journalists that enables compelling story-telling with maps, images and text.
• QGIS -  Likely the world's most popular GIS software suite.  QGIS is a free, fully-functional GIS software with extensive capabilities.  A large user-base generates a lot of tutorial resources and technical support.
• GRASS The Geographic Resources Analysis Support System is an open source GIS providing powerful raster, vector and geospatial processing capabilities. It can be used either as a stand-alone application or as backend for other software packages such as QGIS and R or in the cloud. 
• Google Maps - Google provides limited GIS capabilities mostly in data capture and visualization.  Data captured in Google Maps can be further integrated into other GIS software platforms like ArcGIS and QGIS.
• GeoDa - GeoDa is a free and open source, user-friendly software program that developed to help researchers and analysts translate data into insights. The program is designed for location-specific data such as buildings, firms or disease incidents at the address level or aggregated to areas such as neighborhoods, districts or health areas. What differentiates GeoDa from other data analysis tools is its focus on explicitly spatial methods for these spatial data.

NetLogo (Agent Based Modeling) NetLogo is a programmable modeling environment for simulating natural and social phenomena. NetLogo is particularly well suited for modeling complex systems developing over time. Modelers can give instructions to hundreds or thousands of “agents” all operating independently. This makes it possible to explore the connection between the micro-level behavior of individuals and the macro-level patterns that emerge from their interaction. NetLogo has extensive documentation and tutorials and includes a large collection of discipline-specific, pre-written simulations that can be used and modified. 

R (language) R is a language and environment for statistical computing and graphics in data science. R provides a wide variety of statistical and graphical techniques, and is highly extensible.  R facilitates the production of well-designed publication-quality plots, including mathematical symbols and formulæ. 

Python  Python is an easy-to-use and learn programming and analysis language with a broad range of applications, especially in data analysis.  Python is a free and open source language with an extensive user-base and technical support. The Python Package Index (PyPI) hosts thousands of third-party modules for Python. Both Python's standard library and the community-contributed modules allow for endless possibilities.