In out current era, even nontechnical people need to have some understanding of data science and statistics. What’s confusing is that so many terms—data science, big data, machine learning, statistics—get bandied about with little explanation. To understand how the pieces fit together, I highly recommend this article from the Win Vector blog.
The R programming language is another tool that is making headlines. From Google’s use of R for analysis to Microsoft buying IDE maker Revolution Analytics, R is all the buzz. What is it? Why use R? The R Bloggers website answers these questions and their email list provides a nicely curated flow of articles that will keep you up-to-date.
For folks who are programming already, the Quick-R page is very useful, especially when you are trying to find equivalent R code for a Stata routine.
As a former graphic designer and communications officer, I’ve spent a lot of time thinking about how to present research. As this nice overview article by the WSJ explains, in an era of Big Data, visualization is going to be a key area of inquiry for firms, researchers and the public.
A good introduction to data visualization can be found on Edward Tufte’s website and in his books (the Visual Display of Quantitative Information is well worth buying and his traveling seminar is also great).
For a more contemporary spin on these issues, the Flowing Data website and book are also worth a look. For true visualization geeks, the Parsons Journal for Information Mapping is a fantastic (and free) publication put out the the Parsons Institute.
If you are working on a project and need a resource to inspire creative approaches to visualization, I highly recommend the Visual Literacy project’s Periodic Table of Visualization Methods.
Online search is always changing and it’s worth know how to use the various tools. This helpful NYTs piece covers some basic search tips for the major search engines.
A great article by John Tedesco details the best way to use regular old Google search to find what you need. I learned a lot from this post, including that “AND” is not regarded as a boolean operator, but “OR” is. In the same vein, a “-” in front of a word will remove it from results, but a “+” sign in front will not include. Instead, use the intext command.
And here’s Google’s Search Features page. It contains a lot of interesting targeted searches, including a reference tools section, which has a box to search public data directly.
For academics who use Google Scholar, the official blog details how to use Scholar to search effectively for new research. You can also use Google Scholar to share your research with the world. The first step is to create an author page via Google. Obviously this further integrates your work with Google’s hive-mind—but, on the positive side, it makes it easier to track your citations and share your research.
Welcome to Politics Earth a site about the politics of the environment, and the tools and tricks of digital scholarship. As a PhD student studying public policy and world politics, and a long time environmentalist, I’m interested in connections between social and natural systems and evidence-based approaches to sustainability.
The digital scholarship side of this site began as a list of tools and tips I created to aid my studies — then I realized a) this might be useful and b) I might learn something if I turned it into a web site. Scholars doing empirical work need to search for, code and analyze data; find and organize bibliographic materials; write, program and design, use GIS and statistical tools — and so on. Do you have a way to do it better? Please post!