Data Literacy, Data Science, Data-Mining, Just me

Ice, Software Carpentry, and Data Analytics

Ok, I have a bad habit of disappearing for long intervals (from my own site!) but I promise it’s just because I’ve been so busy. Not because I don’t like writing here. I really do like writing here.

I have some excellent things to share briefly though and figured even if it’s just a taste of what I’ve been doing, it’s good to put these things down somewhere. There are some less awesome things to write about, but for now here’s the highlights. The biggest things I’ve been up to lately:

I won 3 events in the North American Winter Swimming Championship which was held in New Port, VT back in February: 25, 50, 100 m Freestyle

This is me :)

Got my picture on the homepage of NPR with the story too :)

Also, I successfully obtained funding for and organized a Software Carpentry Workshop to be held at Weill Cornell. It took months and months but it’s all finally paying off next week! Check it out here. Funding was provided by the Weill Cornell Graduate School of Medical Sciences, and both the Applied Bioinformatics Core and Institute for Computational Biomedicine have been giving me excellent organizational and logistical support along the way. It’ll be free to all attendees.

Screen Shot 2015-03-26 at 2.08.06 PM

In other news:

I got accepted into the CUNY School of Professional Studies’ MS program in Data Analytics! This will be it’s own post soon I’m sure. I’m nervous but very excited to start in on this. I had to take an exam that covered topics in the following:

  • Statistics and probability including descriptive statistics, skewness/kurtosis, histograms, statistical error, correlation, single variable linear regression analysis, significance testing, probability distributions, and basic probability modeling;
  • Linear algebra including basic matrix manipulation, dot and cross products, inverse matrices, eigenvalues, representing problems as matrices, and solving small systems of linear equations;
  • Programming in a high level language (e.g. Python, Java, R). Coding from scratch;
  • Relational databases including connecting to and manipulating data, working with tables, joins, basic relational algebra, and SQL queries.
  • Analytical thinking including the ability to translate real-world phenomena into quantitative representations and, conversely, the ability to interpret quantitative representations with practical explanations.
Analytics Exam fun

I don’t have a formal math or computer science background so I have had to teach myself A LOT as I’ve come down the data science path. I’m continuing in this fashion as I pursue online coursework in Python and web application frameworks (gotta learn about APIs)– I’m working through some of the material on these online courses currently:

Python – Codecademy

Web Application Architectures – University of New Mexico via Coursera

Full Stack Web Development – Udemy


I have been writing blog posts for the e-Science Portal over the last few months (check them out here) and also published my first peer-reviewed article in the open source journal In the Library with the Lead Pipe, which you can see here— I got to work with some fantastic librarians on this one so please do give it a read!

And my husband and I adopted a new kitten.10959405_10203405359919458_5042590917317009510_n

His name is Herald and he can see a little bit out of his one eye.

And in case that last part slipped by you, I got married! It’s been such a busy few months, but I really can’t complain.

Owen and Daina
Brighton Beach, Brooklyn. Dec. 13, 2014