Nov 2-3, 2015
9:00 - 17:00
Instructors: Leszek Tarkowski, Frederik Coppens
Helpers: Dima Fishman, Christof De Bo
In many domains of research the rapid generation of large amounts of data is fundamentally changing how research is done. The deluge of data presents great opportunities, but also many challenges in managing, analyzing and sharing data. Data Carpentry is designed to teach basic concepts, skills and tools for working more effectively with data. The workshop is aimed at researchers in the life sciences at all career stages and is designed for learners with little to no prior knowledge of programming, shell scripting, or command line tools.
For communication we will be using this Etherpad
Workshop Learning objectives & programme
Where: Avenue Louise/Louizalaan 231, 1050 Brussels. Get directions with OpenStreetMap or Google Maps.
Contact: Please mail leszek.tarkowski@gmail.com for more information.
We especially encourage to register those who may be less familiar with the above topics. There is no prerequisite as to what computing skills and knowledge is required.
The workshop is supported by the ELIXIR programme. Data Carpentry is a sibling organization of Software Carpentry and is designed to teach basic concepts, skills and tools for working more effectively with data. The structure and objectives of the curriculum as well as the teaching style are informed by Software Carpentry.
09:00 | Welcome and setup help |
09:30 | Caveats of working with data in spreadsheets |
10:00 | Introduction to Open Refine |
10:30 | Coffee |
11:00 | Working with Open Refine |
12:00 | Lunch break |
13:00 | Introduction to RStudio |
13:20 | Introduction to data manipulation with R - part 1 |
15:00 | Coffee |
15:30 | Introduction to data manipulation with R - part 2 |
17:00 | Wrap-up |
09:00 | Data visualisation with R - part 1 |
10:30 | Coffee break |
11:00 | Data visualisation with R - part 2 |
12:00 | Lunch break |
13:00 | Introduction to data manipulation with SQL - part 1 |
15:00 | Coffee break |
15:30 | Introduction to data manipluation with SQL - part 2 |
16:30 | Wrap-up and feedback |
17:00 | Close |
Etherpad: http://pad.software-carpentry.org/2015-11-02-DC-Brussels.
We will use this Etherpad for chatting, taking notes, and sharing URLs and bits of code.
To participate in a Data Carpentry workshop, you will need working copies of the software described below. Please make sure to install everything (or at least to download the installers) before the start of your workshop.
When you're writing scripts or text, it's nice to have a text editor that is optimized for writing code, with features like automatic color-coding of key words. The default text editor on Mac OS X and Linux is usually set to Vim, which is not famous for being intuitive. if you accidentally find yourself stuck in it, try typing the escape key, followed by ':wq!' (colon, lower-case 'q', exclamation mark), then hitting Return to return to the shell. (This will exit Vim and save the changes you made in the file.)
Bash is a commonly-used command line interface, a so-called shell. Using a shell gives you the power to do more tasks more quickly by freeing you from having to click everything.
R is a programming language that specializes in statistical computing. It is a powerful tool for exploratory data analysis. To interact with R, we will use RStudio, an interactive development environment (IDE).
SQL is a specialized programming language used with databases. We use a simple database manager called SQLite, either directly or through a browser plugin.
Notepad++ is a popular free code editor for Windows. Be aware that you must add its installation directory to your system path in order to launch it from the command line (or have other tools like Git launch it for you). The instructions to modify your path are available online here. Please ask your instructor to help you do this.
Install Git (version control) and a Bash shell for Windows from the msysGit project's homepage. This will provide you with Bash in the Git Bash program.
Install R by downloading and running this .exe file from CRAN. Also, please install the RStudio IDE.
Install the Firefox SQLite browser plugin described below.
Other tools used in Data Carpentry have been packaged up by Software Carpentry in an installer. This installer requires an active internet connection.
The default shell in all versions of Mac OS X is bash,
so no need to install anything. You access bash from
the Terminal (found
in /Applications/Utilities
). You may want
to keep Terminal in your dock for this workshop.
We recommend
Text Wrangler or
Sublime Text.
Alternatively, you can use nano
,
which should be pre-installed.
Install R by downloading and running this .pkg file from CRAN. Also, please install the RStudio IDE.
sqlite3
comes pre-installed on Mac OS X.
Also install the Firefox SQLite browser plugin described below.
The default shell is usually bash
,
but if your machine is set up differently
you can run it by opening a terminal and typing bash
.
There is no need to install anything.
Kate is one option for Linux users.
Alternatively, you can use nano
,
which should be pre-installed.
You can download the binary files for your distribution
from CRAN. Or
you can use your package manager, e.g. for Debian/Ubuntu
run apt-get install r-base
. Also, please install
the
RStudio IDE.
sqlite3
comes pre-installed on Linux.
Also install the Firefox SQLite browser plugin described below.
Instead of using sqlite3
from the command line,
you will use this plugin
for Firefox instead. If you don't already have firefox, install it first.
To install the sqlite plugin:
OpenRefine (formerly Google Refine) is a powerful tool for exploring and working with messy data. You will need a browser (Firefox or Chrome is recommended) to work with Open Refine. Once you install Open Refine, you should be able to launch it double clicking like most of the programs. Open Refine will open in the browser (but you don't have to be online)
Spreadsheets are useful for data entry and data organization, and some subsetting and sorting of the data as well as getting an overview of the data. To interact with spreadsheets, we can use LibreOffice, Microsoft Excel, Gnumeric, OpenOffice.org, or other programs. Commands may differ a bit between programs, but general ideas for thinking about spreadsheets is the same.
For this lesson, if you don't have a spreadsheet program already, you can use LibreOffice. It's a free, open source spreadsheet program.