Introduction to Data

Welcome to our first module on working with data.


This Library Carpentry lesson introduces librarians to working with data. At the conclusion of the lesson you will:

  • understand terms, phrases, and concepts in software development and data science
  • identify and use best practice in data structures
  • use regular expressions in searches


Time Description
10:00am Introductions
10:05am Data introduction
10:15am Group Exercise: Jargon busting
10:35am Group Feedback
10:45am Run through of terms
11:00am Coffee
11:15am Teaching: Foundations
11:25am Teaching: Regular Expressions
11:40am Exercise: Regular Expressions
12:10pm Feedback
12:20pm Exercise: Working with data
12:40pm Feedback
13:00pm Lunch and OpenRefine installation workshop


We make decisions every day. Sometimes these are very small ones that don't require much consideration. But in professional life they are often key to our roles and the users we're trying to help. There are many aspects to decision making that we always try to take into account. What's the ethical thing to do? Is it legal? Is it possible? Can we afford it? But do we always make decisions based upon clear evidence and data? Think of some example library-based decisions:

  • amount spent on different types of stock;
  • fines for overdue items;
  • charges for certain type of stock;
  • staff levels in a library;
  • van routes and frequencies to move items between branches;
  • what stock to have in different libraries;
  • opening hours;

How often are these fully informed by analysis of data and evidence?

These questions are very much formed from my own experience, which is within a systems role in public libraries.

It's clear that data is essential to decision-making, but even when data is available to us, we don't necessarily have the skills to interpret it, or manipulate it in the way we need to. But you don't need to be a data scientist to gain confidence in using data. This module aims to discuss data tasks we all deal with, and gain practice in some data manipulation techniques.

Source Material

See introduction to data at the Library Carpentry materials site.

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