This will take place on 9-13th January 2023 at the University of Amsterdam. Applications are accepted until 1st December 2022.
More details and registration links are available here and an excerpt on this year’s theme and the format is copied below:
The Digital Methods Initiative (DMI), Amsterdam, is holding its annual Winter School on the ‘Use and Misuse of Open Source Intelligence (OSINT)’. The format is that of a (social media and web) data sprint, with tutorials as well as hands-on work for telling stories with data. There is also a programme of keynote speakers. It is intended for advanced Master’s students, PhD candidates and motivated scholars who would like to work on (and complete) a digital methods project in an intensive workshop setting. For a preview of what the event is like, you can view short video clips from previous editions of the School.
We’ve recently been experimenting with the use of ObservableHQ notebooks for gathering and transforming data in the context of digital research. This post walks through a few recent examples of notebooks from recent Public Data Lab projects.
In one project we wanted to use the CrowdTangle “Links” API to fetch data about how certain web pages were shared online and across different platforms. After gaining access to relevant end points, we could adopt different means to call the APIs and retrieve data: such as using something like Postman (a general-purpose interface to call endpoints), or writing custom scripts (for example in Python or Javascript).
Code notebooks are a third option that lies somewhere in between these options. Designed for programmers, notebooks allow for iterative manipulation and experimentation with code whilst keeping track of creative processes by commenting on the thinking behind each step.
Notebooks allow us to both write and run custom scripts as well as creating simple interfaces for those who may not code. Thus we can use them to help researchers, students and external collaborators to collect data, making it easier to call APIs, setting parameters, or perform manipulations.
ObservableHQ is one solution for writing programming notebooks, it runs in the browser and is oriented towards data and visualisations (“We believe thinking with data is an essential skill for the future”). Hence, we thought it could be a good starting point for what we wanted to do.
Researchers and students contributed to a series of “engaged research led teaching” projects developed with journalists, media organisations and non-governmental organisations around the world.
The book provides a wide-ranging collection of perspectives on how data journalism is done around the world. It is published a decade after the first edition (available in 14 languages) began life as a collaborative draft at the Mozilla Festival 2011 in London.
The new edition, with 54 chapters from 74 leading researchers and practitioners of data journalism, gives a “behind the scenes” look at the social lives of datasets, data infrastructures, and data stories in newsrooms, media organizations, startups, civil society organizations and beyond.
The book includes chapters by leading researchers around the world and from practitioners at organisations including Al Jazeera, BBC, BuzzFeed News, Der Spiegel, eldiario.es, The Engine Room, Global Witness, Google News Lab, Guardian, the International Consortium of Investigative Journalists (ICIJ), La Nacion, NOS, OjoPúblico, Rappler, United Nations Development Programme and the Washington Post.
An online preview of various chapters from book was launched in collaboration with the European Journalism Centre and the Google News Initiative and can be found here.
Further background about the book can be found in our introduction. Following is the full table of contents and some quotes about the book. We’ll be organising various activities around the book in coming months, which you can follow with the #ddjbook hashtag on Twitter.
