Massive Open Online Courses (MOOC) are available worldwide and offer tons of topics, also about Linked Open Data (LOD). An easy way to enter the semantic web.

Two examples:



The Hasso Plattner Institute, Potsdam provides, for some years now, a course in Linked Data Engineering with a certificate. I did it some years ago and enjoyed it.



The French platform FUN offers a LOD course, too. (Thanks to Adrian at zazuko.com for the hint)

And books

Step by step Bob DuCharme introduces RDF, SPARQL, LOD …




Statistics + Journalism = Data Journalism ?

Statistics+journalism=data journalism is not the full truth. The equation may make sense because statistics are the most important source for data journalism. But data journalism needs more than statistics and classic journalism: finding the story behind the data coupled with know how in specific tools (analysis, visualising) lead to the storytelling data journalism needs.

To get an idea what data journalism means and what skills are needed a free MOOC with well-known experts will be offered starting next year.


‘In this course we will provide you with the essential concepts, techniques and skills you need to effectively work with data and produce compelling data stories under tight deadlines.’


Target Group Statisticians

One target group of this course are statisticians. Because storytelling or some journalistic skills are important also for statisticians in order to explain the data and – last but not least –  to demonstrate the importance of statistical data.



Modules (details from the course program)

The modules of the MOOC cover several aspects:

  1. Data journalism in the newsroom

    This module is an introduction to data journalism. It shows what data journalism is, how it works on a busy news desk and what skills you need to know to practise it.

    Instructor: Simon Rogers, Data Editor, Twitter and former editor of the Guardian’s award-winning Datablog.

  2. Finding data to support stories

    This module deals with the range of skills that journalists use to obtain data. This includes setting up alerts to regular sources of information, simple search engine techniques that can save hours of time and using laws in your own and other countries.

    Instructor: Paul Bradshaw, Head of the Online Journalism MA at Birmingham City University, and Visiting Professor at City University’s School of Journalism in London.

  3. Understanding your data I: Finding story ideas with data analysis

    This module focuses on using spreadsheets and basic statistics to find patterns in data that will reveal story ideas and add evidence to the resulting stories.

    Instructor: Steve Doig, Knight Chair in Journalism at the Walter Cronkite School of Journalism & Mass Communication of Arizona State University, and Pulitzer Prize winner.

  4. Understanding your data II: Dealing with messy data

    This module addresses messy data – data that needs to be organised before it can be used. It covers the so-called ‘cleaning’ process, at the end of which the dataset can be analysed using techniques from Module 3.

    Instructor: Nicolas Kayser-Bril, Co-founder and Head at data journalism startup Journalism++.

  5. Telling stories with visualisation

    This module deals with how to transform data into stories, infographics and interactive visualizations: the best practices and the principles of graphic design that a journalist needs to know.

    Instructor: Alberto Cairo, Professor of the Professional Practice at the University of Miami, and author of The Functional Art: An Introduction to Information Graphics and Visualization.